The following guide describes how to setup the OpenTelemetry demo with OpenSearch Observability using Docker compose.

git clone https://github.com/opensearch-project/opentelemetry-demo.git
cd opentelemetry-demo
docker compose up -d

1. Trace Analytics relies on you adding instrumentation to your application and generating trace data. The OpenTelemetry documentation contains example applications for many programming languages that can help you get started, including Java, Python, Go, and JavaScript.

2. The OpenTelemetry Collector receives data from the application and formats it into OpenTelemetry data.

3. Data Prepper processes the OpenTelemetry data, transforms it for use in OpenSearch, and indexes it on an OpenSearch cluster.

4. The Trace Analytics OpenSearch Dashboards plugin displays the data in near real-time as a series of charts and tables, with an emphasis on service architecture, latency, error rate, and throughput.

1. Create an index pattern named ss4o_logs* to explore service logs ingested in OpenSearch via Data prepper

2. Use PPL/SQL/DQL/Lucene to explorer your logs in OpenSearch Dashboards with discover

This repository contains the OpenTelemetry Astronomy Shop, a microservice-based distributed system intended to illustrate the implementation of OpenTelemetry in a near real-world environment.

Our goals are threefold:

• Provide a realistic example of a distributed system that can be used to demonstrate OpenTelemetry instrumentation and observability.
• Build a base for vendors, tooling authors, and others to extend and demonstrate their OpenTelemetry integrations.
• Create a living example for OpenTelemetry contributors to use for testing new versions of the API, SDK, and other components or enhancements.

For detailed documentation, see Demo Documentation. If you're curious about a specific feature, the docs landing page can point you in the right direction.