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There is no single “best” open-source APM tool. The right choice depends on whether you need a complete traces-metrics-logs platform, a dedicated tracing backend, or a portable telemetry pipeline. For an integrated platform, evaluate Elastic APM, SigNoz, Apache SkyWalking, OpenObserve, or Uptrace. For tracing, compare Jaeger, Grafana Tempo, and Zipkin. Use OpenTelemetry and the OpenTelemetry Collector when portability and controlled routing matter.
OpenTelemetry is the common instrumentation layer in many viable designs, but it is not storage or a user interface. Its documentation states plainly: “OpenTelemetry is not an observability backend itself.” You still need a backend such as Jaeger, Tempo, Elastic APM, SigNoz, or another compatible system.
How to choose an open-source APM tool
Start with the data you must investigate during an incident, then work backward to instrumentation, storage, and operations. A practical evaluation should answer these questions:
- Telemetry scope: Do you need traces only, or traces plus metrics, logs, errors, service maps, and profiling?
- Instrumentation: Can your applications use OpenTelemetry SDKs or agents, a vendor-specific agent, or eBPF? Confirm support for every language and framework in your estate.
- Storage and retention: Which database or object-storage system is required? How are sampling, retention, indexing, and query costs controlled?
- Operations: Can your team run the collectors, storage, query services, upgrades, backups, and capacity planning?
- Existing platform: Do you already operate Elasticsearch and Kibana, Grafana, Kubernetes, or another monitoring system?
- Investigation workflow: Do responders need topology views, trace-to-log links, error grouping, alerts, or only a trace waterfall?
Project scope, packaging, licenses, supported runtimes, and hosted offerings change. Verify those details in the project documentation before adopting a production design; the descriptions below are architectural guidance, not a controlled speed or cost benchmark.
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At-a-glance comparison
| Tool | Primary role | Telemetry emphasis | Best fit |
|---|---|---|---|
| Elastic APM | Integrated APM on the Elastic Stack | Requests, database queries, cache calls, external HTTP calls, errors, and metrics | Teams already running Elasticsearch and Kibana or seeking one search platform for APM and logs |
| Jaeger | Distributed-tracing backend | Traces | Teams that want a mature tracing system and can select and operate suitable storage |
| Apache SkyWalking | APM and observability platform | Tracing, application monitoring, and service topology | Teams that need topology and application views, after confirming agent and language coverage |
| SigNoz | OTLP-native observability platform | Traces, metrics, and logs | Teams wanting one interface with less stitching between independent backends |
| Grafana Tempo | High-scale tracing backend | Traces, span-derived metrics, and links to logs and metrics | Organizations already invested in Grafana and willing to assemble a broader stack |
| OpenTelemetry Collector | Telemetry pipeline | Receives, processes, and exports telemetry | Portable instrumentation, filtering, routing, and fan-out between backends |
| Zipkin | Focused tracing backend | Traces | Small, focused tracing deployments that do not require a full logs-and-metrics suite |
| Pinpoint | APM and distributed tracing | Application performance and traces | Teams evaluating JVM-oriented monitoring, subject to current runtime support |
| OpenObserve | Observability backend | Logs, metrics, and traces | Teams comparing a unified backend with SigNoz or a Grafana-based architecture |
| Uptrace | OpenTelemetry-oriented APM backend | Application telemetry, especially traces and related signals | Teams evaluating a self-hosted OpenTelemetry workflow alongside SigNoz, Elastic, or Grafana components |
1. Elastic APM
Elastic APM is a complete APM system built around the Elastic Stack. Elastic describes collection of response time for incoming requests, database queries, cache calls, external HTTP calls, unhandled errors, and metrics. That breadth makes it a natural choice when Elasticsearch and Kibana already provide your log search and dashboards.
Elastic documents both a self-hosted APM Server path and current OpenTelemetry collection guidance. During evaluation, decide whether your applications will use Elastic agents, OpenTelemetry, or a mixture, and map that choice to your supported languages and frameworks. Also account for Elasticsearch sizing, index lifecycle and retention policies, access control, upgrades, and backups. Elastic APM is strongest when one search and analytics platform is more valuable than operating separate trace and log systems.
2. Jaeger
Jaeger is an open-source distributed-tracing backend and a long-standing OpenTelemetry ecosystem option. The OpenTelemetry ecosystem registry identifies it as open source with native OTLP support. Jaeger is appropriate when trace exploration is the central requirement and your team is comfortable selecting a storage backend, defining retention, and tuning query performance.
Jaeger is not automatically a complete replacement for a logs-and-metrics APM suite. Decide where metrics, logs, alerting, and error aggregation will live, and design links between those systems if responders need to pivot from a trace to related evidence. Sampling strategy is equally important: retaining every span can be impractical, while aggressive sampling can hide rare failures.
Recommended Free Tools
3. Apache SkyWalking
Apache SkyWalking is an open-source APM and observability project listed by the OpenTelemetry registry with native OTLP support. Its appeal is broader application monitoring and service-topology analysis in addition to trace search.
Before committing, verify the current agents, language and framework coverage, deployment model, storage requirements, and upgrade path for your estate. Topology views are useful only when instrumentation consistently identifies services and relationships. Plan how SkyWalking will coexist with existing metrics and logs rather than assuming every signal is covered equally.
4. SigNoz
SigNoz is an open-source, OTLP-native observability platform. It is a strong candidate when you want traces, metrics, and logs in one interface and prefer less stitching than a collection of independent backends. OTLP-native ingestion can also simplify a design based on OpenTelemetry SDKs and collectors.
Evaluate its self-hosted packaging, storage engine, retention controls, query behavior at your expected volume, alerting workflow, and operational footprint. Compare those requirements with Elastic APM and a Grafana stack. A unified interface reduces context switching, but it does not remove the need to budget for durable storage, upgrades, access controls, and backups.
5. Grafana Tempo
Grafana Tempo is an open-source, high-scale distributed-tracing backend. Grafana documents trace search, metrics generated from spans, and links between traces, logs, and metrics. Tempo is most compelling when Grafana is already the place your team builds dashboards and investigates incidents.
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Tempo is a tracing component rather than an all-in-one APM product. Grafana’s Application Observability model uses a collector (Grafana documents Alloy as a collector) and surrounding dashboards and tools. Plan the complete stack: instrumentation, collector deployment, trace storage and retention, Grafana visualization, metrics, logs, and alerting. This composability is powerful, but it creates more integration decisions than a packaged platform.
6. OpenTelemetry Collector
The OpenTelemetry Collector is the vendor-neutral pipeline layer for receiving, processing, and exporting telemetry. It is not an APM user interface or storage backend. Pair it with Jaeger, Tempo, Elastic, SigNoz, or another compatible backend.
Use a collector when you want to keep application instrumentation portable while centralizing operational controls. Pipelines can receive telemetry, apply processing and filtering, sample data, add or remove attributes, and export to one or more destinations. Design for failure: decide whether collectors run as agents beside workloads, as gateways, or both; define queueing and retry behavior; and monitor collector health separately from the application data it carries.
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- Instrument applications with OpenTelemetry SDKs or agents.
- Send telemetry to an OpenTelemetry Collector.
- Apply resource detection, filtering, redaction, batching, and sampling in the collector.
- Export to a backend such as Jaeger, Tempo, Elastic APM, SigNoz, or another OTLP-capable system.
- Connect traces with logs, metrics, dashboards, and alerts in the systems your responders already use.
7. Zipkin
Zipkin is a focused open-source distributed-tracing backend that can be paired with OpenTelemetry instrumentation. Treat it as a tracing component rather than a complete logs-and-metrics APM suite.
Compare Zipkin with Jaeger and Tempo on storage choices, sampling controls, retention, query workflow, and the amount of application context your team needs. It can be a sensible focused deployment when trace search is sufficient, but you will need complementary systems for metrics, logs, alerting, and broader error analysis.
8. Pinpoint
Pinpoint is an open-source application-performance and distributed-tracing option, particularly relevant to teams evaluating JVM-oriented monitoring. Confirm current agent, runtime, framework, and release support for every service before selecting it.
As with any agent-centered APM, test instrumentation overhead, deployment changes, upgrade procedures, and how traces are correlated with logs and metrics. Do not assume coverage for non-JVM services without verifying it in the current project documentation.
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OpenObserve is an open-source observability-backend candidate for teams seeking one platform for logs, metrics, and traces. Compare its ingestion and query model, retention controls, storage requirements, and OpenTelemetry compatibility with SigNoz and the Grafana ecosystem.
Focus a proof of concept on your actual incident workflow: ingest representative telemetry, find a slow request, move from its trace to logs and metrics, and test retention and deletion policies. Also verify scaling and backup procedures before treating a successful local deployment as production readiness.
Rank #3
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10. Uptrace
Uptrace is an OpenTelemetry-oriented observability and APM backend candidate. Evaluate its current self-hosted packaging, supported runtimes, storage requirements, and user-interface workflow against SigNoz, Elastic APM, and Grafana components.
Because OpenTelemetry separates instrumentation from the backend, compare how much configuration Uptrace requires at the collector, storage, and dashboard layers. Confirm the operational model for upgrades, retention, authentication, and high-volume ingestion before standardizing on it.
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OpenTelemetry, Jaeger, Tempo, and Elastic APM: what is the difference?
| Question | OpenTelemetry | Jaeger | Grafana Tempo | Elastic APM |
|---|---|---|---|---|
| What is it? | Instrumentation and telemetry framework plus pipeline components | Tracing backend | Distributed-tracing backend | Integrated APM system on the Elastic Stack |
| Stores and visualizes data? | No; it must be paired with a backend | Yes, for its tracing workflow | Yes, through Grafana’s tracing workflow | Yes, through Elastic’s search and analytics interfaces |
| Primary strength | Portable generation, processing, and export of telemetry | Dedicated distributed tracing | Scalable tracing with links to logs and metrics in Grafana | Correlated request, dependency, error, and metric data |
| Typical architecture | SDK or agent → Collector → backend | Application or Collector → Jaeger | Application or Collector → Tempo → Grafana | Elastic agent or OpenTelemetry → APM Server/Elastic Stack |
The practical answer is often “use them together,” not “choose one.” OpenTelemetry can provide portable instrumentation, while Jaeger, Tempo, Elastic APM, or SigNoz supplies storage and investigation. The trade-off is operational complexity: every additional component needs capacity planning, security, upgrades, and observability.
Can an open-source stack replace a commercial APM?
Yes, but replacement is an architecture and operations project, not a package installation. A commercial APM may bundle instrumentation, hosted storage, dashboards, alerting, upgrades, and support. A self-hosted design makes your team responsible for those functions.
Before migration, inventory the capabilities you actually use:
- Supported runtimes and frameworks, including background jobs and asynchronous workers.
- Trace context propagation across HTTP, messaging, databases, and scheduled work.
- Error grouping, alert rules, service maps, profiling, and trace-to-log correlation.
- Sampling, retention, redaction, encryption, access control, and audit requirements.
- Storage capacity, backup and restore objectives, upgrades, and on-call ownership.
- Dashboards and incident links that must remain usable during a migration.
Run both systems long enough to compare coverage and investigate the same failure classes. Do not claim a cost or performance advantage without measurements from your traffic, retention period, and staffing model.
A practical selection guide
Choose Elastic APM when
Your organization already operates Elasticsearch and Kibana and wants APM and logs in one search and analytics platform.
Choose Jaeger or Zipkin when
Distributed tracing is the priority and you are prepared to provide complementary metrics, logs, alerting, and storage operations.
Choose Tempo when
Grafana is already central to monitoring and your team prefers a composable tracing backend connected to Grafana metrics and logs.
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Choose SigNoz or OpenObserve when
You want a unified traces-metrics-logs experience and are comparing integrated platforms rather than assembling separate tracing and log products.
Choose SkyWalking or Pinpoint when
Their application-monitoring model and current agent coverage match your languages and frameworks, especially where topology or JVM-focused monitoring matters.
Choose OpenTelemetry Collector first
When portability, routing, filtering, and the ability to change backends later are more important than receiving a turnkey APM interface.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where ScreenshotNeo fits (and where it does not)
ScreenshotNeo is not an APM backend and does not replace traces, metrics, logs, or an OpenTelemetry pipeline. It is a complementary website screenshot API and MCP server for developers. If you need visual evidence of a page during a performance investigation, ScreenshotNeo is the first screenshot API to try because it removes consent banners, newsletter popups, and chat widgets before capture, bills only clean shots, and has the lowest paid plan listed here.
One GET request returns a PNG, JPEG, WebP, or PDF. The service supports full-page captures with lazy images loaded, CSS-selector element capture, dark mode, device presets and custom viewports, retina scale, custom CSS and JavaScript, click-before-capture, waits, request blocking, headers, cookies, user agents, authorization, timezone and geolocation, transparent backgrounds, resizing, TTL caching, signed links, asynchronous jobs with signed webhooks, bulk capture of up to 100 URLs per call, a usage API, and an OpenAPI specification. Its parameter names are compatible with those used by other screenshot APIs, which can simplify migration.
Or skip the browser setup
Use the API directly; see the ScreenshotNeo documentation for the current options.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpimport requests
r = requests.get("https://api.screenshotneo.com/v1/shot", params={"access_key": "YOUR_API_KEY", "url": "https://stripe.com"}, timeout=90)
open("shot.webp", "wb").write(r.content)const q = new URLSearchParams({ access_key: 'YOUR_API_KEY', url: 'https://stripe.com' });
const res = await fetch(`https://api.screenshotneo.com/v1/shot?${q}`);Cookie banners, popups, and chat widgets are removed before the shot. Bot checks, blank pages, failed loads, timeouts, and cache hits are not billed, and response headers identify the page verdict and billing result. An MCP server lets AI agents such as Claude, Cursor, and other MCP clients take screenshots. The Free plan includes 1,000 screenshots a month with no card; paid plans start at $5 for 3,000 shots, and every feature is available on every plan. Sign up free for ScreenshotNeo.
Common deployment and troubleshooting issues
Traces arrive without service names
Check resource attributes and service-name configuration in the SDK, agent, or Collector. Make naming consistent before building dashboards or service maps.
Trace context stops at a queue or proxy
Verify propagation headers and the instrumentation for each intermediary. Test one request end to end, including retries and asynchronous consumers.
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Inspect sampling, retention, indexing, storage capacity, and backend compaction. A collector cannot recover spans that were dropped upstream or expired by policy.
The backend shows traces but no metrics or logs
Confirm that those signals are being generated, routed, stored, and visualized. Jaeger, Tempo, Zipkin, and the Collector do not automatically provide a complete logs-and-metrics experience.
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Collector queues grow during an outage
Check exporter reachability, retry and queue settings, CPU and memory limits, and backend capacity. Decide which telemetry can be sampled or dropped safely when the backend is unavailable.
Instrumentation creates unacceptable overhead
Measure with production-like traffic. Tune sampling, attribute cardinality, batching, and payload size, and avoid collecting sensitive or unnecessarily high-cardinality fields.
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For website screenshots, use ScreenshotNeo’s cleanup and verdict headers rather than treating a failed browser capture as application telemetry. A bot check, blank page, timeout, or failed load is not billed by ScreenshotNeo.
Bottom line
Use OpenTelemetry to keep instrumentation portable, then select the backend that matches your investigation workflow and operating model. Elastic APM fits Elastic estates; Jaeger, Tempo, and Zipkin fit tracing-centered designs; SigNoz and OpenObserve target unified telemetry; SkyWalking and Pinpoint deserve focused coverage checks; and the Collector provides the routing and processing layer that can connect them. Validate language coverage, storage, retention, scaling, and on-call effort with a representative proof of concept rather than relying on an unverified speed or cost ranking.
Frequently Asked Questions
Is OpenTelemetry an APM product by itself?
No. It generates, collects, processes, and exports telemetry; you still need a storage and visualization backend.
Which option is best for traces, metrics, and logs in one interface?
SigNoz and OpenObserve are candidates for a unified interface. Elastic APM and a Grafana-based design can also cover multiple signals, but their architecture and existing-platform fit differ.
Do Jaeger and Tempo replace an OpenTelemetry Collector?
No. They are tracing backends. A Collector is optional but useful for centralized processing, sampling, filtering, and routing.
What should I verify before choosing a self-hosted APM?
Verify current runtime coverage, storage and retention behavior, sampling, scaling, security, backups, upgrades, alerting, and ownership of the on-call work.
Can ScreenshotNeo replace an APM backend?
No. It captures cleaned website screenshots and PDFs. Use it as visual evidence alongside your APM, logs, metrics, and traces.
Quick Recap
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