Best Open Source APM Tools 2026
Ranked list of 8 open source APM and observability tools evaluated on features, self-hosting complexity, community health, and total cost of ownership.
SigNoz
Best all-in-one open source APMSigNoz provides a unified open-source platform for traces, metrics, and logs with a Datadog-like UI. Built on ClickHouse for high-performance analytics, it offers the most complete self-hosted APM experience. Single Docker Compose deployment makes it the easiest to get started with. The cloud-hosted option starts at $199/month for teams that prefer managed infrastructure.
Pros
- All-in-one: traces, metrics, logs, and dashboards
- ClickHouse backend for fast analytical queries
- Simplest self-hosted setup with Docker Compose
- Native OpenTelemetry support
Cons
- Smaller community than Jaeger or Prometheus
- Cloud pricing is relatively high compared to competitors
- Fewer integrations than established tools
Jaeger
Best CNCF tracing toolJaeger is the CNCF graduated distributed tracing platform originally developed at Uber. It is the most widely deployed open-source tracing tool with production usage at thousands of organizations. Jaeger supports multiple storage backends (Cassandra, Elasticsearch, Kafka) and provides excellent trace visualization. It focuses purely on tracing rather than full observability.
Pros
- CNCF graduated project with strong governance
- Battle-tested at Uber-scale production workloads
- Multiple storage backends for flexibility
- Excellent trace comparison and analysis UI
Cons
- Tracing only -- no metrics, logs, or dashboards
- Requires separate tools for complete observability
- UI is functional but less polished than commercial alternatives
Zipkin
Best for lightweight tracingZipkin is one of the original distributed tracing systems, inspired by Google's Dapper paper. Its simplicity is its strength -- a single JAR file can get you started with trace collection and visualization. Zipkin supports in-memory, MySQL, Cassandra, and Elasticsearch storage. While it lacks the features of newer tools, its stability and minimal resource requirements make it ideal for teams with modest tracing needs.
Pros
- Extremely lightweight and simple to deploy
- Single JAR file deployment option
- Mature and stable with years of production use
- Low resource requirements
Cons
- Limited to basic tracing functionality
- No metrics, logging, or dashboard features
- Less active development than newer alternatives
Grafana Tempo
Best for Grafana ecosystem usersGrafana Tempo is a high-scale distributed tracing backend designed to work seamlessly with the Grafana visualization platform. Unlike Jaeger or Zipkin, Tempo stores traces in object storage (S3, GCS, Azure Blob), dramatically reducing storage costs at scale. Combined with Grafana, Loki, and Mimir, it forms a complete open-source observability stack. The trade-off is operational complexity -- Tempo is designed for Kubernetes environments and requires familiarity with distributed systems.
Pros
- Object storage backend dramatically reduces costs at scale
- Deep integration with Grafana, Loki, and Mimir
- TraceQL query language for powerful trace analysis
- Designed for massive scale with minimal indexing
Cons
- Requires Kubernetes and distributed systems expertise
- Only meaningful with Grafana -- not standalone
- Search capabilities require Tempo Search or TraceQL adoption
TraceKit
Best open-source SDKs with hosted platform Our PickTraceKit offers open-source SDKs (MIT licensed) for Go, Node.js, Python, Java, .NET, Ruby, PHP, and Laravel, while the platform itself is a hosted SaaS service. This is not a fully self-hosted solution, but the open SDKs mean no vendor lock-in at the instrumentation layer. TraceKit's unique value is combining tracing with live production debugging -- non-breaking breakpoints and snapshot capture that other open-source tools lack.
Pros
- Open-source SDKs across 8 languages (MIT license)
- Unique live debugging and snapshot capture capabilities
- No vendor lock-in at the instrumentation layer
- Bridges monitoring and debugging in a single tool
Cons
- Platform is SaaS-only -- cannot fully self-host
- Newer product with smaller community
- Fewer integrations than Jaeger or Grafana ecosystem
Prometheus + Grafana
Best for metrics-focused monitoringPrometheus is the CNCF graduated metrics monitoring system that has become the de facto standard for cloud-native metrics. Combined with Grafana for visualization, it provides powerful metric collection, alerting, and dashboarding. PromQL is one of the most expressive query languages for time-series data. Prometheus does not handle traces or logs natively, so teams pair it with Jaeger or Loki for complete observability.
Pros
- CNCF graduated with massive community adoption
- PromQL is the industry standard for metrics queries
- Pull-based model simplifies service discovery
- Extensive ecosystem of exporters and integrations
Cons
- Metrics only -- no traces or logs natively
- Local storage limits long-term retention without Thanos or Cortex
- Pull model can be challenging in ephemeral or serverless environments
Uptrace
Best for OpenTelemetry-native teamsUptrace is an open-source APM built on ClickHouse that accepts OpenTelemetry data natively. It provides traces, metrics, and logs with a modern UI. Uptrace focuses on the OpenTelemetry ecosystem rather than building proprietary agents, making it a good choice for teams that have already invested in OTel instrumentation. The community is smaller than SigNoz or Jaeger, but the project is actively maintained.
Pros
- Native OpenTelemetry ingestion with no adapters needed
- ClickHouse backend for fast queries
- Traces, metrics, and logs in a single tool
- Modern, clean UI with good UX
Cons
- Smaller community and fewer contributors
- Less documentation than more established projects
- Enterprise features require paid license
Apache SkyWalking
Best for Java ecosystemApache SkyWalking is an APM system designed for microservices, cloud native, and container-based architectures. Originally built for Java environments, it has expanded to support multiple languages. SkyWalking provides automatic instrumentation via Java agents, topology maps, and a metrics analysis platform. It has strong adoption in the Asia-Pacific region and is well-suited for Java-heavy microservice architectures.
Pros
- Excellent Java auto-instrumentation via agent
- Apache Software Foundation governance and community
- Service topology maps and dependency analysis
- Built-in alarm and notification system
Cons
- Java-centric -- other language support is less mature
- Documentation primarily in English and Chinese
- Less adoption in North America and Europe
Frequently Asked Questions
Infrastructure costs typically range from $200-$2,000/month for small to medium deployments, depending on data volume and retention needs. You also need to factor in 5-15 hours per week of engineering time for operations, upgrades, and troubleshooting. For small teams, managed SaaS is often more cost-effective. For large organizations, self-hosting can save 50-80% compared to commercial APM pricing.
SigNoz offers the simplest setup with a single Docker Compose file. Zipkin is also extremely simple -- a single JAR file. Jaeger requires more configuration but has excellent Kubernetes support. Grafana Tempo is the most complex, designed for large-scale Kubernetes deployments.
Yes. Jaeger was built for Uber's scale, SigNoz uses ClickHouse for high-throughput analytics, and Grafana Tempo is designed for petabyte-scale trace storage. The key factor is choosing the right storage backend and allocating sufficient infrastructure resources.
OpenTelemetry is recommended for open-source tools since it provides vendor-neutral instrumentation that works across all tools in this list. Most open-source APM tools now support OTel natively, making it the standard choice for new projects.
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