Use library injection to auto-instrument and trace your Kubernetes applications with Datadog APM

Organizations often use distributed tracing in Datadog APM to monitor the performance of their Kubernetes applications. However, as teams grow and new applications are added, manual configuration becomes impractical. To address this issue, a workflow has been developed that automates instrumentation, allowing for the configuration of tracing for Kubernetes applications without changing or rebuilding the application image. This is achieved by injecting Java, Node.js, and Python tracing libraries directly into the pod at runtime via the Datadog Admission Controller, which only requires writing a single annotation in the application's YAML file. This method does not require altering application code or pushing new container images, thus avoiding the CI/CD pipeline that would otherwise be necessary for building and deploying a new image. As a result, tracing can be set up quickly without any downtime.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.