Four key metrics you need to know when monitoring microservices applications running on Kubernetes

Understanding how microservices applications work in Kubernetes is important for software development. In this article, we explain why it is important to observe microservice applications in Kubernetes and some of the metrics you should focus on as part of your observability strategy.

Why should I observe the health of microservices running on Kubernetes and what Kubernetes metrics should I monitor?

Consider a large-scale e-commerce platform that leverages a microservices architecture deployed on a Kubernetes cluster. Each microservice, responsible for a specific function, such as inventory management, order processing, payment processing, etc., operates independently and communicates with other services through APIs, which are critical to business/service growth.

In these complex environments, ensuring smooth operation and proactively detecting problems can be essential and difficult.

The observability of this scenario can help provide real-time insights into the performance, availability, and interdependencies of these microservices and Kubernetes applications.

Observability is essential for several reasons:

• Early detection of problems: Microservices are distributed and interconnected, making it difficult to identify problems when they arise. Observing conditions can help you detect problems early, minimizing downtime and potential service interruptions. Instana allows for one-second granularity, helping you detect issues faster than other solutions.
• Trustworthy: Monitoring the health of your microservices maintains the stability of your application. Tracking metrics like response time, error rate, and resource utilization allows you to proactively address performance issues before they impact your users.
• Scale efficiently: Kubernetes can dynamically scale microservices based on demand. Observing health helps you make informed decisions about when and how to scale your services to ensure optimal performance and resource utilization.
• Meet SLAs: Many organizations have service level agreements (SLAs) that define expected service availability and performance levels. Observing the health of your microservices helps you meet these SLAs by ensuring that your services are running smoothly and meeting performance goals.

By monitoring Kubernetes health, organizations can proactively identify and resolve issues, optimize resource usage, and maintain optimal cluster performance.

Key metrics you can measure include:

Cluster availability:

Monitoring Kubernetes cluster availability metrics helps you ensure that your cluster is running and healthy. Metrics such as cluster uptime and pod health provide insight into the overall health of your cluster. This is at the highest and most important layer and can provide complete visibility into what is happening in the environment.

Pod metrics:

Monitoring pod health metrics such as pod restarts, pod readiness, and pod removals can help you identify issues with individual pods and ensure that your applications are running smoothly. Monitoring pod health allows organizations to quickly detect and resolve issues, minimizing downtime and ensuring high availability.

Service availability:

Monitoring service availability metrics such as service uptime, service response time, and service error rate helps ensure that Kubernetes services are available and responsive to users. By monitoring service availability, organizations can detect service failures or performance degradation and take proactive steps to restore service availability and minimize the impact to users.

Node status:

This is a metric that shows node health in the context of Kubernetes cluster metrics. Other important indicators include:

• kube_node_status_capacity: This metric indicates the available capacity for various resources on a node, helping you identify how much resource is available.
• kubelet_running_container_count: This tells you how many containers are currently running on the node.
• kubelet_runtime_actions_latency_microseconds: This metric measures the time each operation takes to complete, broken down by type, in microseconds.

Observability in numbers

IBM Instana can monitor microservice applications running on Kubernetes.

IBM Instana is a fully automated, real-time observation platform that contextualizes performance data. This allows you to detect issues or transactions in your microservices applications in fractions of a second. Plus, if you run into any issues running your microservices on Kubernetes, you get 100% traceability so you can easily troubleshoot them.

Resources to get started observing Kubernetes

To gain full visibility and more proactive problem resolution, consider Instana’s new Self-Hosted Standard Edition, a comprehensive solution designed for all levels of Kubernetes usage. Whether you are a beginner or an advanced Kubernetes user, Instana Standard Edition monitoring is supported. You can sign up for a free account and start monitoring your Kubernetes cluster today, or view the step-by-step guide below.

Check out our step-by-step guide now