New Relic is a popular application performance monitoring (APM) tool that allows developers to monitor and troubleshoot their software applications. However, New Relic is a proprietary paid software that can be expensive for some teams and organizations. That’s why many developers are looking for open source alternatives to New Relic that offer similar functionality for free.
Key Takeaways:
- Popular APM tools like New Relic are proprietary and expensive, driving developers to explore quality open source alternatives that offer similar functionality.
- Top open source alternatives like Grafana Tempo, Jaeger, and Prometheus provide robust application monitoring capabilities across traces, metrics, and logs.
- Consider key criteria like integrations, community support, features, scalability, and ease of use when evaluating alternatives.
- The “best” tool depends heavily on an organization’s specific infrastructure, skills and monitoring needs.
- Lightweight instrumentation libraries like OpenTracing allow flexibility to mix and match different open source components as needed.
- While no single tool offers full parity with New Relic’s end-to-end capabilities, combining open source solutions can provide a highly capable APM stack.
In this article, we will look at the top 15 open source alternatives to New Relic in 2024 based on features, ease of use, community support and other factors. Whether you are looking to replace New Relic completely or just want an additional free monitoring tool, this list has some great options worth considering.
Key Considerations for Evaluation
When evaluating open source APM tools as potential alternatives to New Relic, keep a few key criteria in mind:
- Integrations: What other common dev tools does it integrate with for visualization, orchestration, etc? Grafana and Elastic Stack stand out here.
- Community & Support: Is it backed by an active open source community that can provide documentation and assistance?
- Feature Set: Does it cover logging, tracing, and metrics all together or just focus on one area? Think about your specific monitoring needs.
- Scalability: For large scale cloud deployments, analyze the architecture for bottlenecks. Prometheus, Jaeger, and Tempo scale very well.
- Ease of Use: Can new users get started quickly or is the learning curve a cliff? Stagemonitor and Jaeger are quite complex.
The “best” open source APM solution ultimately depends heavily on your organization’s specific needs, team skills, and application infrastructure. Use this list as a starting point for exploration before deciding on replacement tools.
Best Open Source New Relic Alternatives
1. Grafana Tempo
| Core Features | Pros | Cons |
|---|---|---|
| Trace search and analytics, alerts, distributed tracing | Great visualization, integrates with other Grafana tools, easy instrumentation | Steep learning curve, less out of box capabilities |
Grafana Tempo is an open source APM tool focused on traces, metrics, and logs. It’s part of the Grafana ecosystem and integrates tightly with tools like Grafana for advanced visualizations. Tempo is very flexible but has a steeper learning curve than some competitors.
2. Jaeger
| Core Features | Pros | Cons |
|---|---|---|
| Distributed tracing, monitoring visualizer, instrumentation libraries | Feature rich, flexible storage backends, great for microservices | Complex deployment, requires other tools for metrics monitoring |
Jaeger focuses specifically on distributed tracing for complex microservice architectures. It has rich features out of box but requires other tools to get a full view of metrics and logs. The initial deployment can be more complex than other alternatives.
3. Prometheus
| Core Features | Pros | Cons |
|---|---|---|
| Time series monitoring, multi dimensional data model, PromQL query language | Scalable, efficient for containers & microservices, rich tool ecosystem | Time series focused, steep learning curve |
Prometheus is an extremely popular open source monitoring and alerting toolkit that focuses specifically on processing time series data very efficiently. It provides rich capabilities for Kubernetes and cloud native environments. The highly multidimensional data model does mean a steeper learning curve for new users.
4. OpenTracing
| Core Features | Pros | Cons |
|---|---|---|
| Vendor neutral distributed tracing instrumentation | Portable traces across backends, integrated with other tools | Need collection and visualization layer, more piecemeal |
OpenTracing provides an open standard and instrumentation library for distributed tracing that is not locked into any one particular tracing backend or vendor tool. This makes traces portable across many storage and visualization options but does require additional tools to get a full APM solution in place.
5. Pinpoint
| Core Features | Pros | Cons |
|---|---|---|
| Distributed tracing, dashboards, call graphs | Feature rich out-of-box, real user monitoring | Designed for high volume so can be heavy |
Pinpoint was originally developed by Naver and is now an Apache project. For high scale environments, it comes packed with great features out of box like tracing, dashboards, real user metrics, and more. The flip side is that it can also feel overly complex for smaller implementations.
6. Zipkin
| Core Features | Pros | Cons |
|---|---|---|
| Distributed tracing system, UI dashboard and API | Easy data ingestion and querying, multiple storage options | Focused just on tracing data |
Zipkin is a distributed tracing system originally developed by Twitter. It focuses specifically on collecting, aggregating, and querying tracing data with flexibility around storage mechanisms. As a result, it requires additional tools for full metrics and logs visibility.
7. SkyWalking
| Core Features | Pros | Cons |
|---|---|---|
| Tracing, metrics, logs, visualization | Great default dashboards, multiple language agents | Complex deployment, mostly used in Asian market |
Apache SkyWalking originates from China and offers an observability platform encompassing tracing, metrics, and logs all together. It has good default dashboards and broad language support. But the deployment architecture involves many components and SkyWalking hasn’t yet gained critical mass in Western markets.
8. Stagemonitor
| Core Features | Pros | Cons |
|---|---|---|
| Performance metrics, distributed tracing, visual dashboards | Easy setup, automatically instruments common libraries | Limited community support |
Stagemonitor is an open source performance monitoring suite covering metrics, tracing, and visualization. It sets up easily and has automatic instrumentation helpers for frameworks like Spring Boot and Dropwizard. However, the project has a smaller community following than alternatives.
9. Hawkular
| Core Features | Pros | Cons |
|---|---|---|
| Metrics storage and querying, alerting | Feature rich, integrates with many tools | Future uncertain after Red Hat deprioritization |
Hawkular offers an open source solution for collecting, storing, and querying time series metrics data. It has many great built-in features and development was originally driven by Red Hat. But since being moved to a community project, the pace of updates has slowed while users wait to see what the future holds.
10.inspectIT
| Core Features | Pros | Cons |
|---|---|---|
| Performance monitoring, transaction tracing analysis | Lightweight, advanced transaction analysis | Setup requires Java expertise |
inspectIT offers lightweight performance management and transaction tracing for Java applications, letting developers drill down to analyze root causes. Being focused just on Java does however limit broader technology stack tracing. And the instrumentation configuration demands specific Java expertise.
11. Elastic APM
| Core Features | Pros | Cons |
|---|---|---|
| Metrics monitoring, distributed tracing, logs | Leverages full Elastic Stack ecosystem | Poor default visualizations for APM data |
The Elastic APM solution covers the key observability pillars of metrics, tracing, and logs by building upon Elastic’s proven open source stack that includes Elasticsearch, Kibana, Beats, and Logstash. The downside is the out-of-box Kibana dashboards are not well optimized for visualizing performance data.
12. eBay Go Toolkit
| Core Features | Pros | Cons |
|---|---|---|
| Tracing instrumentation, metrics collection | Lightweight, supports multiple languages | Requires additional tools for analysis |
The eBay Go Toolkit contains instrumentation to enable tracing and metrics collection across JVM based, Node.js, and other applications. It’s deployed simply as a library. But you still need additional tools to aggregate, analyze, and visualize the data.
13. Kamon
| Core Features | Pros | Cons |
|---|---|---|
| Metrics, tracing, logging for JVM & Scala apps | Highly scalable, very low overhead | Focused on Scala ecosystem |
Kamon provides an APM and instrumentation toolkit optimized specifically for the scale and performance demands of applications written with Scala and Akka. It supports tracing and metrics collection with very low overhead. But the toolset is primarily designed just for JVM services written in Scala.
14. Hunter
| Core Features | Pros | Cons |
|---|---|---|
| Metric visualization and alarming | Customizable dashboards, flexible architecture | Large scope can be overwhelming |
Hunter provides visualization and alerts for time series metrics data. It allows full customization over dashboarding and has a modular architecture. But with a very large scope tackling metrics, logs, and tracing all together, new users may feel overwhelmed configuring everything.
15. Trace Compass
| Core Features | Pros | Cons |
|---|---|---|
| Trace analysis and visualization | Advanced analysis features | Steep learning curve |
Trace Compass is an Eclipse project focusing just on highly advanced analysis of trace data. So it requires sending trace data to the tool from elsewhere first. Trace Compass enables very sophisticated timing and sequence analysis. But its depth comes at the cost of approachability for more casual end users.
Conclusion: Viable Open Source Options Available
While New Relic established itself early as a leader in application performance monitoring, compelling open source alternatives have continued maturing on pace with the DevOps toolchain revolution. Solutions like Grafana Tempo, Jaeger, Prometheus, and Elastic APM now provide full featured observability stacks for cloud scale environments.
And lighter weight instrumentation libraries like OpenTracing allow flexibility to mix and match just the components you need. Hopefully this guide of the top 15 open source options for replacing New Relic gave you some great candidates to evaluate further on your journey towards innovation and scale. Reach out if we can ever help with advice or support!
Frequently Asked Questions
Which open source APM tool has the widest language and framework coverage?
Based on community instrumentation and integration libraries, OpenTracing, Zipkin, and Jaeger have very broad coverage across languages for distributed tracing. Prometheus similarly has extensive metrics instrumentation libraries for most languages and frameworks.
Can I replace all New Relic capabilities with a single open source tool?
It is difficult to find full parity with one single tool due to New Relic’s end-to-end proprietary architecture. But combining a tracing system (Jaeger), metrics engine (Prometheus), and visualization layer (Grafana) provides highly robust APM capabilities.
How hard is it to deploy these open source solutions?
Ease of deployment spans the spectrum based on which tools you select. Prometheus, Zipkin, and Tempo are reasonably straightforward to install for metrics, tracing, and visualization. Solutions like Pinpoint and SkyWalking involve many more components and architecture planning for large scale operation.
Can I visualize open source APM data in tools other than Grafana?
Definitely! Kibana, Trace Compass, Hunter, and even notebook environments like Jupyter can be great visualization layers, depending on how much customization you want compared to Grafana’s more turnkey dashboards.
Which alternative is most scalable for high traffic cloud native environments?
When working with large microservices architectures, distributed tracing systems like Jaeger and Tempo tend to handle scale the best since they were designed specifically for cloud native complexity. Prometheus also works very efficiently for large volumes of metrics data.
