What are the best network performance analysis and optimization practices for DevOps?

Metrics should also account for real world traffic patterns using applications that commonly trigger bottlenecks. Does Jira always load slowly? What applications are sending traffic during peak usage times? These will give greater insight than raw throughput metrics alone.

Network performance metrics from a DevOps standpoint refer to the indicators used to measure the effectiveness and efficiency of a network infrastructure. Metrics include: 1) Throughput - amount of data that can be transmitted over the network in a given amount of time 2) Latency - the time it takes for a packet of data to travel from one point in the network to another 3) Packet Loss - missing data 4) Availability - the amount of time that the network is available for use 5) Bandwith Utilization - the percentage of the available bandwidth that is being used. 6) Throughput - data transfer rate etc.

Your prometheus exporters should include networking metrics. But for the actual network NetFlow is very good with tooling around that with or without sampling. Nagios, Zabbix ando ther Nagios derivates is the old world, and should not be used anymore.

Start by identifying your monitoring objectives and defining the metrics that matter. Best practices include regularly monitoring performance across key points, setting up alert thresholds, and conducting trend analysis. Some of the top tools used by companies across the industry for network monitoring are 1) Prometheus 2) Zabbix 3) DataDog 4) Grafana 5) Dynatrace Although, one should play around with these individually to identify which tool would best suit their needs.

Some of the good ones are listed below: Apache JMeter: A widely-used open-source tool for load testing and performance measurement. Gatling: An open-source, high-performance load testing tool that emphasizes scalability and performance. Locust: An open-source distributed load testing tool written in Python. It uses an event-driven, asynchronous architecture and allows for scripting realistic test scenarios. LoadRunner: A comprehensive performance testing solution from Micro Focus. It supports wide range of protocols and provides features like load balancing and performance monitoring. Neoload: A commercial load testing tool known for its simplicity and flexibility. It offers an intuitive interface and advanced scripting capabilities.

A thing to remember when working with networking performance is that bandwidth will not tell the full story, you have to look att pps (Packet Per Second) because the packets is what cost interrupts in the end systems handling the Layer 4-7.

When you work with performance, and autoscaling you will have to rememeber the TCP stack (usually) and source ports. Because that is a hard limit of 65535 per ip:port-pair. And this is an issue systems run into when they use proxies, loadbalancers - often.

Some additional pointers to consider (that I always practice) 1) Network segmentation: Analyze your network architecture and segment it logically to isolate critical components and services. 2) Quality of Service (QoS): Prioritize network traffic by implementing QoS policies based on different application requirements. 3) Security monitoring: Integrate security monitoring tools and practices into your network performance monitoring architecture to identify potential threats, vulnerabilities, and attack patterns. (Important) 4) Continuous improvement: Regularly review and assess your network performance monitoring architecture. (important)