NashTech Insights

Integrating Jaeger for Microservices Monitoring

Rahul Miglani
Rahul Miglani
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In the fast-paced world of containerized microservices, monitoring and understanding application interactions become paramount. Enter Jaeger, the distributed tracing system that offers insights into the journeys of requests across services. When combined with the power of Kubernetes, the orchestration platform, you get a robust solution for monitoring microservices in a containerized environment. In this blog, we’ll walk you through the process of integrating Jaeger with Kubernetes-based applications, for Microservices Monitoring enabling you to gain invaluable insights into the interactions within your container ecosystem.

The Marriage of Jaeger and Kubernetes

Firstly, Jaeger and Kubernetes are a match made in microservices heaven. Kubernetes efficiently manages containerized applications, while Jaeger tracks their interactions. By integrating the two, you unlock the ability to visualize, analyze, and optimize your microservices architecture running on Kubernetes.

Step-by-Step Guide: Integrating Jaeger with Kubernetes

Step 1: Set Up Your Kubernetes Cluster

  1. Firstly, Install and configure a Kubernetes cluster using a tool like minikube, kops, or a managed Kubernetes service.

Step 2: Deploy Jaeger Components

  1. Secondly, Deploy the Jaeger components using Kubernetes manifests. These components include the collector, agent, query service, and UI.

Step 3: Configure Instrumentation

  1. Thirdly, Instrument your microservices code using Jaeger client libraries compatible with your programming language.
  2. Ensure trace context propagation across service boundaries.

Step 4: Configure Agent and Collector

  1. Configure the Jaeger agent to point to the collector service within your Kubernetes cluster.
  2. Ensure the agent is deployed as a sidecar container alongside your microservices.

Step 5: Access Jaeger UI

  1. Expose the Jaeger UI service to access the web interface. You can use kubectl port-forward or expose it through an Ingress or LoadBalancer.

Step 6: Visualize Traces

  1. Finally, Access the Jaeger UI through the exposed service URL. Use it to visualize traces, understand service interactions, and analyze performance.

Benefits of Jaeger-Kubernetes Integration

  • Granular Insights: Dive into traces to understand individual requests’ paths and interactions.
  • Dependency Mapping: Visualize service dependencies within the Kubernetes environment.
  • Performance Optimization: Identify latency issues, bottlenecks, and resource-heavy services.
  • Distributed Context: Lastly, Trace propagation maintains context even in the dynamic Kubernetes environment.

Best Practices for Integration

  • Automate Deployment: Use Kubernetes manifests or Helm charts for streamlined deployment.
  • Resource Planning: Allocate appropriate resources to Jaeger components to handle the tracing load.
  • Regular Maintenance: Keep both Jaeger and Kubernetes components updated for stability and security.
  • Sample Strategically: Lastly, Choose a sampling strategy that balances data accuracy with performance overhead.


Finally, The integration of Jaeger with Kubernetes elevates your microservices monitoring to a new level. As Kubernetes orchestrates your containerized applications, Jaeger brings their interactions to light.

Lastly, By following this guide, you seamlessly weave together Kubernetes and Jaeger, creating a dynamic ecosystem where you can explore the intricacies of your microservices architecture. Embrace this integration to optimize performance, troubleshoot issues, and enhance user experiences within the containerized world.

At-last, With Kubernetes and Jaeger as your allies, you’re equipped to navigate the complexities of microservices with precision and confidence.

Rahul Miglani

Rahul Miglani

Rahul Miglani is Vice President at NashTech and Heads the DevOps Competency and also Heads the Cloud Engineering Practice. He is a DevOps evangelist with a keen focus to build deep relationships with senior technical individuals as well as pre-sales from customers all over the globe to enable them to be DevOps and cloud advocates and help them achieve their automation journey. He also acts as a technical liaison between customers, service engineering teams, and the DevOps community as a whole. Rahul works with customers with the goal of making them solid references on the Cloud container services platforms and also participates as a thought leader in the docker, Kubernetes, container, cloud, and DevOps community. His proficiency includes rich experience in highly optimized, highly available architectural decision-making with an inclination towards logging, monitoring, security, governance, and visualization.

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