Monitor Kubernetes with dashboards for proactive decision-making and growth
Strategically monitor K8s clusters and accelerate decisions with prebuilt Kubernetes dashboards
April 21, 2021 | By: Vaividh Yasa and Shivadhar Pingili
Kubernetes (K8s) is an increasingly popular cloud computing container orchestration system that automates the management, scaling and deployment of microservice applications. In fact, Gartner predicts that by 2022, more than 75% of global organizations will be running containerized applications in production, up from less than 30% today.
For organizations today, not only does deploying and managing applications on Kubernetes play a key role in their digital transformation initiatives, but it’s important to monitor Kubernetes environments to ensure systems are operating correctly and get alerted when they aren’t. Kubernetes can simplify the management of your containerized applications but can also add layers of complexity—meaning, more services and components that need to be monitored. Traditional performance monitoring techniques were not designed to support the volume, granularity and dynamic nature of today’s cloud microservices architectures. The combination of cloud microservices and containers results in many moving parts across many networking layers, and massive amounts of telemetry data flows from hardware all the way to business performance metrics.
Historically, it takes years of experience in handling a wide variety of Kubernetes issues—from simple to complex—to deeply understand and get to the right metrics needed to efficiently monitor a Kubernetes cluster. For example, if an application goes down or is not running well, it’s essential to quickly get to the heart of the issue. Each Kubernetes pod may have one or more containers to support that application. You need to discover exactly what is happening with the resources allocated to those pods and their containers. The application could be:
- Running out of CPU
- Suffering from memory issues
- Experiencing network issues
- Having underlying infrastructure issues
Without effective K8s monitoring, it’s difficult to know what to investigate first. Newer Kubernetes monitoring tools like Prometheus and Grafana are fairly easy to use but can be challenging to deploy in the most efficient way.
Harness performance monitoring metrics in Kubernetes dashboards to power decisions, reveal insights and act
As Kubernetes has matured, so have the metrics associated with performance monitoring. For any distributed, user-facing system, Google’s Site Reliability Engineering (SRE) teams recommend focusing on the four “golden” signals of monitoring: latency, traffic, errors and saturation. “Red” metrics are a subset of the original golden signals, and they capture overall network-level metrics. Finally, “use” metrics capture infrastructure-related metrics inside of clusters.
Not surprisingly, it can be challenging to understand and process the relative importance and intersection of these metrics, much less generate meaningful insights and trending information from the data. Any cluster has underlying infrastructure, pods and containers, and every cluster uses memory, CPU and network resources. Ultimately, a lot of data and metric logs are produced. Organizations need to be empowered to use performance monitoring metrics to make decisions about critical issues, like hardening security or application failure post-mortems. Given the sheer volume of metrics log data, it’s critical to integrate the information into an easily understood and visual dashboard that helps you make sense of those metrics and reveals insights. However, building your own dashboard is complex and requires expertise in Prometheus and Grafana querying languages like PromQL. Leveraging an experienced IT services partner with experience in custom dashboarding can help you shine a light on your data and enable proactive decision-making—without the stress.
A custom Kubernetes cluster monitoring dashboard accelerator can help you make strategic decisions
Smart data can put your organization in the fast lane to high-powered decisions and digital transformation. But first, you need to analyze and interpret the data in digestible formats and dashboards. TEKsystems has created a customizable Kubernetes container monitoring solution that helps tame complexity with prebuilt and pretested dashboards that visualize metrics, as well as an automated library. A proprietary Helm chart—based on approved Prometheus and Grafana chart templates—deploys Prometheus and Grafana together with well-organized and prebuilt dashboards that show the most essential metrics. An automated CI/CD pipeline library deploys the Helm chart into any Kubernetes cluster with ease.
Our Kubernetes dashboard system helps you make decisions by looking for patterns in data as it is collected, identifying patterns and critical event thresholds and creating alerts. These alerts can be communicated through the channel of your choice and help you manage your system and make important planning decisions, such as:
- When CPU utilization exceeds 70% and a pod is added
- When a Java-based application runs out of memory and pods stop responding
- When utilization of any critical metric exceeds a threshold
Pretested and built according to industry best practices, our solution can monitor performance regardless of where a Kubernetes cluster resides—whether it is on-premises or on any public cloud platform such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure. Plus, the cluster can be custom built or part of a managed Kubernetes service.
Manage Kubernetes with TEKsystems’ Kubernetes monitoring tool
Whether you need a custom dashboard that helps you see the light, or a master strategy to cultivate exponential business value in the digital age, we can help—and our thought leadership, proprietary tools and accelerators will help you find your focus, faster.
Vaividh Yasa is a practice architect with TEKsystems Global Services. Over the last seven years, he has worked in number of technical and leadership roles in the cloud and DevOps field. He has expertise in cloud architecture, DevOps, infrastructure as code (IaC), CI/CD, containerized environments, monitoring and automation.
Shivadhar Pingili is a senior DevOps engineer at TEKsystems Global Services. Over the past five years, he has worked in a number of technical roles in the cloud and DevOps field. He has expertise in multiple cloud platforms, DevOps, IaC, CI/CD,Kubernetes, Docker, automation and monitoring.