{"id":2613,"date":"2018-07-16T07:00:52","date_gmt":"2018-07-16T01:30:52","guid":{"rendered":"http:\/\/www.upnxtblog.com\/?p=2613"},"modified":"2021-05-27T16:02:09","modified_gmt":"2021-05-27T10:32:09","slug":"kubernetes-tutorial-distributed-tracing-with-jaeger","status":"publish","type":"post","link":"https:\/\/www.upnxtblog.com\/index.php\/2018\/07\/16\/kubernetes-tutorial-distributed-tracing-with-jaeger\/","title":{"rendered":"Kubernetes Tutorial : Distributed tracing with Jaeger"},"content":{"rendered":"
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Jaeger<\/strong><\/a> is an open-source distributed tracing system by Uber Technologies<\/a>. Like Dapper<\/a> or Zipkin<\/a>, it is used for monitoring and troubleshooting microservices-based distributed systems. In this post, we are going to look at how to deploy Jaeger to the Kubernetes cluster.<\/p>\n

This quickstart assumes a basic understanding of Kubernetes concepts<\/a>, please refer to earlier posts for understanding on Kubernetes & how to create, deploy & rollout updates<\/a> to the cluster.<\/p>\n

\"Jaeger
Image – Jaeger Distributed Tracing<\/figcaption><\/figure>\n\n

#1.Why Distributed Tracing?<\/h2>\n

In the Microservices architecture, the application is usually structured as a set of loosely coupled, collaborating services. Each service implements a set of related functions. For example, an application might consist of services such as the order management service, the customer management service, etc. Services communicate using either synchronous protocols such as HTTP\/REST or asynchronous protocols such as AMQP. Services can be developed and deployed independently of one another. Each service has its own database in order to be decoupled from other services. For more intro on Microservice architecture, check out here<\/a>.<\/p>\n

Service requests often span multiple services. Each service handles a request by performing one or more operations, e.g. database queries, publishes messages, etc. To understand the behavior of an application and troubleshoot problems there is a need to monitor each service but if you use any of the external monitoring tools, it only tells you the overall response time and number of invocations but there would be no insight into the individual operations. To understand how each service is performing we would need to instrument services with code that will do the following<\/p>\n

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  1. Assign each external request a unique external request id<\/em><\/li>\n
  2. Pass the external request id<\/em> to all services that are involved in handling the request<\/li>\n
  3. Include the external request id<\/em> in all log messages<\/li>\n
  4. Record information (e.g. start time, end time)<\/em> about the requests and operations performed when handling an external request in a centralized service<\/li>\n<\/ol>\n

    So this where Jaeger can help us, it supports the OpenTracing initiative and can be used for monitoring microservices-based distributed systems:<\/p>\n