In DevOps, Observability is the software tools and methodology that enable Dev and Ops teams to log, collect, compare, and analyze large volumes of performance data from distributed applications and gain real-time insights that enable teams to track, update, and improve the application to provide a better customer experience.?
Implementing DevOps observability involves creating a set of practices and tools that enable you to gain insights into your systems, applications, and infrastructure. This helps you understand the performance, health, and behavior of your systems, facilitating faster detection and resolution of issues. Here's a general guide on implementing DevOps observability:?
- Your Observability platform must be future ready: The DevOps landscape is constantly changing. An observability platform designed to meet your current business requirements and infrastructure likely won’t keep up with your future needs. So, you’ll need to consider your future business requirements and trends and choose the observability platform best suited to your long-term vision. Whether it’s open-source or commercial, you must consider your future infrastructure needs and choose a platform that meets your future needs without impacting your bottom line.?
- Your Observability platform must collect and automate data: You want your observability platform to be able to collect and store data from all systems and components in a central location. This makes information easier to access, easier to understand, and gives you a holistic view of the health of your system. The collected telemetry data (metrics, logs, traces, etc.) should be as fluid as your application environment. If you run your applications on virtual machines (VMs), make sure your observability platform can include and track any automatically spinning VMs. If you run in containers, configure the monitoring to include any automatically spinning containers. The platform should provide the insights you need to identify whether the issues are programmatic, or environmental.??
- Your Observability platform must collect and analyze the telemetry data for actionable insights: Logs, metrics and traces are all distinct from one another. Your observability solution must analyze 100% of telemetry data and deliver actionable insights. Your data should be easy to visualize and navigate, so you can easily interact with your data. It should also allow you to filter and define the logs for a particular application at a particular time. In short, you need to be able to quickly create custom metric aggregations so you can quickly research and solve a performance issue. The last objective is to achieve complete visibility across your application environments with all your telemetry information. The solution should provide visibility across infrastructure metrics, across the application stack, and across the end user experience. In addition, the solution should analyze and match telemetry data with your specific requirements at any given time. A strong observability platform allows you to track daily application performance, resolve known problems, and detect unknown problems.?
- Your Observability platform must work in near real time: To help DevOps teams respond quickly and effectively to performance issues, you need to have an observability platform that is as close as possible to being in real-time. With the amount of data, you’re dealing with, an observability platform needs to be able to run at an intelligent speed without becoming a bottleneck. Developing insights and alerts into telemetry at the right time can save your business from thousands of dollars in missed service level obligations (SLOs) and lost customer relationships.?
- Simple to Integrate: The tools you select for observability must be easy to integrate. Complex integration can slow down your project execution. For observability to be effective, you need to leverage existing tools. The tools should support environments with different languages, frameworks, and environments. The tools should integrate easily with service mesh, container platform, and integrate with Slack and pagerduty or your preferred systems.?
- Easy to use: If observability tools are hard to learn and implement, it can be difficult to integrate them with your existing processes and workflow. DevOps teams may feel uncomfortable using observability tools during critical events, resulting in incremental improvements to the system’s health and reliability.?
- Scalable: The correct observability tools are extremely scalable. They can ingest, process and analyze telemetry data without latency in a cost-efficient way. In the end, observability tools need to improve customer experience, increase developer speed and provide a more robust, resilient and stable system on a large scale.?
In conclusion, DevOps observability is a crucial component of a successful and efficient development and operations process. It requires a combination of cultural, organizational, and technical considerations to implement effective practices that contribute to the overall success of a DevOps approach.?
