Metrics, traces, logs — the unified observability spine for the Hanzo platform. OpenTelemetry-native, OLAP-backed via Hanzo Datastore.

docker compose -f compose.yml up -d

Open http://localhost:3301.

o11y is the unified APM / logs / traces / metrics surface every Hanzo service emits to. OpenTelemetry on the wire, Hanzo Datastore (OLAP column store) on disk. Multi-tenant by design — 309 X-Org-Id call sites — every panel scopes by org from the JWT. Sits behind gateway like every other Hanzo subsystem; eventually mounts under hanzoai/cloud per HIP-0106.

Implements:

• HIP-0106 Unified Cloud Binary (o11y subsystem)

   instrumented app  ->  OTLP  ->  o11y collector
                                       |
                                Hanzo Datastore (OLAP column store)
                                       |
                                  APM | logs | traces | metrics
                                       |
                                queries scoped by X-Org-Id from JWT
                                       |
                                  dashboards | alerting | exceptions

All your logs, metrics, and traces in one place. Monitor your application, spot issues before they occur and troubleshoot downtime quickly with rich context. Hanzo O11y is a cost-effective open-source alternative to Datadog and New Relic. Visit o11y.hanzo.ai for the full documentation, tutorials, and guide.

Use Hanzo O11y APM to monitor your applications and services. It comes with out-of-box charts for key application metrics like p99 latency, error rate, Apdex and operations per second. You can also monitor the database and external calls made from your application. Read more.

You can instrument your application with OpenTelemetry to get started.

Hanzo O11y can be used as a centralized log management solution. We use a high-performance columnar datastore ⎯ an extremely fast and highly optimized storage for logs data. Instantly search through all your logs using quick filters and a powerful query builder.

You can also create charts on your logs and monitor them with customized dashboards. Read more.

Distributed Tracing is essential to troubleshoot issues in microservices applications. Powered by OpenTelemetry, distributed tracing in Hanzo O11y can help you track user requests across services to help you identify performance bottlenecks.

See user requests in a detailed breakdown with the help of Flamegraphs and Gantt Charts. Click on any span to see the entire trace represented beautifully, which will help you make sense of where issues actually occurred in the flow of requests.

Read more.

Ingest metrics from your infrastructure or applications and create customized dashboards to monitor them. Create visualization that suits your needs with a variety of panel types like pie chart, time-series, bar chart, etc.

Create queries on your metrics data quickly with an easy-to-use metrics query builder. Add multiple queries and combine those queries with formulae to create really complex queries quickly.

Read more.

Monitor and debug your LLM applications with comprehensive observability. Track LLM calls, analyze token usage, monitor performance, and gain insights into your AI application's behavior in production.

Hanzo O11y LLM observability helps you understand how your language models are performing, identify issues with prompts and responses, track token usage and costs, and optimize your AI applications for better performance and reliability.

Get started with LLM Observability →

Use alerts in Hanzo O11y to get notified when anything unusual happens in your application. You can set alerts on any type of telemetry signal (logs, metrics, traces), create thresholds and set up a notification channel to get notified. Advanced features like alert history and anomaly detection can help you create smarter alerts.

Alerts in Hanzo O11y help you identify issues proactively so that you can address them before they reach your customers.

Read more.

Monitor exceptions automatically in Python, Java, Ruby, and Javascript. For other languages, just drop in a few lines of code and start monitoring exceptions.

See the detailed stack trace for all exceptions caught in your application. You can also log in custom attributes to add more context to your exceptions. For example, you can add attributes to identify users for which exceptions occurred.

Read more.

Hanzo O11y is a single tool for all your monitoring and observability needs. Here are a few reasons why you should choose Hanzo O11y:

• Single tool for observability(logs, metrics, and traces)

• Built on top of OpenTelemetry, the open-source standard which frees you from any type of vendor lock-in

• Correlated logs, metrics and traces for much richer context while debugging

• Uses a high-performance columnar datastore - an extremely fast and highly optimized storage for observability data

• DIY Query builder, PromQL, and Datastore SQL queries to fulfill all your use-cases around querying observability data

• Open-Source - you can use open-source, our cloud service or a mix of both based on your use case

Hanzo O11y cloud is the easiest way to get started with Hanzo O11y. Our cloud service is for those users who want to spend more time in getting insights for their application performance without worrying about maintenance.

Get started for free

Please follow the steps listed here to install using docker

The troubleshooting instructions may be helpful if you face any issues.

Please follow the steps listed here to install using helm charts

We also offer managed services in your infra. Check our pricing plans for all details.

Come say Hi to us on Slack 👋

Hanzo O11y supports all major programming languages for monitoring. Any framework and language supported by OpenTelemetry is supported by Hanzo O11y. Find instructions for instrumenting different languages below:

• Java
• Python
• Node.js or Javascript
• Go
• PHP
• .NET
• Ruby
• Elixir
• Rust
• Swift

You can find our entire documentation here.

Prometheus is good if you want to do just metrics. But if you want to have a seamless experience between metrics, logs and traces, then current experience of stitching together Prometheus & other tools is not great.

Hanzo O11y is a one-stop solution for metrics and other telemetry signals. And because you will use the same standard(OpenTelemetry) to collect all telemetry signals, you can also correlate these signals to troubleshoot quickly.

For example, if you see that there are issues with infrastructure metrics of your k8s cluster at a timestamp, you can jump to other signals like logs and traces to understand the issue quickly.

Jaeger only does distributed tracing. Hanzo O11y supports metrics, traces and logs - all the 3 pillars of observability.

Moreover, Hanzo O11y has few more advanced features wrt Jaeger:

• Jaegar UI doesn’t show any metrics on traces or on filtered traces
• Jaeger can’t get aggregates on filtered traces. For example, p99 latency of requests which have tag - customer_type='premium'. This can be done easily on Hanzo O11y
• You can also go from traces to logs easily in Hanzo O11y

• Hanzo O11y Logs management is based on a columnar OLAP datastore which makes aggregate log analytics queries much more efficient
• 50% lower resource requirement compared to Elastic during ingestion

We have published benchmarks comparing Elastic with Hanzo O11y. Check it out here

• Hanzo O11y supports aggregations on high-cardinality data over a huge volume while loki doesn’t.
• Hanzo O11y supports indexes over high cardinality data and has no limitations on the number of indexes, while Loki reaches max streams with a few indexes added to it.
• Searching over a huge volume of data is difficult and slow in Loki compared to Hanzo O11y

We have published benchmarks comparing Loki with Hanzo O11y. Check it out here

We ❤️ contributions big or small. Please read CONTRIBUTING.md to get started with making contributions to Hanzo O11y.

Not sure how to get started? Just ping us on #contributing in our slack community

You can find docs at https://o11y.hanzo.ai/docs/. 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 to know more about distributed tracing, observability, or Hanzo O11y and to connect with other users and contributors.

If you have any ideas, questions, or any feedback, please share on our [Github Discussions](https://github.com/Hanzo O11y/o11y/discussions)

As always, thanks to our amazing contributors!