A properly managed and implemented observability system provides DevOps with granular insights that can be used to debug and heal complex systems. Observability combines monitoring, alerting, and logging with metrics visualization and its analysis. It allows development teams to get detailed insights into the real-time performance of Kubernetes clusters and applications so that they can make timely and informed actions. Here, in this blog, we’ve discussed three important tools to implement Kubernetes Observability. Let’s take a look! Kubernetes at its Boom Today, containers and microservices are emerging as the cornerstone of a flexible hybrid cloud strategy. Kubernetes have completely revolutionized the deployment and lifecycle management of containers across public clouds and private data centers. So profound was its effect that initially Kubernetes was considered a “be-all and end-all” for software lifecycle management. However, things have changed. Now that the initial “hype” around Kubernetes in the industry has somewhat settled, it is clear that Kubernetes adoption can be a tough row to hoe. Considering microservices and containers is one critical piece of the cloud-native puzzle. The other part is also a must to crack for leveraging all its benefits. Organizations must understand how these systems work in their totality before embarking on a cloud-native journey. The Dynamic Nature of Kubernetes Kubernetes, due to its dynamic nature, is unpredictable. Despite the best efforts, failures and performance bottlenecks in such systems are inevitable ​and can be difficult to separate. In such a complex environment, getting deep visibility into the behavior of enterprise applications becomes critical to solve bugs & issues instantly for seamless and rapid app delivery. But, a bigger challenge is how to monitor a Kubernetes cluster and its components. Importance of Observability- The 3 main Pillars IT decision-makers and tech strategists consider that observability plays an important role in the planning and operating phases of the software development life cycle. The three pillars of observability—metrics, logging, and tracing not only help teams to gain observability into the Kubernetes environment, but also provides them with deep insights into the underlying infrastructure, regardless of the technology stack being used. As per New Relic’s 2021 Observability Forecast report on the adoption of observability and the expected trends, 83% of the enterprises agree that the best Kubernetes observability strategy pivots on deploying a solution that can automatically collect and associate observability data from all available sources . This outlines enterprises’ need for a non-intrusive, friction-less approach to track observability for managing the cloud-native stack. Here are three important Kubernetes observability tools that have become the de-facto industry standards for enterprises within the cloud-native community. The implementation of these Kubernetes monitoring tools will give DevOps & SRE teams the complete visibility of the cluster components required to maintain the Kubernetes environment. is an open-source monitoring and alerting tool that provides in-depth insights into the system's performance. It is a cloud-native time-series data store- with a built-in query language for metrics. The tool has in-built support for Kubernetes and containers. It can easily be run in Kubernetes using a or in a stand-alone mode. Prometheus- Automating Collection and Storage of Observability Data Prometheus Kubernetes Operator Prometheus uses exporters to bring third-party data into its data store. There are a number of ready-to-use exporters maintained as part of Prometheus. These include, - Elasticsearch stats exporter for Prometheus, -the Exporter for MySQL server metrics, -and the Kafka exporter for Prometheus. Prometheus scrapes metrics from Kubernetes nodes, containers, pods, services and user applications running in Kubernetes. To allow Prometheus to scrape metrics from applications, developers need to expose metrics via HTTP at the metrics endpoint. Prometheus uses a highly efficient PromQL query language and integrations with major databases and metrics collector agents such as Elasticsearch and Metricbeat. In some cases, teams need to monitor components that cannot be scraped. Using the Prometheus Pushgateway which is a component of Prometheus, teams can collect metrics for extremely brief jobs and push time series directly into a Prometheus data store. The Prometheus comprises interlocking components that include, Prometheus Server: It acts as the system’s “brain” by collecting various metrics and storing them in a time-series database. Prometheus Client libraries: These help users integrate their built services by sending metrics and data in a format that Prometheus can understand. Prometheus Alertmanager: This Prometheus component sends alerts and notifications to designated users when the tool detects anomalies and performance issues. Collecting data with Prometheus helps DevOps teams capture granular insights of the complete infrastructure and the containers running within the Kubernetes cluster. To ensure efficient performance of Kubernetes clusters in production, product teams must have a real-time understanding of diverse metrics that tell about various issues such as memory or storage shortage, node, network health, application errors, etc. By providing in-depth visibility of the application's components usage, this K8s monitoring tool helps in keeping a track of the performance of an application for identifying bottlenecks and ways to get rid of them. Prometheus Visualization Tools: These help in displaying metrics and data in a human-readable format. Users can also integrate Prometheus with Grafana, an open-source web application for analytics and data visualization. Source: Prometheus.io At times, raw metrics ( data that has not been processed) do not serve the best for the visualization of observability data. The reason is that they often consist of time series and text-based data with thousands of events, which cannot be untangled by human beings. , an observability platform which can be easily deployed in Kubernetes, helps conquer the problem by processing raw metrics. Grafana—Visualizing Observability Data Grafana Grafana manages and executes all of this through its official and community-built dashboards. These dashboards can be downloaded and imported into the Grafana instance. According to Grafana documentation , this tool “allows teams to query, visualize, alert on, and understand metrics no matter where they are stored.” Grafana is a powerful data visualization and analytics tool that supports alerting and notifications. The tool has integrations with major time-series databases (Prometheus, InfluxDB), Elasticsearch, SQL databases, cloud monitoring services, and many more. It operates via metrics aggregations and powerful dashboards making Kubernetes observability a plain-sailing task. You read more about Grafana, its components and how to monitor a Kubernetes cluster here ! Kubernetes Dashboard for Cluster Monitoring (Source: Grafana) BuildPiper- Getting a comprehensive view of the Kubernetes Cluster BuildPiper is a Kubernetes & Microservices Application Delivery platform that offers a 360-degree view of the Kubernetes cluster. With BuildPiper, visibility and anomaly detection across the Kubernetes clusters is reimagined to give teams an in-depth analysis in a few simple clicks. This Kubernetes monitoring tool has a Service Overview Dashboard that enables DevOps teams to view and observe the build and deploy details and a Service Kubernetes Dashboard, that provides in-depth cluster observability capabilities to monitor the performance, health status, CPU &  memory allocation, node availability, logs, and other important metrics. The 360-degree view offered gives a clear picture of the performance, health status, availability, and functionality of the cluster components. It offers complete node visibility to enable viewing of the health status of the nodes. The pod health feature displays the real-time health status of the containers highlighting the environment variables and volume mounts for the pods present in the K8s cluster.  Moreover, teams can keep a track of the real-time status of NameSpaces, Ingress, and other K8s assets of the Kubernetes cluster with the help of this monitoring tool. Source: BuildPiper Kubernetes is powerful, only if Managed and Monitored well Due to the ephemeral and constantly-changing nature of Kubernetes, a Kubernetes monitoring system demands the ability to recognize changes automatically and continually monitor events, logs, pod health status, and much more without any interruption. Exploring solutions for how to monitor a Kubernetes cluster and knowing metrics on finding faults, scanning cluster health status, and figuring out ways to solve these issues are some of the common problems that enterprises often face. So, while choosing a Kubernetes deployment platform or a Kubernetes monitoring tool, it’s important that the solution you opt for has the ability to keep a track of these metrics and give a clear picture of what is exactly happening inside the cluster to enable a hassle-free Kubernetes deployment. The article has also been published Here !

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