Network Traffic Engineering

September 11, 2015

by Matt Conran Blog

Network Traffic Engineering

In today's interconnected world, network traffic engineering plays a crucial role in optimizing the performance and efficiency of computer networks. This blog post aims to provide a comprehensive overview of network traffic engineering, its importance, and the techniques used to manage and control traffic flow.

Network traffic engineering efficiently manages and controls the flow of data packets within a computer network. It involves analyzing network traffic patterns, predicting future demands, and implementing strategies to ensure smooth data transmission.

Bandwidth allocation is a critical aspect of traffic engineering. By prioritizing certain types of data traffic, such as VoIP or video streaming, network engineers can ensure optimal performance for essential applications. Quality of Service (QoS) mechanisms, such as traffic shaping and prioritization, allow for efficient bandwidth allocation, reducing latency and packet loss.

Load balancing distributes network traffic across multiple paths or devices, optimizing resource utilization and preventing congestion. Network traffic engineering employs load balancing techniques, such as Equal-Cost Multipath (ECMP) routing and Dynamic Multipath Optimization (DMPO), to distribute traffic intelligently. This section will discuss load balancing algorithms and their role in traffic optimization.

QoS plays a crucial role in network traffic engineering by prioritizing certain types of traffic over others. Through QoS mechanisms such as traffic shaping, prioritization, and bandwidth allocation, critical applications can receive the necessary resources while preventing congestion from affecting overall network performance.

Routing protocols like OSPF (Open Shortest Path First) and BGP (Border Gateway Protocol) play a vital role in traffic engineering. By selecting optimal paths based on metrics like bandwidth, delay, and cost, these protocols adapt to changing network conditions and direct traffic along the most efficient routes.

Conclusion: Network traffic engineering is an indispensable discipline for managing the complexities of modern networks. By implementing effective traffic monitoring, QoS mechanisms, load balancing, and routing protocols, organizations can optimize network performance, improve user experience, and ensure seamless connectivity in the face of evolving traffic patterns and demands.

Matt Conran

Highlights: Network Traffic Engineering

Generic Traffic Engineering

Network traffic engineering involves optimizing and managing traffic flows to enhance overall performance. It encompasses various techniques and strategies for controlling and shaping the flow of data packets, minimizing congestion, and maximizing network efficiency.

Network traffic engineering involves analyzing, monitoring, and controlling network traffic to achieve desired performance levels. It aims to maximize efficiency, minimize congestion, and optimize resource utilization. Network traffic engineering ensures seamless communication and reliable connectivity by intelligently managing data flows.

a) Traffic Analysis: This technique involves studying traffic patterns, identifying bottlenecks, and analyzing network behavior. Network engineers can make informed decisions to enhance performance and mitigate congestion by understanding the data flow dynamics.

b) Quality of Service (QoS): QoS mechanisms prioritize different types of traffic based on predefined criteria. This ensures critical applications receive sufficient bandwidth and low-latency connections while less important traffic is appropriately managed.

c) Load Balancing: Load balancing distributes network traffic across multiple paths or devices, preventing resource overutilization and congestion. It optimizes available capacity, ensuring efficient data transmission and minimizing delays.

Traffic Engineering with Routing protocols

Routing protocol traffic engineering is the art of intelligently managing network traffic flow. It involves the manipulation of routing paths to achieve specific objectives, such as minimizing latency, maximizing bandwidth utilization, or enhancing network resilience. By strategically steering traffic, network administrators can overcome congestion, bottlenecks, and other performance limitations.

Traffic Engineering with OSPF: OSPF (Open Shortest Path First) is a widely used routing protocol that supports traffic engineering capabilities. It allows network administrators to influence traffic paths by manipulating link metrics, enabling the establishment of preferred routes and load balancing across multiple links.

MPLS Traffic Engineering: Multiprotocol Label Switching (MPLS) is another powerful tool in traffic engineering. By assigning labels to network packets, MPLS enables the creation of explicit paths that bypass congested links or traverse paths with specific quality of service (QoS) requirements. MPLS traffic engineering provides granular control and flexibility in routing decisions.

BGP Traffic Engineering: Border Gateway Protocol (BGP) is primarily used in large-scale networks and internet service provider (ISP) environments. BGP traffic engineering allows network operators to manipulate BGP attributes to influence route selection and steer traffic based on various criteria, such as AS path length, local preference, or community values.

Example Technologies: Network Traffic Engineering Tools

Network Monitoring and Analysis: Network monitoring tools, like packet sniffers and flow analyzers, provide valuable insights into traffic patterns, bandwidth utilization, and performance metrics. These tools help network engineers identify bottlenecks, analyze traffic behavior, and make informed decisions for traffic optimization.

Software-defined networking (SDN): SDN decouples network control from the underlying hardware, allowing centralized management and programmability. With SDN, traffic engineering tasks can be automated, and policies can be dynamically adjusted based on real-time traffic conditions. This flexibility and agility enable efficient traffic engineering in complex networks.

Software-defined networking (SDN) revolutionizes traditional network architecture by separating the control plane from the data plane. SDN enables centralized network management and programmability, empowering traffic engineers to dynamically control and shape network traffic.

Network Flow Model

In a computer network, an important function is to carry traffic efficiently, given the routing paradigm in place. Traffic engineering achieves this efficiency. Network flow models are used for network traffic engineering and can help determine routing decisions. Network Traffic engineering (TE) is the engineering of paths that can carry traffic flows that vary from those chosen automatically by the routing protocol(s) used in that network.

Therefore, we can engineer the paths that better suit our application. We can do this in several ways, such as standard IP routing, MPLS, or OpenFlow protocol. When considering network traffic engineering and MPLS OpenFlow, let’s start with the basics of traffic engineering and MPLS networking.

Traffic engineering is not an MPLS-specific practice; it is a general practice. Implementing traffic engineering can be as simple as tweaking IP metrics on interfaces or as complex as running an ATM PVC full-mesh and optimizing PVC paths based on traffic demands. Using MPLS, traffic engineering techniques (like ATM PVC placement) are merged with IP routing techniques to achieve connection-oriented traffic engineering. With MPLS, traffic engineering is just as practical as with ATM, but without some drawbacks of IP over ATM.

Decoupling Routing and Forwarding

A hop-by-hop forwarding paradigm is used in IP routing. When an IP packet arrives at a router, it is checked for the destination address in the IP header, a route lookup is performed, and the packet is forwarded to the next hop. The packet is dropped if there is no route. Each hop repeats this process until the packet reaches its destination. Nodes in MPLS networks also forward packets hop by hop, but this forwarding is based on fixed-length labels. MPLS applications such as traffic engineering are enabled by this ability to decouple packet forwarding from IP headers.

Better Integration of the IP and ATM Worlds

There was a clash between IP and ATM as soon as they were introduced. Despite being standardized, IP has always been viewed as a sideshow to ATM. Since it became apparent that our PCs and wristwatches would not run ATM stacks, attempts have been made to map IP onto ATM. In previous attempts to map IP to ATM, the main drawback was that they either attempted to separate the two worlds (carrying IP over ATM VCs) or tried to integrate IP and ATM with mapping services (such as ATM Address Resolution Protocol [ARP] and Next-Hop Resolution Protocol [NHRP]). Despite its usefulness, IP over ATM VCs (also known as the overlay model) has scalability limitations. The network is more vulnerable to failure when mapping servers are used.

Example Technology: Next-Hop Resolution Protocol

NHRP, or Next Hop Resolution Protocol, is vital in dynamic address resolution. It enables efficient communication between devices in a network by mapping logical IP addresses to physical addresses. By doing so, NHRP bridges the gap between network layers, ensuring seamless connectivity.

The operation of NHRP involves various components working in tandem. These components include the Next Hop Server (NHS), Next Hop Client (NHC), and Next Hop Forwarder (NHF). Each element performs specific tasks, such as address resolution, maintaining mappings, and forwarding packets. Understanding the roles of these components is critical to comprehending NHRP’s functionality.

Implementing NHRP offers numerous benefits in networking environments. First, it enhances network scalability, allowing devices to discover and connect dynamically. Second, NHRP improves network performance by reducing the burden on routers and enabling direct communication between devices. Third, it enhances network security by providing a secure mechanism for address resolution.

NHRP is used in various scenarios. One everyday use case is Virtual Private Networks (VPNs), where NHRP enables efficient communication between remote sites. It is also employed in dynamic multipoint virtual private networks (DMVPNs) to establish direct tunnels between multiple sites dynamically. These use cases highlight the versatility and significance of NHRP in modern networking.

MPLS and Traffic Engineering

The applications MPLS enables will motivate you to deploy it in your network. Traditional IP networks are either incapable of supporting these applications or are challenging to implement. Traffic engineering and MPLS VPNs are examples of such applications. This book is about the latter. In the sections below, we will discuss MPLS’s main benefits:

Routing and forwarding can be decoupled.
IP and ATM integration should be improved.
Providing the basis for building next-generation network applications and services, such as MPLS VPNs and traffic engineering

MPLS Traffic Engineering (MPLS TE)

IP class-of-service differentiation and ATM traffic engineering capabilities are combined in MPLS TE. A Label-Switched Path (LSP) enables you to construct a network and forward traffic down it.

As with ATM VCs, an MPLS TE LSP (a TE tunnel) enables the headend to control the path traffic takes to a particular destination. This method allows traffic to be forwarded based on various criteria rather than just the destination address.

Due to MPLS TE’s inherent nature, ATM VCs and other overlay models do not suffer from flooding problems like MPLS TE. To construct a routing table with MPLS TE LSPs without forming a full mesh of routing neighbors, MPLS TE uses an autoroute mechanism (unrelated to the WAN switching circuit-routing protocol of the same name).

In the same way ATM reserves bandwidth for LSPs, MPLS TE does the same when it builds LSPs. If you reserve bandwidth for an LSP, your network becomes a consumable resource. As new LSPs are added, TE-LSPs can find paths across the network with bandwidth available to reserve.

The Role of Traffic Analysis

Traffic analysis is a fundamental aspect of network traffic engineering. By analyzing network traffic patterns, administrators gain insights into peak usage times, identify bottlenecks, and make informed decisions regarding network resource allocation. This data-driven approach allows for proactive network management and optimization.

Related: You may find the following posts helpful for pre-information:

MPLS OpenFlow. Key Network Traffic Engineering Discussion Points:	Introduction to network traffic engineering and what is involved. Highlighting the different components of an MPLS network and how they work. MPLS traffic engineering (TE). Controller-based networking and its advantages. Discussing a predictable Traffic Engineering solution.

Back to Basics: Network traffic engineering

Traffic Engineering	Main Traffic Engineering Components Network Traffic Engineering Optimal Resource Utilization Enhanced Quality of Service (QoS) Scalability Example: MPLS TE

Importance of Network Traffic Engineering

Efficient network traffic engineering is essential for several reasons:

1. Optimal Resource Utilization: Traffic engineering balances network resources to minimize congestion and maximize bandwidth utilization, improving network performance.

2. Enhanced Quality of Service (QoS): Traffic engineering techniques prioritize critical applications, ensuring they receive the necessary bandwidth and reduce latency, improving user experience and customer satisfaction.

3. Scalability: With proper traffic engineering, networks can accommodate increased traffic demands, scalability, and future growth without significant performance degradation.

Techniques Used in Network Traffic Engineering

Here are some commonly used techniques in network traffic engineering:

1. Traffic Monitoring and Analysis: Network administrators employ tools to monitor and analyze traffic patterns, helping them identify bottlenecks, congestion points, and potential network vulnerabilities.

2. Traffic Shaping: Traffic shaping involves regulating network traffic flow to optimize performance. It can prioritize certain types of traffic, delay less critical traffic, and prevent data bursts that may overload network resources.

3. Load Balancing: Load balancing distributes network traffic across multiple paths or devices, preventing congestion and ensuring efficient use of available resources.

4. Quality of Service (QoS): QoS mechanisms prioritize specific types of traffic, ensuring that critical applications receive the necessary resources and reduce latency.

5. Traffic Engineering Protocols: Network engineers utilize RSVP (Resource Reservation Protocol) and MPLS (Multiprotocol Label Switching) to manage network traffic and allocate resources effectively and dynamically.

1st Lab Guide: MPLS Forwarding

In the following guide, we have an MPLS network. MPLS networks have devices with different roles. So, we have the core node called the “P” provider and the “PE” provider edge nodes. The beauty of MPLS forwarding is that we can have scale in the network’s core. The P nodes do not need customer routes from the CE devices. These are usually carried out in BGP.

Note:

However, with an MPLS network, we have MPLS forwarding between the loopbacks. Notice the diagram below. The loopback addresses 2.2.2.2/32 and 4.4.4.4/32 belong to the PE nodes. The P node is entirely unaware of any BGP routing.

Knowledge Check: IntServ and RSVP

Quality of Service (QoS) can be measured in three ways:

Best Effort (don’t use QoS for traffic that doesn’t need special treatment.)
DiffServ (Differentiated Services)
IntServ (Integrated Services)

DiffServ implements QoS by classifying IP packets based on their ToS byte or hop by hop. INTSERV is entirely different; it’s a signaling process where network flows can request a specific bandwidth and delay. RFC 1633 describes two components of IntServ:

Resource reservation
Admission control

Reserved resources notify the network that a certain amount of bandwidth and delay is needed for a particular flow. When the reservation is successful, a network component (primarily routers) reserves bandwidth and delay. Reservations are permitted or denied by admission control. We cannot guarantee any service without allowing all flows to make reservations.

RSVP path messages are used when a host requests a reservation. This message is passed along the route on the way to the destination. A router will forward a message when it can guarantee the bandwidth/delay required. An RSVP resv message will be sent once it reaches the destination. In the opposite direction, the same process will occur. Upon receiving the reservation message from the host, each router will check if it has enough bandwidth/delay for the flow and forward it to the source of the reservation.

While this might sound nice, IntServ is challenging to scale…each router must keep track of each reservation for each flow. Is there a problem if a particular router does not support Intserv or its reservation information is lost? We primarily use RSVP for MPLS traffic engineering and DiffServ for QoS implementations.

Traffic Engineering: Inbound and Outbound

Before you can understand how to use MPLS to do traffic engineering, you must understand what traffic engineering is. So, we have network engineering that manipulates your network to suit your traffic. You make the most reasonable predictions about how traffic will flow across your network and then order the right components.

Then we have traffic engineering. Network traffic engineering is manipulating traffic to fit your network. Traffic engineering is not MPLS-specific but a general practice among all networking and security technologies. It could be a simple or complex implementation. Something as simple as tweaking IP metrics on the interface can be implemented in its simplest form for traffic engineering. Then, we have traffic engineering specific to MPLS.

2nd Lab Guide: MPLS TE

In this lab, we will examine MPLS TE with ISIS configuration. Our MPLS core network consists of PE1, P1, P2, P3, and PE2 routers. The CE1 and CE2 routers use regular IP routing. All routers are configured to use IS-IS L2.

Tip: There are four main items we have to configure:

Enable MPLS TE support:
- Globally
- Interfaces
Configure IS-IS to support MPLS TE.
Configure RSVP.
Configure a tunnel interface.

Understanding MPLS and MPLS forwarding

MPLS is the de facto technology for service provider WAN networks. Its scalable architecture moves complexity and decision-making to the network’s edges, leaving the core to label switch packets efficiently. The PE nodes sit at the edge and perform path calculations and encapsulations. The P nodes sit in the core and label switch packets. They only perform MPLS switching and have no visibility of customer routes.

Edge MPLS routers map incoming packets into forwarding equivalence classes (FEC) and use a different label-switched path (LSP) for each forwarding class. Keeping the network core simple enables scalable network designs. Many of today’s control planes encompass a distributed architecture and can make forwarding decisions independently.

MPLS control plane still needs a distributed IGP (OSPF and ISIS) to run in the core and a distributed label allocation protocol (LDP) to label packets. Still, it shifted how we think of control planes and distributed architectures. MPLS reduced the challenges of some early control plane approaches but proposes challenges by not having central visibility, especially for traffic engineering (TE).

MPLS forwarding — Diagram: MPLS Forwarding. The source is NetworkInterview.

Example Technology: DMVPN Phase 3 Traffic Manipulation

DMVPN Phase 3 is the third and final phase of a Dynamic Multipoint Virtual Private Network DMVPN setup. This phase is focused on implementing the DMVPN tunnel and enabling dynamic routing. The tunnel is built between multiple network points, allowing communication between them.

In DMVPN Phase 1, the spoke devices rely on the configured tunnel destination to identify where to send the encapsulated packets. Phase 3 DMVPN uses mGRE tunnels and depends on NHRP redirect and resolution request messages to determine the NBMA addresses for destination networks.

Packets flow through the hub in a traditional hub-and-spoke manner until the spoke-to-spoke tunnel has been established in both directions. Then, as packets flow across the hub, the hub engages NHRP redirection to find a more optimal path with spoke-to-spoke tunnels.

NHRP Routing Table Manipulation

NHRP tightly interacts with the routing/forwarding tables and installs or modifies routes in the Routing Information Base (RIB), also known as the routing table, as necessary. If an entry exists with an exact match for the network and prefix length, NHRP overrides the existing next hop with a shortcut. The original protocol is still responsible for the prefix, but the percent sign (%) indicates overwritten next-hop addresses in the routing table.

3rd Lab Guide: DMVPN Phase 3

The following example shows DMVPN Phase 3 running on the network.

DMVPN Phase 3 is the latest iteration of the DMVPN technology, offering enhanced scalability and flexibility compared to its predecessors. It builds upon the foundation of Phase 1 and Phase 2, incorporating improvements that address the limitations of these earlier versions.

One of the critical features of DMVPN Phase 3 is the addition of a hub-and-spoke network topology. This allows for a centralized hub connecting multiple remote spokes, creating a dynamic and efficient network infrastructure. The hub is a central point for all spokes, enabling secure communication. In our case below, R11 is the hub, and R31 and R41 are the spokes.

Note:

Once the hub site receives traffic indicating spoke to spoke traffic, it sends back a “Traffic Indication” message. Notice the output from the debug command below. Via NHRP, the spoke knows a better path to reach the other spoke, not via the hub. The spoke then proceeds to build spoke-to-spoke tunnels.

Network Traffic Engineering and MPLS

MPLS was very successful, and significant service provider networks could support many customers by employing MPLS-style architecture. End-to-end Label Switch Paths (LSP) are extended to interconnect multiple MPLS service providers, route reflectors, and BGP confederations for large-scale deployments and complexity reduction.

However, no matter how scalable the MPLS architecture could be, you can’t escape the fact that Inter-DC circuit upgrades are time-consuming and expensive. To help alleviate this, MPLS providers introduced MPLS Traffic engineering (TE). TE moves traffic to other parts of the network to underutilized sections.

While simple TE can be done with IGP metrics, they don’t satisfy unique traffic class requirements. Therefore, provider networks commonly deploy MPLS RSVP/ TE. This type of TE enhances IGP metric tuning, allowing engineers to forward core traffic over non-shortest paths. The non-shorted path is used to avoid network “hot spots.” Since the traffic is now moved to other underutilized network parts, it prevents the lengthy process of upgrading congested core links. MPLS TE distributes traffic optimally across a network. “MPLS RSVP/ TE is a widely adopted and well-defined technology. Can SDN and OpenFlow do a better job?”

Holistic visibility – Controller-based networking

MPLS/TE is a distributed architecture. There is no real-time global view of the end-to-end network path. The lack of a global view may induce incorrect traffic engineering decisions, lack of predictability, and deterministic scheduling of LSPs.

Some tools work with MPLS TE to create a holistic view, but they are usually expensive and do not offer a “real-time” picture. They often make an offline topology. They also don’t change the fact that MPLS is a distributed architecture.

The significant advantage of a centralized SDN and OpenFlow framework, commonly called MPLS OpenFlow, is that you have a holistic view of the network, controller-based networking. The centralized software sits on the controllers, analyzing and controlling the production network forwarding paths. It has a real-time network view and gains insights into various network analytics about link congestion, delay, latency, drops, and other performance metrics.

MPLS OpenFlow can push down rules to the nodes per-flow basis, offering a granular approach to TE. The traditional TE mechanism is challenging in achieving a per-flow TE state. OpenFlow’s finer granularity is also evident in service insertion use cases. In addition, OpenFlow 1.4 supports better statistics that give you visibility into application performance.

This metric and a central viewpoint can only enhance traffic engineering decisions. Let’s face it: MPLS RSVP/TE, while widely deployed, involves several control plane protocols. All these protocols need to interact and work together.

The OpenFlow MPLS protocol steers traffic over MPLS using OpenFlow.

You can direct traffic from OpenFlow networks over MPLS LSP tunnel cross-connects and logical tunnel interfaces. By stitching OpenFlow interfaces to MPLS label-switched paths (LSPs), you can direct OpenFlow traffic onto MPLS networks. In addition, through MPLS LSP tunnel cross-connects between interfaces and LSPs, you can connect the OpenFlow network to a remote network by creating MPLS tunnels that use LSPs as conduits.

Network state vs. Centralized end-to-end visibility

RSVP requires that some state is stored on the Label Switch Router (LSR). The state is always bad for a network and imposes control plane scalability concerns. The network state is also a target for attack. Hierarchical RSVP was established to combat the state problem, but in my opinion, it adds to network complexity. All these kludges become an operational nightmare and require skilled staff to design, implement, and troubleshoot.

Removing MPLS signaling protocols from the network and the state they need to maintain eliminates some of the scale concerns with MPLS TE. Distributed control planes must maintain many tables and neighbor relationships (LSDB and TED). They all add to network complexity.

Predictable and deterministic TE solution

Using SDN and OpenFlow for traffic engineering provides a more predictable and deterministic TE solution. By informing the OpenFlow controller that you want the traffic redirected toward a specific MAC address, the necessary forwarding entries are programmed and automatically appear across the path. NETCONF and MPLS-TP are possibilities, but they operationally cause problems and don’t alleviate the distributed signaling protocols.

Having a central controller view, the contents of the network allow for particular network touchpoints. New features are implemented in the software and pushed down to the individual nodes. Similar to all SDN architectures, fewer network touchpoints increase network agility. The box-by-box and manual culture is slowly disappearing.

Challenges and Future Trends

Network traffic engineering faces several challenges, including ever-increasing data volumes, evolving network architectures, and the rise of new technologies such as cloud computing and the Internet of Things (IoT). However, emerging trends like Software-Defined Networking (SDN) and Artificial Intelligence (AI) are promising to address these challenges and optimize network traffic.

Summary: Network Traffic Engineering

Understanding Network Traffic Engineering

Network traffic engineering analyzes and manipulates traffic to enhance performance and meet specific objectives. It involves various techniques such as traffic shaping, route optimization, and load balancing. By intelligently managing the flow of data packets, network administrators can ensure optimal utilization of available bandwidth and minimize latency issues.

Traffic Engineering Techniques

Traffic Shaping

Traffic shaping is a technique used to control network traffic flow by enforcing predetermined bandwidth limits. It allows administrators to prioritize critical applications or services, ensuring smooth operation during peak traffic hours. By regulating the rate at which data packets are transmitted, traffic shaping helps prevent congestion and maintain a consistent user experience.

Route Optimization

Route optimization focuses on selecting the most efficient paths for data packets to travel across a network. Network engineers can determine the optimal routes that minimize delays and packet loss by analyzing various factors such as latency, bandwidth availability, and network topology. This ensures faster data transmission and improved overall network performance.

Load Balancing

Load balancing is a technique that distributes network traffic across multiple paths or devices, avoiding bottlenecks and optimizing resource utilization. By evenly distributing the workload, load balancers ensure that no single component is overwhelmed with traffic, thereby improving network efficiency and preventing congestion.

Benefits of Network Traffic Engineering

Enhanced Performance

By implementing traffic engineering techniques, network administrators can significantly enhance network performance. Reduced latency, improved throughput, and minimized packet loss contribute to a smoother and more efficient network operation.

Scalability and Flexibility

Network traffic engineering enables scalability and flexibility in network design. It allows for the efficient allocation of resources and the ability to adapt to changing traffic patterns and demands. This ensures that networks can handle increasing traffic volumes without sacrificing performance or user experience.

Effective Resource Utilization

Optimized network traffic engineering ensures that network resources are utilized effectively, maximizing the return on investment. By efficiently managing bandwidth and routing paths, organizations can avoid unnecessary expenses on additional infrastructure and improve overall cost-effectiveness.

Challenges and Considerations

While network traffic engineering offers numerous benefits, it also comes with its own set of challenges. Factors such as dynamic traffic patterns, evolving network technologies, and security considerations must be considered. Network administrators must stay updated with industry trends and continuously monitor and analyze network performance to address these challenges effectively.

Conclusion: Network traffic engineering is a critical discipline that ensures computer networks’ efficient and reliable functioning. By employing various techniques and protocols, network administrators can optimize resource utilization, enhance the quality of service, and pave the way for future network scalability. As technology evolves, staying updated with emerging trends and best practices in network traffic engineering will be crucial for organizations to maintain a competitive edge in today’s digital landscape.

OpenFlow and SDN Adoption

August 20, 2015

by Matt Conran Blog

OpenFlow and SDN Adoption

In the ever-evolving world of networking, new technologies and approaches continue to reshape the landscape. One such technology that has gained significant attention is OpenFlow, which forms the backbone of Software-Defined Networking (SDN). In this blog post, we will delve into the concept of OpenFlow and explore its growing adoption in the networking industry.

OpenFlow can be best described as a protocol that enables the separation of the control plane and the data plane in a network. Traditionally, network devices handled both the control and data forwarding aspects, leading to limited flexibility and scalability. With OpenFlow, the control plane is centralized in a controller, allowing for dynamic network management and programmability.

Benefits of OpenFlow: The adoption of OpenFlow brings forth a multitude of benefits. Firstly, it offers network administrators unprecedented control and visibility into the network, empowering them to efficiently manage traffic flows and implement changes on the fly. Additionally, OpenFlow promotes network programmability, enabling the development of innovative applications and services that can harness the full potential of the network infrastructure.

OpenFlow in Action: Numerous organizations and industries have recognized the potential of OpenFlow and have embraced it in their networks. For instance, data centers have leveraged OpenFlow to create virtual networks with enhanced security and improved resource allocation. Internet Service Providers (ISPs) have also adopted OpenFlow to optimize traffic routing and enhance network performance.

Challenges and Considerations: While OpenFlow holds great promise, it is not without its challenges. One of the primary concerns is ensuring interoperability across different vendors and devices, as OpenFlow relies on a standard set of protocols and features. Additionally, network security and policy enforcement must be carefully addressed to prevent unauthorized access and protect sensitive data.

In conclusion, OpenFlow and SDN adoption are revolutionizing the networking industry, offering unprecedented control, programmability, and scalability. As organizations continue to recognize the benefits of OpenFlow, we can expect to see further advancements and innovations in the realm of network management and infrastructure.

Matt Conran

Highlights: OpenFlow and SDN Adoption

Understanding OpenFlow

At its core, OpenFlow is a communications protocol that enables the separation of the control plane and the data plane in networking devices. It allows for the programmability and centralized control of network switches and routers. With OpenFlow, network administrators can dynamically manage traffic, define routing paths, and apply policies, all through a centralized controller.

Unveiling Software-Defined Networking (SDN)

SDN takes the concept of OpenFlow further by providing a framework for network management and configuration. It abstracts the underlying network infrastructure and allows for programmability and automation through a software-based controller. SDN architectures offer flexibility, scalability, and agility, making adapting to evolving network demands easier.

Benefits of OpenFlow and SDN

The combination of OpenFlow and SDN brings numerous benefits to network operators, administrators, and end-users. Firstly, it simplifies network management by providing a centralized view and control of the entire network. This simplification leads to enhanced network visibility, easier troubleshooting, and faster deployment of new services. Additionally, OpenFlow and SDN enable network virtualization, allowing for the creation of logical networks decoupled from the physical infrastructure.

Use Cases and Real-World Applications

OpenFlow and SDN have been found to be extensively used in various domains and industries. From data centers and cloud computing environments to enterprise networks and even telecommunications, the versatility of OpenFlow and SDN is undeniable. They enable dynamic traffic engineering, efficient load balancing, and improved network security. Furthermore, SDN has paved the way for network function virtualization (NFV), allowing the deployment of network services as software applications rather than dedicated hardware.

The Application Layer

As its name suggests, this layer includes network applications. Examples of these applications include communication applications, such as VoIP prioritization, and security applications, such as firewalls. Also included in this layer are utilities and network services.

Switches and routers traditionally handled these applications. SDN simplifies their management by offloading them. In addition, companies can save a lot of money by stripping down the hardware.

The Control Layer

Switches and routers are now controlled by a centralized control plane, which allows the network to be programmed. As an open-source network protocol, OpenFlow has become the industry standard despite Cisco’s OpenFlow variant.

The Infrastructure Layer

This layer includes data, switches, and routers. Traffic is moved according to flow tables. SDN leaves this layer essentially unchanged since routers and switches still move packets. The main difference is the centralization of traffic flow rules. However, the intelligence of vendor devices is not stripped away. The API provides centralized control of SDN for large network providers to protect their intellectual property. However, the cost of generic packet-forwarding devices is much lower than traditional networking equipment.

A Programmable Network

Developers have made it possible for network administrators to create “slices” that allow generic networking hardware to support multiple configurations by adding a virtualization layer between the control system and the hardware layer. It resembles how a hypervisor can run a virtual machine (VM) on a single server. Using SDN, an administrator can create different rules and applications for various groups of users.

Because most applications are not installed on the devices, SDN enables the network to appear as one big switch/router. There could be three devices on the network or 30,000. They are all the same as centralized applications. (Some applications are just nodes on the network.) Therefore, upgrades, changes, additions, and configurations are much more accessible.

The role of OpenFlow

Firstly, the basis of the SDN adoption report is the OpenFlow protocol, an existing technology derived from academic labs. Its origins can be traced back to 2006 when Martin Casado, part of the “Clean Slate” program, developed Ethane. They were trying to figure out ways to manage the network states via a centrally managed global policy.

The idea that networks are dynamic and non-symmetrical poses challenges in keeping track of their state to enforce programmability. The program has stopped but produced several follow-up programs, including OpenFlow and SDN.

SDN OpenFlow is not revolutionary new. Similar ideas have been available, and previous projects have tried to solve the same problems OpenFlow is trying to solve today. Besides the central viewpoint use case, whatever you can do with OpenFlow today is possible with Policy-Based Routing (PBR) and ACL. The problem is that these tools are clumsy and do not scale well.

You may find the following useful for pre-information:

SDN Adoption Report. Key SDN Adoption Discussion Points:	Introduction to SDN OpenFlow and what is involved. Highlighting the SDN architecture. Critical points on the virtual switching fabric. Technical details on the use of OSPF. Technical details for programming the forwarding paths. Final comments on SDN OpenFlow.

Back to basics with the SDN.

What is OpenFlow?

OpenFlow is an open standard that enables the separation of the control plane and the data plane in network devices. It allows network administrators to centrally control and manage the behavior of network switches and routers, resulting in increased network programmability, flexibility, and scalability. OpenFlow provides a standardized protocol that facilitates communication between the control and data planes, enabling the network to be programmed and controlled through software.

Understanding SDN Adoption:

SDN is a paradigm shift in network architecture that leverages OpenFlow and other technologies to virtualize and abstract network resources. With SDN, the control plane is decoupled from the underlying physical infrastructure, allowing network administrators to configure and manage networks dynamically through a centralized controller. This centralized control simplifies network operations, enhances automation, and creates innovative network services.

The use of APIs

Besides the network abstraction, the SDN architecture will deliver a set of APIs that streamline the implementation of standard network services. These network services include routing, security, access control, and traffic engineering. Consequently, we can achieve exceptional programmability, automation, and network control, enabling us to build highly scalable and flexible networks that readily adapt to changing business needs. Then, we have OpenFlow and the SDN story. OpenFlow is the first standard interface explicitly designed for SDN, providing high-performance and granular traffic control across multiple networking devices.

Benefits of OpenFlow and SDN Adoption:

The adoption of OpenFlow and SDN comes with numerous benefits for organizations of all sizes:

1. Enhanced Network Programmability: OpenFlow and SDN enable network administrators to program and control networks through software, making implementing new network services and policies easier.

2. Increased Flexibility and Scalability: SDN allows for dynamic network reconfiguration and resource allocation, ensuring networks can adapt to changing requirements and scale efficiently.

3. Centralized Network Management: With SDN, network administrators can manage and configure multiple network devices from a centralized controller, simplifying network operations and reducing the complexity of managing traditional networks.

4. Improved Network Security: SDN facilitates the implementation of granular security policies, enabling network administrators to quickly detect and respond to security threats, enhancing overall network security.

Challenges and Considerations:

While OpenFlow and SDN offer significant advantages, their adoption comes with a few challenges that organizations need to address:

1. Compatibility: Not all network devices and vendors fully support OpenFlow and SDN, requiring organizations to consider device compatibility carefully before implementation.

2. Skillset and Training: SDN introduces new concepts and requires network administrators to acquire skills and knowledge to deploy and manage SDN-based networks effectively.

3. Transition from Legacy Infrastructure: Migrating from traditional networking solutions to SDN-based architectures requires careful planning and a phased approach to minimize disruptions and ensure a smooth transition.

Starting Points for SDN Adoption

SDN Architectures and OpenFlow

SDN architectures and OpenFlow offer several advantages. You can influence traffic forwarding behavior at a more granular flow level. A holistic view instead of a partial view of distributed devices simplifies the network. Traffic engineering with SDN becomes easier to implement when you have a centralized view; this is how Google implemented SDN. Google has two network backbones: an Internet-facing backbone and a data center backbone.

They noticed that the cost/bit was not decreasing as the network grew. It was doing the opposite. Their solution was to implement a centralized controller and manage the WAN as a fabric, not as a collection of individual nodes.

SDN adoption report: Virtual switching fabric

SDN architectures allow networks to move from loosely coupled systems to a virtual switching fabric. One extensive flat virtualized network that appears and can be managed as a single switch has many operational advantages. The switch fabric consists of multiple physical nodes but behaves like one big switch. For example, a port on any underlying switch fabric nodes or virtual switch appears as a port to the single switching fabric.

The entire data plane becomes an abstraction. By employing this architecture, we manage the data plane as a whole entity instead of a set of loosely coupled connected devices. If we study existing networks, the control and data planes are distributed to the same locations. No central point controls individual nodes, resulting in complex cross-network interactions.

Open Shortest Path First (OSPF)

Open Shortest Path First (OSPF) calculates the shortest path tree from each node to every other node. Each OSPF neighbor must establish an adjacency and build and synchronize the link-state databases (LSB). The complexity can be reduced by designing OSPF areas with ABRs but by sacrificing some precision of route information. Imagine that every node reports and synchronizes its LSB to a central controller with an OSPF SDN application instead of individual nodes.

The controller can perform the Shortest Path First (SPF) calculation and directly update each node’s forwarding information base (FIB). The network now becomes programmable. While it does bring advantages, the laws of physics have not changed.

OpenFlow does not decrease latency or let you push more bits through a link. It does, however, let you better manage and control your network. It removes the box-by-box mentality and introduces automation and programmability.

Do you think OpenFlow will be derailed?

SDN OpenFlow has come up against some market adoption barriers, such as silicon challenges and numerous vendor-specific extensions. In addition, the lack of conformance tests has led to some inconsistencies. It depends on how you define it. To explain it, you need to know what it is not. It is not a controller or a forwarding switch but a communication between the two.

It has a distinct place in the SDN architecture and does not run anywhere except between the control (controller) and the data plane, such as the OVS bridge acting as the switch infrastructure. SDN OpenFlow is also not alone in this space; other technologies provide control and data plane communications, such as BGP, Open vSwitch Database Management Protocol (OVSDB), NETCONF, and Extensible Message and Presence Protocol (XMPP).

Juniper’s OpenContrail uses XMPP.

It is evolving, and emerging technologies are sometimes slow to adopt. For example, in the early days of Novell networks, there were 4-frame types. Likewise, OpenFlow is changing and adapting as time progresses. For example, the original version of OpenFlow did not have multiple flow tables; now, versions 1.3 and 1.4 have multiple tables with various actions and many additional features.

Will it be used for program forwarding paths instead of BGP?

Probably not, but it will augment BGP and other traditional technologies. It is not strictly a YES or NO answer as the SDN adoption falls into two buckets: one with OpenFlow and one without. Take the IPv6 adaptations as the IPv4 “replacement.” There was a “D” day of IPv4 address exhaustion, but IPv4 is still widely used. New “transition” mechanisms such as 6to4 and NAT64 are still widely deployed. It is the same with SDN and OpenFlow.

There will be ways to make traditional networks communicate with SDN and OpenFlow. BGP was invented as an EBGP, but people use EBGP Internal in their network. BGP is also used as an SDN control plane. It will be the case that you have controllers that provide automation and a holistic view but can speak BGP or OSPF to program the forwarding devices. SDN migrations will come incrementally, similar to what we see with IPv4 and IPv6

The lack of clarity in the controller space has limited OpenFlow’s progress. However, the controller market is consolidating now, which gives users a clear path forward. This emergence is a good thing and will move OpenFlow forward. Maintaining SDN applications on different controllers is a dead end, but now that OpenDaylight is emerging, we have controller unity.

A market with numerous open-source controllers would make SDN application development difficult. There will always be business drivers for proprietary controllers serving a particular niche and corner case problems the open community did not invest in. Even today, specialized UNIX platforms exist when you look at open Linux. Similarly, this adoption of technology will be evident for OpenFlow controllers.

The Future of OpenFlow and SDN:

The adoption of OpenFlow and SDN has gained significant momentum in recent years, and the future looks promising for these technologies. With the increasing demand for flexible, scalable, and programmable networks, OpenFlow and SDN are vital in deploying 5G networks, Internet of Things (IoT) applications, and network virtualization.

OpenFlow and SDN adoption revolutionizes network infrastructure, offering increased programmability, flexibility, and centralized management. While challenges exist, the benefits of OpenFlow and SDN far outweigh the drawbacks. As organizations continue to embrace digital transformation, OpenFlow and SDN will continue to shape the future of networking, enabling agile, scalable, and secure networks that can adapt to the evolving needs of modern businesses.

Summary: OpenFlow and SDN Adoption

In today’s rapidly evolving technological landscape, Software-Defined Networking (SDN) and OpenFlow have emerged as game-changing innovations revolutionizing the world of networking. This blog post delves into the intricacies of SDN and OpenFlow, exploring their capabilities, benefits, and their potential to reshape the future of networking.

Understanding SDN

SDN, short for Software-Defined Networking, is a paradigm that separates the control plane from the data plane, enabling centralized network management. Unlike traditional networking approaches, SDN decouples network control, making it programmable and agile. It empowers network administrators with unprecedented flexibility and control over their infrastructure.

Unveiling OpenFlow

At the core of SDN lies OpenFlow, a protocol that enables communication between the control and data planes. OpenFlow facilitates the flow of network packets, allowing administrators to define and manage network traffic dynamically. Providing a standardized interface promotes interoperability between different vendors’ networking equipment, fostering innovation and cost-effectiveness.

Benefits of SDN and OpenFlow

Enhanced Network Flexibility and Scalability: SDN and OpenFlow enable network administrators to adjust network resources dynamically, optimize traffic flow, and respond to changing demands. This flexibility and scalability empower organizations to adapt swiftly to evolving network requirements, ensuring efficient resource utilization.

Simplified Network Management: With SDN and OpenFlow, network administrators can centrally manage and orchestrate network devices, eliminating the need for manual configurations on individual devices. This centralized control simplifies network management, reduces human errors, and accelerates the deployment of new services.

Improved Network Security: SDN’s centralized control allows for better security management. Administrators gain granular control over network access, threat detection, and response by implementing security policies and protocols at the controller level. This enhanced security posture helps safeguard critical assets and data.

Data Center Networking: SDN and OpenFlow find extensive applications in data centers, where virtualization and cloud computing demand dynamic resource allocation and efficient traffic management. By abstracting network control, SDN facilitates seamless scalability, load balancing, and efficient utilization of data center resources.

Campus and Enterprise Networks: In campus and enterprise networks, SDN and OpenFlow enable administrators to manage and optimize network traffic, prioritize critical applications, and quickly respond to changing user demands. These technologies also facilitate network slicing, allowing organizations to create virtual networks tailored to specific requirements.

In conclusion, SDN and OpenFlow represent a paradigm shift in networking, offering immense potential for increased efficiency, scalability, and security. As organizations continue to embrace digital transformation, these technologies will play a pivotal role in shaping the future of networking. By decoupling network control and leveraging the power of programmability, SDN and OpenFlow empower administrators to build agile, intelligent, and future-ready networks.

OpenStack written on the keyboard button

Openstack Architecture in Cloud Computing

August 14, 2015

by Matt Conran Blog

OpenStack Architecture in Cloud Computing

Cloud computing has revolutionized businesses' operations by providing flexible and scalable infrastructure for hosting applications and storing data. OpenStack, an open-source cloud computing platform, has gained significant popularity due to its robust architecture and comprehensive services.

In this blog post, we will explore the architecture of OpenStack and how it enables organizations to build and manage their own private or public clouds.

At its core, OpenStack comprises several interconnected components, each serving a specific purpose in the cloud infrastructure. The architecture follows a modular approach, allowing users to select and integrate the components that best fit their requirements.

OpenStack architecture is designed to be modular and scalable, allowing businesses to build and manage their own private or public clouds. At its core, OpenStack consists of several key components, including Nova, Neutron, Cinder, Glance, and Keystone. Each component serves a specific purpose, such as compute, networking, storage, image management, and identity management, respectively.

Matt Conran

Highlights: OpenStack Architecture in Cloud Computing

What is OpenStack?

OpenStack is a comprehensive cloud computing platform that enables the creation and management of private and public clouds. It provides interrelated services, including computing, storage, networking, and more. OpenStack’s open-source nature fosters collaboration and innovation within the cloud community.

Cloud computing platforms such as OpenStack are free and open standards. Both public and private clouds use infrastructure-as-a-service (IaaS) to provide users with virtual servers and other resources. In a data center, a software platform controls diverse, multi-vendor pools of processing, storage, and networking resources. In addition to web-based dashboards, command-line tools, and RESTful web services are available to manage them.

NASA and Rackspace Hosting began developing OpenStack in 2010. The OpenStack Foundation, a non-profit corporation established in September 2012[3] to promote OpenStack software and its community, managed the project as of 2012. In 2021, the foundation announced it would be renamed the Open Infrastructure Foundation. By 2018, more than 500 companies had joined the project.

Key Features of OpenStack

OpenStack offers a wide range of features, making it a powerful and flexible cloud solution. Some of its notable features include:

1. Scalability and Elasticity: OpenStack allows users to scale their infrastructure up or down based on demand, ensuring optimal resource utilization.

2. Multi-Tenancy: With OpenStack, multiple users or organizations can securely share the same cloud infrastructure while maintaining isolation and privacy.

3. Modular Architecture: OpenStack’s modular design allows users to choose and integrate specific components per their requirements, providing a highly customizable cloud environment.

OpenStack: The cloud operation system

Cloud operating systems such as OpenStack are best viewed as public and private clouds, respectively. In this era of cloud computing, we are moving away from virtualization and software-defined networking (SDN). Any organization can build a cloud infrastructure using OpenStack without committing to a vendor. Despite being open source, OpenStack has the support of many heavyweights in the industry, such as Rackspace, Cisco, VMware, EMC, Dell, HP, Red Hat, and IBM. If a brand name acquires OpenStack, it won’t disappear overnight or lose its open-source status.

OpenStack is also an application and toolset that provides identity management, orchestration, and metering. Despite supporting several hypervisors, such as VMware ESXi, KVM, Xen, and Hyper-V, OpenStack is not a hypervisor. Thus, OpenStack does not replace these hypervisors; it is not a virtualization platform but a cloud management platform.

OpenStack is composed of many modular components, each of which is governed by a technical committee. OpenStack’s roadmap is determined by a board of directors driven by its community.

OpenStack Modularity

OpenStack is highly modular. Components provide specific services, such as instance management, image catalog management, network management, volume management, object storage, and identity management. A minimal OpenStack deployment can provision instances from images and connect them to networks. Identity management controls cloud access. Some clouds are only used for storage.

There is an object storage component and, again, an identity component. The OpenStack community does not refer to services by their functions, such as services, images, etc. Instead, these components are referred to by their nicknames. Server functions are officially called compute, but everyone calls them Nova. It’s pretty fitting since NASA co-founded OpenStack. Glance is the image service, Neutron is the network service, and Cinder is the volume service. Swift provides object storage, while Keystone includes identity management, which keeps everything together.

The role of decoupling

The key to cloud computing is decoupling virtual resources from physical ones. The ability to abstract processors, memory, etc., from the underlying hardware enables on-demand/elastic provisioning and increased efficiency. This abstraction process has driven the cloud and led to various popular cloud flavors such as IaaS – Infrastructure-as-as-Service, PaaS – Platform-as-as-Service, and SaaS – Software-as-as-Service, a base for OpenStack foundations.

The fundamentals have changed, and the emerging way of consuming I.T. ( compute, network, storage ) is the new “O.S.” for the data center in the cloud. The cloud cannot operate automatically and needs a management suite to control and deploy service-oriented infrastructures. Different companies deploy different teams that specialize only in managing cloud computing. Those without an in-house team get it outsourced by firms like Global Storage.

SDN Abstraction

These platforms rely on a new networking architecture known as software-defined networking. Traditional networking relies on manual administration, and its culture is based on a manual approach. Networking gear is managed box by box, and administrators maintain singular physical network hardware and connectivity. SDN, on the other hand, abstracts the network.

The switching infrastructure may still contain physical switch components but is managed like one switch. The data plane is operated as an entire entity rather than a loosely coupled connected device. SDN approach is often regarded as a prerequisite and necessary foundation for scalable cloud computing.

Related: You may find the following post of interest:

Openstack Architecture in Cloud Computing. Key Openstack Architecture in Cloud Computing Discussion Points:	Introduction to OpenStack architecture in cloud computing and what is involved. Highlighting the components of cloud computing. Critical points on OpenStack foundations and operations. Technical details on the use of APIs. Technical details for the OpenStack deployment details.

Back to Basics: Cloud Adoption.

The adoption of cloud technology has transformed how companies run their IT services. By leveraging new strategies for resource use, several cloud solutions came into play with different categories: private, public, hybrid, and community.

OpenStack falls into the private cloud category. However, deploying OpenStack is still tricky, requiring a good understanding of its beneficial returns to a given organization regarding automation, orchestration, and flexibility.

The New Data Center Paradigm

n cloud computing, infrastructure services such as Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) are provided. Agility, speed, and self-service are the challenges the public cloud sets. Most companies have expensive IT systems, which they have developed and deployed over the years, but these systems are siloed and require human intervention. As public cloud services become more agile and faster, IT systems struggle to keep up. Today’s agile service delivery environment may make the traditional data center model and siloed infrastructure unsustainable. To achieve next-generation data center efficiency, enterprise data centers must focus on speed, flexibility, and automation.

Fully Automated Infrastructure

Admins and operators can deploy fully automated infrastructures with a software infrastructure within a minute. Next-generation data centers reduce infrastructure to a single, significant, agile, scalable, and automated unit. The result is an infrastructure that is programmable, scalable, and multi-tenant-aware. In this regard, OpenStack stands out as the next generation of data center operating systems. Several sizeable global cloud enterprises, such as VMware, Cisco, Juniper, IBM, Red Hat, Rackspace, PayPal, and eBay, have benefited from OpenStack. Many are running a private cloud based on OpenStack in their production environment. Your IT infrastructure should use OpenStack if you wish to be a part of an innovative, winning cloud company.

The main components of OpenStack are:

While different services cater to various needs, they follow a common theme in their design:

In OpenStack, Python is used to develop most services, making it easier for them to be developed rapidly.
REST APIs are available for all OpenStack services. The APIs are the primary communication interfaces for other services and end users.
Different components may be used to implement the OpenStack service. A message queue communicates between the service components and has several advantages, including queuing requests, loose coupling, and load distribution.

1. Nova: Nova is the compute service responsible for managing and provisioning virtual machines (VMs) and other instances. It provides an interface to control and automate the deployment of instances across multiple hypervisors.

2. Neutron: Neutron is a networking service that enables the creation and management of virtual networks within the cloud environment. It offers a range of networking options, including virtual routers, load balancers, and firewalls, allowing users to customize their network configurations.

3. Cinder: Cinder provides block storage to OpenStack instances. It allows users to create and manage persistent storage volumes, which can be attached to cases for data storage. Cinder supports various storage backends, including local disks and network-attached storage (NAS) devices.

4. Swift: Swift is an object storage service that provides scalable and durable storage for unstructured data. It enables users to store and retrieve large amounts of data, making it suitable for applications that require high scalability and fault tolerance.

5. Keystone: Keystone serves as the identity service for OpenStack, providing authentication and authorization mechanisms. It manages user credentials and assigns access rights to the various components and services within the cloud infrastructure.

6. Glance: Glance is an image service that enables users to discover, register, and retrieve virtual machine images. It provides a catalog of images that can be used to launch instances, making it easy to create and manage VM templates.

7. Horizon: Horizon is the web-based dashboard for OpenStack, providing a graphical user interface (GUI) for managing and monitoring the cloud infrastructure. It allows users to perform administrative tasks like launching instances, managing networks, and configuring security settings.

These components work together to provide a comprehensive cloud computing platform that offers scalability, high availability, and efficient resource management. OpenStack’s architecture is designed to be highly modular and extensible, allowing users to add or replace components per their specific requirements.

Additional Details on OpenStack Components

Keystone

Architecturally, Keystone is the most straightforward service in OpenStack. OpenStack’s core component provides an identity service that enables tenant authentication and authorization. By authorizing communication between OpenStack services, Keystone ensures that the correct user or service can access the requested OpenStack service. Keystone integrates with numerous authentication mechanisms, including usernames, passwords, tokens, and authentication-based systems. It can also be integrated with existing backends like Lightweight Directory Access Protocol (LDAP) and Pluggable Authentication Module (PAM).

Swift

Swift is one of the storage services that OpenStack users can use. REST APIs provide access to its object-based storage service. Object storage differs from traditional storage solutions, such as file shares and block-based access, in that it treats data as objects that can be stored and retrieved. An overview of Object Storage can be summarized as follows. In the Object Store, data is split into smaller chunks and stored in separate containers. A cluster of storage nodes maintains redundant copies of these containers to provide high availability, auto-recovery, and horizontal scalability.

Cinder

Another way to provide storage to OpenStack users may be to use the Cinder service. This service manages persistent block storage, which provides block-level storage for virtual machines. Virtual machines can use Cinder raw volumes as hard drives.

Some of the features that Cinder offers are as follows:

Volume management: This allows the creation or deletion of a volume
Snapshot management: This allows the creation or deletion of a snapshot of volumes
Attaching or detaching volumes from instances
Cloning volumes
Creating volumes from snapshots
Copy of images to volumes and vice versa

Like Keystone services, Cinder features can be delivered by orchestrating various backend volume providers, such as IBM, NetApp, Nexenta, and VMware storage products, through configurable drivers.

Manila

As well as the blocks and objects we discussed in the previous section, OpenStack has had a file-share-based storage service called Manila since the Juno release. Storage is provided as a remote file system. Unlike Cinder, it is similar to the Storage Area Network (SAN) service as opposed to the Network File System (NFS) we use on Linux. The Manila service supports NFS, SAMBA, and CIFS as backend drivers. The Manila service orchestrates shares on the share servers.

Glance

An OpenStack user can launch a virtual machine from the Glance service based on images and metadata. Depending on the hypervisor, various image formats are supported. With Glance, you can access images for KVM/Qemu, XEN, VMware, Docker, etc.

When you’re new to OpenStack, you might wonder, What’s the difference between Glance and Swift? Both handle storage. How do they differ? What is the need for such a solution?

Swift is a storage system, whereas Glance is an image registry. In contrast, Glance keeps track of virtual machine images and their associated metadata. Metadata can include kernels, disk images, disk formats, etc. Glance uses REST APIs to make this information available to OpenStack users. Images can be stored in Glance utilizing a variety of backends. Directories are the default approach, but other methods, such as NFS and Swift, can be used in massive production environments.

In contrast, Swift is a storage system. This solution allows you to store data such as virtual disks, images, backup archiving, and more.

As an image registry, Glance serves as a resource for users. Glance focuses on an architectural approach to storing and querying image information via the Image Service API. In contrast, storage systems typically offer highly scalable and redundant data stores, whereas Glance allows users (or external services) to register virtual disk images. You, as a technical operator, must find the right storage solution at this level that is cost-effective and performs well.

OpenStack Features

- Scalability and Elasticity

OpenStack’s architecture enables seamless scalability and elasticity, allowing businesses to allocate and manage resources dynamically based on their needs. By scaling up or down on demand, organizations can efficiently handle periods of high traffic and optimize resource utilization.

- Multi-Tenancy and Isolation

One of OpenStack’s standout features is its robust multi-tenancy support, which enables the creation of isolated environments for different users or projects within a single infrastructure. This ensures enhanced security, privacy, and efficient resource allocation across various departments or clients.

- Flexible Deployment Models

OpenStack offers a variety of deployment options, including private, public, and hybrid clouds. This flexibility allows businesses to choose the most suitable model based on their specific requirements, whether maintaining complete control over their infrastructure or leveraging the benefits of public cloud providers.

- Comprehensive Service Catalog

With an extensive service catalog, OpenStack provides a wide range of services such as compute, storage, networking, and more. Users can quickly provision and manage these services through a unified dashboard, simplifying the management and deployment of complex infrastructure components.

- Open and Vendor-Agnostic

OpenStack’s open-source nature ensures vendor-agnosticism, allowing organizations to choose hardware, software, and services from various vendors. This eliminates the risk of vendor lock-in and fosters a competitive market, driving innovation and cost-effectiveness.

OpenStack Architecture in Cloud Computing

OpenStack Fundations and Origins

OpenStack Foundations is a software platform for orchestrating and automating data center environments. It provides APIs enabling users to create virtual machines, network topologies, and scale applications to business requirements. It does not just let you control your cloud; you may make it available to customers for unique self-service and management.

It’s a collection of projects (each with a specific mission) to create a shared cloud infrastructure maintained by a community. It enables any organization type to build its public or private cloud stack. A key differentiator from OpenStack and other platforms is that it’s open-source, run by an independent community continually updating and reviewing publicly accessible information. The key to its adoption is that customers do not fear vendor lock-in.

The pluggable framework is supported by multiple vendors, allowing customers to move away from the continuous path of yearly software license renewal costs. There is real momentum behind it. The lead-up to OpenStack and cloud computing started with Amazon Web Service (AWS) in 2006. They offered a public IaaS and virtual instances with an API. However, there was no SLA or data guarantee, so research academies mainly used it.

NASA and Rackspace

Historically, OpenStack was founded by NASA and Rackspace. NASA was creating a project called Nebula, which was used for computing. Rackspace was involved in a storage project ( object storage platform ) called Cloud Files. The two projects mentioned above led to a community of collaborating developers working on open projects and components.

There are plenty of vendors behind it and across the entire I.T. stack. For servers, we have Dell and H.P.; Storage consists of NetApp and SolidFire; Networking has Cisco and Software with VMware and IBM.

Initially, OpenStack foundations started with three primary services: NOVA computer service, SWIFT storage service, and GLANCE virtual disk image service. Soon after, many additional services, such as network connectivity, were added. The initial implementations were simple, providing only basic networking via Linux Layer 2 VLANs and IPtables.

Now, with the Neutron networks, you can achieve a variety of advanced topologies and rich network policies. Most networking is based on tunneling ( GRE or VXLAN ). Tunnels are used within the hypervisor, so it fits nicely with multi-tenancy. Tunnels are created between the host over the Layer 3 network within the hypervisor. As a result, tenancy V.M.s can spin up where they want and communicate over the tunnel.

What is an API?

The application programming interface ( API ) is the engine under the cloud hood. The messenger takes requests, tells the systems what you want to do, and then returns the response to you—ultimately creating connectivity.

Each core project (compute, network, etc.) will expose one or more HTTP/RESTful interfaces for public or managed access. This is known as a Northbound REST API. Northbound API faces some programming interfaces. It conceptualizes lower-level detail functions. Southbound faces the forwarding plane and allows components to communicate with a lower-level part.

For example, a southbound protocol could be OpenFlow or NETCONF. Northbound and southbound are software directions from the reference point of the network operating systems. We now have an East-West interface. At the time of writing, this protocol is not fully standardized, but eventually, it will be used to communicate between federations of controllers for state synchronization and high availability.

OpenStack Architecture: The Foundations

OpenStack Compute – Nova is comparable to AWS EC2. She is used to provisioning instances for applications.
OpenStack Storage – Swift is comparable to AWS S3. Provides object storage functions for application objects.
OpenStack Storage – Cinder is comparable to AWS Elastic Block Storage. Provides persistent block storage functions for stateless instances.
OpenStack Orchestration – Heat is comparable to AWS Cloud formation. Orchestrates deployment of cloud services
OpenStack Networking—Neutron Network is comparable to AWS VPC and ELB. It creates networks, topologies, ports, and routers.

There are others, such as Identity, Image Service, Trove, Ceilometer, and Sahara.

Each OpenStack foundation component has an API that can be called from either CURL, Python, or CLI. CURL is a command-line tool that lets you send HTTP requests and receive responses. Python is a widely used programming language within the OpenStack ecosystem. It automates scripts to create and manage resources in your OpenStack cloud. Finally, command-line interfaces (CLI) can access and send requests to APIs.

OpenStack Architecture & Deployment

OpenStack has a very modular design, and the diagram below displays key OpenStack components. Logically, it can be divided into three groups: a) Control, b) Network, and c) Compute. All of the features use a database or a message bus. The database can either be MySQL, MariaDB, or PostgreSQL. The message bus can be RabbitMQ, Qpid, and ActiveMQ.

The messaging and database could run on the same control node for small or DevOps deployments but could be separated for redundancy. The cloud controller on the left consists of numerous components, which are often disaggregated into separate nodes. It is the logical interface to the cloud and provides the API service.

The network controller includes the networking service Neutron. It offers an API for orchestrating network connectivity. Extension plugins provide additional network services such as VPNs, NAT, security firewalls, and load balancing. Generally, it is separate from the cloud controller, as traffic may flow through it. The compute nodes are the instances. This is where the application instances are deployed.

Leverage vagrant

Vagrant is a valuable tool for setting up Dev OpenStack environments to automate and build virtual machines ( with OpenStack ). It’s a wrapper around a virtualization platform, so you are not running the virtualization in Vagrant. The Vagrant V.M. gives you a pure environment to work with as it isolates dependencies from other V.M. applications. Nothing can interfere with the V.M., offering a full testing scope. An excellent place to start is Devstack. It’s the best tool for setting up small single-node non-production/testing installs.

Summary: OpenStack Architecture in Cloud Computing

In the fast-evolving world of cloud computing, OpenStack has emerged as a powerful open-source platform that enables efficient management and deployment of cloud infrastructure. Understanding the architecture of OpenStack is essential for developers, administrators, and cloud enthusiasts alike. This blog post delved into the various components and layers of OpenStack architecture, providing a comprehensive overview of its inner workings.

Section 1: OpenStack Components

OpenStack comprises several key components, each serving a specific purpose in the cloud infrastructure. These components include:

1. Nova (Compute Service): Nova is the heart of OpenStack, responsible for managing and provisioning virtual machines (VMs) and controlling compute resources.

2. Neutron (Networking Service): Neutron handles networking functionalities, providing virtual network services, routers, and load balancers.

3. Cinder (Block Storage Service): Cinder offers block storage capabilities, allowing users to attach and manage persistent storage volumes to their instances.

4. Swift (Object Storage Service): Swift provides scalable and durable object storage, ideal for storing large amounts of unstructured data.

Section 2: OpenStack Architecture Layers

The OpenStack architecture is structured into multiple layers, each playing a crucial role in the overall functioning of the platform. These layers include:

1. Infrastructure Layer: This layer comprises the physical hardware resources such as servers, storage devices, and switches that form the foundation of the cloud infrastructure.

2. Control Layer: The control layer comprises services that manage and orchestrate the infrastructure layer. It includes components like Nova, Neutron, and Cinder, which control and coordinate resource allocation and network connectivity.

3. Application Layer: At the topmost layer, the application layer consists of software applications and services that run on the OpenStack infrastructure. These can range from web applications to databases, all utilizing the underlying resources OpenStack provides.

Section 3: OpenStack Deployment Models

OpenStack offers various deployment models to cater to different needs and requirements. These models include:

1. Public Cloud: OpenStack is operated and managed by a third-party service provider in a public cloud deployment, offering cloud services to multiple organizations or individuals over the internet.

2. Private Cloud: A private cloud deployment involves setting up an OpenStack infrastructure exclusively for a single organization. It provides enhanced security and control over data and resources.

3. Hybrid Cloud: A hybrid cloud deployment combines both public and private clouds, allowing organizations to leverage the benefits of both models. This provides flexibility and scalability while ensuring data security and control.

Conclusion:

OpenStack architecture is a complex yet robust framework that powers cloud computing environments. Understanding its components, layers, and deployment models is crucial for effectively utilizing and managing OpenStack infrastructure. Whether you are a developer, administrator, or simply curious about cloud computing, exploring OpenStack architecture opens up a world of possibilities for building scalable and efficient cloud environments.

Network Configuration Automation

August 8, 2015

by Matt Conran Blog

Network Configuration Automation

In today's fast-paced digital landscape, efficient network configuration automation has become a cornerstone for organizations striving to enhance their operational productivity. Automating network configuration processes not only saves time and effort but also minimizes human error and ensures consistent network performance. In this blog post, we will explore the key benefits and considerations of network configuration automation, along with best practices to implement it effectively.

Network configuration automation refers to the practice of automating the deployment, management, and monitoring of network devices and related configurations. It streamlines the repetitive and time-consuming tasks involved in configuring network devices, such as routers, switches, and firewalls. By utilizing automation tools and frameworks, organizations can achieve greater agility, scalability, and accuracy in their network infrastructure.

Automating network configuration brings numerous advantages to organizations. Firstly, it significantly reduces the risk of human errors that can lead to network downtime or security vulnerabilities. Automation ensures consistency across network devices, eliminating configuration discrepancies.

Secondly, it enhances operational efficiency by reducing manual efforts and standardizing configuration processes, allowing IT teams to focus on more strategic initiatives. Lastly, network configuration automation facilitates faster troubleshooting and enables rapid changes to adapt to dynamic network requirements.

1. Comprehensive Network Inventory: Begin by creating a detailed inventory of network devices, including their models, firmware versions, and current configurations. This inventory will serve as a foundation for automation workflows.

2. Define Configuration Standards: Establish clear and standardized configuration templates that align with industry best practices. These templates should include essential parameters, such as IP addresses, routing protocols, and security policies.

3. Utilize Automation Tools: Choose a robust automation tool or framework that suits your organization's requirements. Evaluate features like device compatibility, scalability, and ease of integration with existing network management systems.

4. Test and Validate: Before deploying automated configurations in a production environment, thoroughly test and validate them in a controlled lab or staging environment. This step helps identify potential issues or conflicts.

While network configuration automation offers substantial benefits, it is essential to consider potential challenges. Organizations must ensure proper security measures are in place to protect automation tools and the integrity of network configurations. Additionally, regular monitoring and auditing of automated processes are crucial to detect any anomalies or unauthorized changes.

Conclusion: Network configuration automation serves as a catalyst for operational efficiency and reliability in modern network infrastructures. By embracing automation tools, defining robust processes, and adhering to best practices, organizations can streamline their network configuration workflows, reduce errors, and improve overall network performance. With the right approach, network configuration automation becomes a strategic enabler for organizations seeking to stay competitive in today's digital landscape.

Matt Conran

Highlights: Network Configuration Automation

Deterministic outcomes

An enterprise organization’s change review involves examining upcoming network changes, their impact on external systems, and their rollback plans. When humans use the CLI to make changes, typing the wrong command can have catastrophic results. Think about a team of three, four, five, or fifty engineers. Depending on the engineer, changes can be made in a variety of ways. In addition, even using a GUI or a CLI does not eliminate or reduce the chance of errors during change control.

The executive team has a better chance of achieving deterministic outcomes when they use proven and tested network automation to make changes. This increases their chances of achieving a successful project the first time around by achieving more predictable behavior than when making changes manually. This might happen when a new VLAN is added or a new customer is onboarded, requiring multiple network changes.

Furthermore, deterministic results result in lower operating expenses (OpEx), as network changes require less manual labor, resulting in a more efficient network operation (e.g., automating time-consuming tasks such as updating a network device’s operating system). Network engineers can focus on more strategic projects and improve processes with less operating time.

Device Provisioning

An easy and fast way to get started with network automation is to automate the creation and pushing of device configuration files.

Two steps are involved in this process: creating the configuration file and pushing it to the device.

To automate configuration files (or configuration data in general), the input parameters (configuration parameters) must first be decoupled from the vendor-proprietary syntax (CLI). Separate files will be created for configuration templates, VLANs, domains, interfaces, routing, etc.

Data Collection and Enrichment

Through SNMP, monitoring tools typically poll management information bases (MIBs) for data. Data may be returned in excess or insufficient to meet your needs. What should be done when polling interface statistics? What if you only need interface resets, not CRC errors, jumbo frames, or output errors? The command show interface may return every counter, but what if you only need interface resets? Moreover, what if you want to see interface resets correlated with Cisco Discovery Protocol (CDP) or LLDP neighbors now rather than in the future? In this context, what role does network automation play?

We focus on giving you more control so you can customize what you get when you get it, how it is formatted, and how it is used after it is collected. Automating the process can maximize your data.

Migrations

Migrating from one platform to another is never easy. There may be platforms from the same vendor or different vendors. In our example, you can create configuration templates for network devices and operating systems using various forms of automation. Vendors may provide a script or tool that helps with migrations. It would then be possible to generate a configuration file for every vendor using a defined and standard data set (common data model).

If you are using them, you must also consider vendor-proprietary extensions. It is fantastic that such a tool can be built independently rather than by a vendor. A vendor must account for all the device features, while an organization only needs a limited number. Vendors aren’t concerned about this; they are worried about their equipment not making it easier for you, the network operator, to manage multivendor environments.

Configuration Management

In this chapter, we won’t spend much time on configuration management since it is the most common type of automation. In configuration management, devices are deployed, pushed, and managed in terms of their configuration state. Everything from interface descriptions to configurations of ToR switches, firewalls, load balancers, and advanced security infrastructure is covered in order to deploy three-tier applications.

As you can see, with the read-only forms of automation, you don’t have to start by pushing configurations. This method may be worthwhile if you spend countless hours pushing the same change across many routers or switches.

Application Changes

Applications are deployed differently today than they were 10-15 years ago. So much has changed with the app. The problem we are seeing today is that the network is not tightly coupled with these other developments. Providing various network policies and corresponding configurations is not tightly associated with the application.

They are usually loosely coupled and reactive. For example, analyzing firewall rules and providing a network assessment is nearly impossible with old security devices, driving the need for network configuration automation and the ability to automate network configuration.

Before you proceed, you may find the following articles of interest:

Automate Network Configuration. Key Network Configuration Automation Discussion Points:	Introduction to Network Configuration Automation and what is involved. Highlighting the components of Automate Network Configuration. Critical points on the use of Ansible and Ansible variables. Technical details on how virtualization changes the manual approach. Technical details on SDN as a companion to automation.

Back to basics with the Network Automation.

One of the easiest and quickest ways to get started with network automation is to automate the creation of the device configuration files used for initial device provisioning and push them to network devices. You can also get a lot of information with automation. For example, network devices have enormous static and ephemeral data buried inside, and using open-source tools or building your own gets you access to this data.

Examples of this type of data include entries in the BGP table, OSPF adjacencies, active neighbors, interface statistics, specific counters and resets, and even counters from application-specific integrated circuits (ASICs) themselves on newer platforms.

Lab guide with Ansible Core

We have Ansible installed and a managed host already prepared in the following. The managed host needs to have SSH enabled and a user with admin privileges. Ansible finds managed hosts by looking at the inventory file. The inventory file is also a great place to pass variables that can be used to remove site-specific information; this is set under the host var section below.

Remember that Ansible requires Python, and below, we are running Python version 3.0.3 and Jinja version 3.0.3, which is used for templating. You can pass information to ansible managed hosts with playbooks and ad hoc commands. Below, I’m using an ad hoc command, calling the command module by default, and testing with a ping.

Ansible configuration — Diagram: Ansible Configuration

Benefits of Network Configuration Automation:

1. Time and Resource Efficiency: By automating repetitive and time-consuming network configuration tasks, organizations can free up their IT staff to focus on more strategic initiatives. This results in increased productivity and efficiency across the organization.

2. Enhanced Accuracy and Consistency: Manual configuration processes are prone to human error, leading to misconfigurations and network downtime. Network configuration automation eliminates these risks by ensuring consistency and accuracy in network configurations, reducing the chances of costly errors.

3. Rapid Network Deployment: With automation tools, network administrators can quickly deploy network configurations across multiple devices simultaneously. This accelerates network deployment and enables organizations to respond faster to changing business needs.

4. Improved Security and Compliance: Network configuration automation enhances security by enforcing standardized configurations and ensuring compliance with industry regulations. Automated security protocols can be applied consistently across the network, reducing vulnerabilities and enhancing overall network protection.

5. Simplified Network Management: Automation tools provide a centralized platform for managing network configurations, making it easier to monitor, troubleshoot, and maintain network devices. This simplifies network management and reduces the complexity associated with manual configuration processes.

Implementing Network Configuration Automation:

To implement network configuration automation, organizations need to consider the following steps:

1. Assess Network Requirements: Understand the specific network requirements, including device types, network protocols, and security policies.

2. Select an Automation Tool: Evaluate different automation tools available on the market and choose the one that best suits the organization’s needs and network infrastructure.

3. Create Configuration Templates: Develop standardized configuration templates that can be easily applied to network devices. These templates should include best practices, security policies, and network-specific configurations.

4. Test and Validate: Before deploying automated configurations, thoroughly test and validate them in a controlled environment to ensure their effectiveness and compatibility with the existing network infrastructure.

5. Monitor and Maintain: Regularly monitor and maintain the automated network configurations to identify and resolve any issues or security vulnerabilities that may arise.

The Need to Automate Network Configuration

There are always hundreds, if not thousands, of outdated rules even though the application service is not required. Another example is unused VLANs left configured on access ports, posing a security risk. The problem lies in the process: how we change and provision the network is not tied to the application. It is not automated. Inconsistent configurations tend to grow as human interaction is required to tidy things up. People move on and change roles.

You cannot guarantee the person creating a firewall rule will be the engineer deleting the rule once the corresponding applications are decommissioned or changed. And if you don’t have a rigorous change control process, deprecated configurations will be idle on active nodes.

A key point: The use of Ansible variables in an Ansible architecture.

For configuration management, you could opt for Red Hat Ansible. The Ansible architecture consists of modules with tasks on the target hosts listed in the inventory. Various plugins are available for additional context and Ansible variables for flexible playbook development. Ansible Core is the CLI-based version of automation, and Ansible Tower is the platform.

The recommended approach for enterprise-wide security would be a platform-based approach to the Ansible architecture. Using a platform approach using Ansible variables creates a very flexible automation journey where you can have one playbook with Ansible variables, removing any site-specific information running against several different inventories that could relate to your other functions, Dev, Staging, and Production.

The network is critical for business continuity, resulting in real uptime pressure. Operational uptime is directly tied to the success of the business. This results in a manual culture, which manifests as manual and slow. The actual bottleneck is our manual culture for network provision and operation.

Virtualization – Beginning the change

Virtualization vendors are changing the manual approach. For example, if we look at essential MAC address learning and its process with traditional switches. The source MAC address of an incoming Ethernet frame is examined, and if the source MAC address is known, it doesn’t need to do anything, but if it’s not known, it will add that MAC to its table and make a note of the port the frame entered. The switch has a port for MAC mapping. The table is continually maintained, and MAC addresses are added and removed via timers and flushing.

The virtual switch

The virtual switch operates differently. Whenever a VM spins up and a VNIC attaches to the virtual switch, the Hypervisor programs everything it needs to know to forward that traffic into its process on the virtual switch. There is no MAC learning. When you spin down the VM, the hypervisor does not need to wait for a timer.

It knows the source is no longer there; as a result, it no longer needs to have that state. Less state in a network is a good thing. The critical point is that the provision of the application/ virtual machine is tightly coupled with the provisioning of network resources. Tightly coupling applications to network resources/provisioning offers less “Garbage Collection.”

Box mentality

When the contents of HLD / LLD are completed and you are now moving to the configuration stage, the current implementation-specific details are done per box. The commands are defined on individual boxes and are vendor-specific. This works functionally, and it’s how the Internet was built, but it lacks agility and proper configuration management. Many repetitive tasks with a box mentality destroy your ability to scale.

Businesses are mainly concerned with agility and continuity, but you cannot have these two things with manual provisions. You must look at your network as a system, not individual boxes. When you look at applications and their scaling, the current network-style implementation method does not scale and keeps in line with the apps. A move to network configuration automation and automatic interaction is the solution.

Network Configuration Automation and Automate Network Configuration

We must move out of a manual approach and into an automated system. Focus initially on low-hanging fruit and easy wins. What takes engineers the longest to do? Do VLAN and Subnet allocation sheets ring a bell? We should size according to demand and not care about the type of VLAN or the Internal subnet allocation. Microsoft Azure cloud is a perfect example.

They do not care about the type of private address they assign to internal systems. They automate the IP allocation and gateway assignment so you can communicate locally. Designing optimum networks to last and scale is not good enough anymore. The network must evolve and be programmed to keep up with app placement. The configuration approach needs to change, and we should move to proper configuration management and automation.

Ansible is a widespread tool of choice. As previously mentioned, we have Ansible Tower as a platform, and for CLI-based devices, we have Ansible Core—both support variable substitution with Ansible variables.

SDN: A companion to network automation?

One benefit of Software-Defined Networking (SDN) is that it lets you view your network holistically, with a central viewpoint. Network configuration automation is not SDN, and SDN is not network automation. They work side by side and complement each other. SDN allows you to be abstract and prevents those who do not need to see the detail from not seeing it.

The application owners do not care about VLANs. Application designers should also not care about local IP allocations if they have designed the application correctly. Centralization is also a goal for SDN. Centralization with SDN is different from control-plane centralization. Central SDN controller devices should not fully control the control plane.

SDN companies have learned this and now allow network nodes to handle some or part control plane operations.

Programming network: Automate network configuration

You don’t need to be a programmer, but you should start thinking like one. Learning to program will make you better equipped to deal with things. Programming networks is a diagonal step from what you are doing now, offering an environment to run code and ways to test code before you run it out.

The current CLI is the most dangerous approach to device configuration; you can even lock yourself out of a device. Programming adds a safety net. It’s more of a mental shift. Stop jumping to the CLI and THINK FIRST. Break the task down and create workflows. Workloads are then mapped to an automation platform.

A key point: TCL and EXPECT

TCL ( Tool Command Language ) is a scripting language created in 1988 at UC Berkeley. It aims to connect Shell scripts and Unix commands. EXPECT is a TCL extension written by Don Libes. It automates Telnet, SSH, and Serial sessions to perform many repetitive tasks.

EXPECT’s main drawback is that it is not secure and is synchronous only. If you log onto a device, you display login credentials in the EXPECT scripts and cannot encrypt that data in the code. In addition, it operates sequentially, meaning you send a command and wait for the output; it does not send send send and wait to receive; it’s a send and waits, sends and wait for mythology.

A key point: SNMP has failed | NETCONF begins

SNMP is used for fault handling, monitoring equipment, and retrieving performance data, but very few use SNMP to set configurations. More often, there is no 1:1 translation between a CLI configuration operation and an SNMP “SET.” It’s hard to get this 1-2-1 correlation. As a result, not many people use SNMP for device configuration and management of structures.

CLI scripting was the primary approach to automating network configuration changes before NETCONF. Unfortunately, CLI scripting has several limitations, including a lack of transaction management, no structured error management, and the ever-changing structure and syntax of commands, making scripts fragile and costly to maintain. Even the use of autocorrelation scripts won’t be able to fix it.

People make mistakes, and ultimately, people are bad at stuff. It’s the nature of the beast. Human error plays a significant role in network outages, and if a person is not logging in doing CLI, they are less likely to make a costly mistake. Human interaction with the network is a major cause of network outages.

NETCONF & Tail-F

NETCONF ( network control protocol ) is an XML-based data encoding for configuration and protocol messages. It offers secure transport and is Asynchronous, so it’s not sequential like TCL and EXPECT. Asynchronous makes NETCONF more efficient. It allows the separation of the configuration from the non-configuration items.

SNMP makes backup and restore complex, as you have no idea what fields are used to restore. Also, because of SNMP’s binary nature, it isn’t easy to compare configurations from one device to another. NETCONF is much better at this.

A final note: Transaction-based approach

It offers a transaction-based approach. A transaction is a set of configuration changes, not a sequence. SNMP for configuration requires everything to be in the correct sequence/order. But with a transaction, you throw in everything, and the device figures out how to roll it out.

What matters is that operators can write service-level applications that activate service-level changes and don’t have to make the application aware of all the sequence of changes that must be completed before the network can serve application responses and requests. Check out an exciting company called Tail-F (now part of Cisco), which offers a family of NETCONF-enabled products.

Network configuration automation is revolutionizing how businesses manage their networks. It offers many benefits, including time and resource efficiency, enhanced accuracy, rapid network deployment, improved security, and simplified network management. By embracing this technology, organizations can streamline network operations, reduce human error, and stay ahead in the dynamic and ever-evolving digital landscape.

Summary: Network Configuration Automation

Network configuration is crucial in ensuring seamless connectivity and efficient data flow in today’s fast-paced technological landscape. However, the manual configuration of networks can be time-consuming, prone to errors, and hinder scalability. This is where network configuration automation comes into play, revolutionizing how networks are managed and optimized. In this blog post, we explored the benefits, implementation techniques, and best practices of network configuration automation.

Understanding Network Configuration Automation

Network configuration automation involves leveraging software and tools to automate configuring and managing network devices. Reducing human intervention eliminates manual errors, enhances agility, and enables effective network management at scale.

Benefits of Network Configuration Automation

Automating network configuration brings a plethora of advantages to organizations. Firstly, it significantly reduces human errors, ensuring accurate and consistent device configurations. Secondly, it enhances efficiency by saving time and effort spent on manual configurations. Additionally, automation allows for faster deployment of network changes, improving overall network agility and responsiveness.

Implementation Techniques for Network Configuration Automation

Implementing network configuration automation requires a structured approach. It involves:

1. Inventory and Device Discovery: Create an inventory of network devices and establish a comprehensive understanding of the existing network infrastructure.

2. Configuration Templates and Version Control: Develop standardized configuration templates that can be easily applied to multiple devices. Implement version control mechanisms to track and manage configuration changes effectively.

3. Orchestration and Automation Tools: Leverage network automation tools that provide scripting, scheduling, and deployment automation features. Tools like Ansible, Chef, and Puppet offer potent capabilities to streamline network configuration.

Best Practices for Network Configuration Automation

To ensure a successful implementation of network configuration automation, consider the following best practices:

1. Test and Verify: Before deployment, thoroughly test and verify automation scripts and templates to ensure they align with the desired network configuration and functionality.

2. Security and Compliance: Incorporate security measures and compliance standards into automation processes to protect network assets and ensure adherence to industry regulations.

3. Documentation and Change Management: Maintain detailed documentation of configurations and changes made through automation. Implement a change management process to track modifications and facilitate troubleshooting.

Conclusion:

Network configuration automation is a game-changer in network management. By embracing automation, organizations can reduce errors, enhance efficiency, and improve overall network performance. Whether deploying standardized configurations or orchestrating complex network changes, automation streamlines processes, allowing IT teams to focus on strategic initiatives and innovation.

Network Traffic Engineering

Highlights: Network Traffic Engineering

Back to Basics: Network traffic engineering

1st Lab Guide: MPLS Forwarding

Knowledge Check: IntServ and RSVP

Traffic Engineering: Inbound and Outbound

2nd Lab Guide: MPLS TE

Understanding MPLS and MPLS forwarding

3rd Lab Guide: DMVPN Phase 3

Network Traffic Engineering and MPLS

Holistic visibility – Controller-based networking

Summary: Network Traffic Engineering

OpenFlow and SDN Adoption

Highlights: OpenFlow and SDN Adoption

Back to basics with the SDN.

Starting Points for SDN Adoption

Summary: OpenFlow and SDN Adoption

OpenStack Architecture in Cloud Computing

Highlights: OpenStack Architecture in Cloud Computing

Back to Basics: Cloud Adoption.

The main components of OpenStack are:

Additional Details on OpenStack Components

Keystone

Swift

Cinder

Manila

Glance

OpenStack Features

OpenStack Architecture in Cloud Computing

What is an API?

OpenStack Architecture: The Foundations

OpenStack Architecture & Deployment

Leverage vagrant

Summary: OpenStack Architecture in Cloud Computing

Network Configuration Automation

Highlights: Network Configuration Automation

Back to basics with the Network Automation.

Lab guide with Ansible Core

The Need to Automate Network Configuration

Virtualization – Beginning the change

Network Configuration Automation and Automate Network Configuration

Summary: Network Configuration Automation

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