NashTech Insights

Unraveling Application Insights: An Introduction to Distributed Tracing with Jaeger

Rahul Miglani
Rahul Miglani
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As modern application insights embrace microservices architecture, the complexity of tracking requests across multiple services becomes a challenge. This is where distributed tracing steps in, offering a clear view of the journey a request takes through various components. Among the array of distributed tracing tools, Jaeger stands out as a powerful and versatile option. In this blog, we’ll embark on a journey to understand the essence of distributed tracing, explore the benefits of using Jaeger, and delve into its seamless integration with various frameworks.

Demystifying Distributed Tracing

Distributed tracing is a technique that involves instrumenting your application to capture timing data for requests as they traverse through different services. It creates a detailed map of the journey, allowing you to identify bottlenecks, performance issues, and dependencies in your microservices architecture.

Benefits of Distributed Tracing:

  • Performance Optimization: Pinpoint slow components and latency issues affecting user experience.
  • Issue Resolution: Quickly identify and troubleshoot errors or failures within the application.
  • Dependency Mapping: Understand dependencies between services and visualize how they interact.
  • Capacity Planning: Gain insights into resource utilization and plan for scaling efficiently.
  • User Experience Enhancement: Improve overall application responsiveness and user satisfaction.

Introducing Jaeger: A Versatile Distributed Tracing Solution

Jaeger is an open-source, end-to-end distributed tracing tool that was originally developed by Uber Technologies. It’s designed to offer comprehensive insights into application performance and streamline troubleshooting efforts.

Key Features of Jaeger:

  • Trace Visualization: Visualize the journey of requests as they move across services.
  • Dependency Mapping: Discover service dependencies and understand communication patterns.
  • Performance Metrics: Gain insights into latency, response times, and bottlenecks.
  • Error Tracking: Identify errors and exceptions in your application’s execution flow.
  • Root Cause Analysis: Drill down into traces to identify the source of performance issues.

Seamless Integration with Various Frameworks

Jaeger’s flexibility shines through its ability to integrate with a wide range of frameworks and platforms:

  • Microservices Architectures: Integrate Jaeger into microservices built using languages like Java, Python, Go, and more.
  • Kubernetes and Containers: Deploy Jaeger alongside your containerized applications to gain insights in dynamic environments.
  • Serverless Architectures: Instrument serverless functions to capture traces even in event-driven architectures.
  • Cloud-Native Applications: Utilize Jaeger’s cloud-native integrations for seamless trace collection in platforms like Kubernetes.


In the realm of distributed systems, understanding how your application insights behave is no longer a luxury – it’s a necessity. Distributed tracing with Jaeger equips you with a map to navigate the complex landscape of microservices interactions. By gaining insights into performance bottlenecks, dependencies, and errors, you’re empowered to deliver exceptional user experiences and maintain the health of your applications. As you embark on your journey of embracing distributed tracing, consider Jaeger as your guiding light, illuminating the path to a more resilient and efficient microservices architecture.

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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