As organizations transform and modernize, they are adopting Kubernetes for better scalability and faster innovation. However, it can quickly turn complex based on the decoupled nature of microservices and containers. With distributed environments, observability is crucial to see how all the systems in your environment are dependent and communicate with one another.
Observability vital for Kubernetes
Observability provides context on how Kubernetes components influence the performance of Kubernetes applications, and correct problems before they become end-user problems. Because Kubernetes does not optimize performance on its own, engineers must identify the types of instances. Only observability provides engineers with a complete picture of all the necessary information for increasing performance and improving the stability and resiliency of applications, the Kubernetes components, and the underlying infrastructure.
A core function of Kubernetes is to automate deploying and running workloads. Workloads are a collection of IT assets and application workloads are the footprint of an application as it consumes computing resources in terms of CPU, memory, I/O, and network. Observability into workloads is a key function as it details performance, providing insight, troubleshooting, which allows for faster time to market.
Cloud native environments, like Kubernetes, are dynamic, and Operators play a powerful role in simplifying software. An Operator is a piece of software that understands how to run and facilitate operating another piece of software. In the context of this blog, we will explore the Kubernetes Operator, which is a software extension to Kubernetes, to manage applications and their components.
Why Operators are important in Kubernetes environments?
Kubernetes Operators enable complex clusters and systems to operate automatically. They eliminate the need for manual tasks and reduce errors by making application performance part of the platform, making processes consistent, repeatable, and scalable. Some key benefits of a Kubernetes Operator are:
- Application Management: Manage the update of an application with all its dependencies, including new configuration settings.
- Centralized Configuration: The custom resource yaml file encloses all the needed configurations to manage your metrics, logging, and tracing settings. The operator will ensure the needed underlying components are updated to reflect the desired configuration.
- Status Reporting: “Monitoring the monitoring system” is simpler with an operator. The operator will run health checks on the managed components, and present them to the user, along with any relevant status messages.
- Configuration Validation: YAML config changes are automatically verified, and any misconfigurations are reported back to the user in order to simplify configuration of the operator.
VMware Kubernetes Observability Operator
VMware released an updated Kubernetes Observability Operator to accelerate configuration management and reduce onboarding time. Enhanced configuration validation will surface what needs to be corrected to deploy successfully and enhanced status reporting of Aria Operations for Applications integration ensures clusters and Kubernetes resources are reporting data.
VMware Aria Operations for Applications delivers full-stack observability for Kubernetes with advanced analytics on metrics, traces, events, and logs that come from the applications themselves, from application services, container services, and multi-cloud environments. VMware Aria Operations for Applications supports metric-intensive workloads and millions of data points per second and can scale across multi-cloud environments. With enterprise-grade observability for Kubernetes, developers, site reliability engineers (SREs), and Kubernetes platform operators get accelerated time to value with automated and unified comprehensive insights into the health, state and performance of their application, Kubernetes, and multi-cloud environments. Engineers use VMware Aria Operations for Applications to proactively alert on problems so they can troubleshoot and optimize the performance of their modern applications rapidly.
By ingesting the data from Aria Operations for Applications into Kubernetes through the Kubernetes Observability Operator, developers, and Kubernetes operators to get automated observability across the Kubernetes environment, including containerized applications, Kubernetes, and underlying infrastructure by creating dashboards with context to help with monitoring and troubleshooting.
As users scale Kubernetes, it can be challenging and time consuming for Kubernetes administrators to keep track of the many clusters that are being spun up and make sure they are being monitored. The Kubernetes Observability Operator removes this issue by automatically discovering all Kubernetes clusters, including those in AWS EKS clusters and Azure AKS clusters.
Conclusion
VMware’s Kubernetes Observability Operator makes observability part of your platform, simplifying Kubernetes monitoring and leveraging automation to eliminate manual tasks. This is currently available to all Aria Operations for Applications customers who manage Kubernetes. For more information on how to get started, visit our github page.
