Pixie - Amazon Managed Grafana
Using Pixie

Pixie

Note

In workspaces that support version 9 or newer, this data source might require you to install the appropriate plugin. For more information, see Grafana plugins.

Pixie is an observability platform for Kubernetes that enables developers to debug, monitor, and explore their applications. Pixie uses eBPF to automatically capture telemetry data without the need for manual instrumentation.

Grafana users can install the Grafana plugin and use Pixie as a datasource in their Grafana dashboards. It can be used to visualize the following data automatically collected in Pixie:

  • Protocol tracing and metrics: Pixie automatically collects full-body messages between the pods of your applications. Supports protocols such as HTTP, MySQL, DNS, and Redis. You can also expose application metrics such as request latency, error rate, and throughput.

  • Resource metrics: CPU, memory and I/O metrics for your pods.

  • Network metrics: Network-layer and connection-level RX/TX statistics.

  • JVM metrics: JVM memory management metrics for Java applications.

  • Application CPU profiles: Sampled stack traces from your application.

Using Pixie

To create a Pixie dashboard, you need to have access to a Kubernetes cluster and access to the Grafana server.

For a tutorial about setting up the Pixie datasource, refer to Adding Pixie as a datasource.

Creating a Pixie panel

To create a Pixie panel, you need to first create a dashboard.

  1. First, create a dashboard. Choose the + icon in the console menu and choose the Create Dashboard menu.

  2. Add a panel to the dashboard.

    In the New Dashboard view, choose Add an empty panel.

  3. In the Edit Panel view, navigate to the Query tab.

  4. Configure the query by selecting Pixie Grafana Datasource Plugin from the data source selector.

  5. Choose the Saveicon to save the dashboard.

Pixie language (PxL)

Pixie uses the Pixie language (PxL) to query telemetry data collected by the Pixie platform.

Pixie language (PxL) is a domain-specific language and uses a Python dialect. It is heavily influenced by the popular data processing library, Pandas, and is almost a subset of Pandas. PxL is used by the Pixie Platform, enabling developers to create high-performance data processing pipelines to monitor, secure, and operate their applications and infrastructure. Like Python, PxL is implicitly typed and supports high-level data types and functions. Unlike Python, PxL is a dataflow language that enables the Pixie platform to optimize its performance while maintaining expressiveness for data processing. PxL programs are typically short-lived and have no implicit side effects. As a result, PxL has no support for classes and exceptions. Such features of Python PxL can be run by the Pixie platform by using either the web-based UI, API or CLI.

For more information on the Pixie language (PxL), refer to PxL.