The open source Jaeger distributed tracing platform has officially graduated into the top tier of projects being stewarded by the Cloud Native Computing Foundation (CNCF).
Designed to be employed within any DevOps environment, Jaeger is a tool for monitoring transactions across complex distributed computing environments. It consists of a backend for trace collection and analysis and multiple client libraries implementing the OpenTracing application programming interface (API) in various languages.
Developed by Uber, Jaeger now integrates with tools such as OpenTracing, OpenTelemetry, Envoy and Prometheus to make it easier to discover the root cause of issues impacting transactions in complex IT environments. For example, DevOps teams can apply data mining techniques and machine learning algorithms to analyze data from a specific cluster.
Organizations that are already using Jaeger in production environments include GrafanaLabs, Northwestern Mutual, SeatGeek, Symantec, Ticketmaster, Uber, Weaveworks and Zenly.
Jaeger is also starting to be bundled with other platforms, such as the Red Hat OpenShift Service Mesh. As that trend continues, more organizations are likely to become exposed to Jaeger as a tool for debugging a wide variety of issues.
Although originally developed to address the inherent complexity associated with microservices, Jaeger also can be applied to monolithic applications, Shkuro said. While many of those monolithic applications eventually are likely to be deconstructed into a set of microservices, many of those applications are not going away anytime soon, he noted.
Jaeger now has 15 active maintainers from four companies, with more than 1,200 contributors and 375 authors of commits and pull requests. It also has more than 9,000 GitHub stars and has been pulled from Docker Hub more than 10 million times.
While distributed tracing as a concept has been around for a while, the rise of microservices is forcing IT teams to look for tools that make it possible to engage in deeper forensics. The dependencies between microservices coupled with the ephemeral nature of containers often make it challenging for IT organizations to discover the root cause of intermittent issues. Within IT environments that have adopted Kubernetes to run those containers, it’s also become easier to deploy Jaeger using tools as Kubernetes templates, Operator software and a Helm Chart.
As developers are held more accountable for applications, interest in programmable forensics tools is rising. Performance issues that developers once viewed as a problem to be solved by faceless IT operations staffs are now being solved much faster by developers. As a result, application experiences have improved now that developers are seeking out tools such as Jaeger to identify issues that are preventing them from focusing their efforts on writing additional code. Given the long, difficult history of IT, there are more than a few IT leaders wondering what took them so long to figure that out.
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