SigNoz is an opensource observability platform. SigNoz uses distributed tracing to gain visibility into your systems and powers data using [Kafka](https://kafka.apache.org/) (to handle high ingestion rate and backpressure) and [Apache Druid](https://druid.apache.org/) (Apache Druid is a high performance real-time analytics database), both proven in the industry to handle scale.
- See exact request trace to figure out issues in downstream services, slow DB queries, call to 3rd party services like payment gateways, etc
- Filter traces by service name, operation, latency, error, tags/annotations.
- Aggregate metrics on filtered traces. Eg, you can get error rate and 99th percentile latency of `customer_type: gold` or `deployment_version: v2` or `external_call: paypal`
- Unified UI for metrics and traces. No need to switch from Prometheus to Jaeger to debug issues.
- In-built workflows to reduce your efforts in detecting common issues like new deployment failures, 3rd party slow APIs, etc (Coming Soon)
- SaaS vendors charge an insane amount to provide Application Monitoring. They often surprise you with huge month end bills without any transparency of data sent to them.
**You can choose a different namespace too. In that case, you need to point your applications to correct address to send traces. In our sample application just change the `JAEGER_ENDPOINT` environment variable in `sample-apps/hotrod/deployment.yaml`*
You can find docs at https://signoz.io/docs/deployment/docker. If you need any clarification or find something missing, feel free to raise a GitHub issue with the label `documentation` or reach out to us at the community slack channel.
Join the [slack community](https://app.slack.com/client/T01HWUTP0LT#/) to know more about distributed tracing, observability, or SigNoz and to connect with other users and contributors.
