OpenTelemetry vs APM - The Future of Application Monitoring Explained

Application monitoring is important for finding and fixing issues in modern software systems. Traditionally, teams have used Application Performance Monitoring (APM) tools to track application health and performance. These tools provide built-in features like dashboards, alerting, and error tracking.

Now, OpenTelemetry is becoming popular as an open-source way to collect telemetry data like traces, metrics, and logs. It gives developers more control and avoids vendor lock-in.

In this blog, we will compare OpenTelemetry and APM tools, explain how they work, and help you decide which one is better for your use case or how to use them together.

Table of Contents:

1. What is APM?
2. What is OpenTelemetry and how does it work?
3. OpenTelemetry vs APM: What are the core differences?
4. What kind of data can you collect with APM?
5. What kind of data can you collect with OpenTelemetry?
6. What are the most common use cases of OpenTelemetry vs APM?
7. What challenges you might face with OpenTelemetry?
8. Is OpenTelemetry replacing APM?
9. How does OpenTelemetry integrate with APM tools?
10. How to choose between OpenTelemetry and APM?

What is APM?

Application Performance Monitoring (APM) is a set of tools and practices used to monitor, analyze, and manage the performance, availability, and reliability of applications. Modern APM solutions go beyond basic metrics by offering deep insight into every layer of the application stack, from backend infrastructure to frontend user interactions.

Key Features of APM Tools

• Transaction Tracing: Follow individual user requests through every layer of your stack.
• Automatic Instrumentation: Most APM tools auto-instrument common libraries and frameworks.
• Real-Time Monitoring: Dashboards and live views of system health and performance.
• Error and Exception Tracking: Capture stack traces, contextual metadata, and frequency.
• Infrastructure Correlation: Correlate application behavior with server/network metrics.
• Alerting and Anomaly Detection: AI/ML-driven insights to detect performance degradation.

Examples of top APM tools include: Atatus, Datadog, New Relic, AppDynamics, and Dynatrace

What is OpenTelemetry and how does it work?

OpenTelemetry is an open-source observability framework developed by the Cloud Native Computing Foundation (CNCF). It provides standardized APIs, SDKs, agents, and collectors to generate and export telemetry data—namely logs, metrics, and traces.

Key Components of OpenTelemetry

• OpenTelemetry API: Language-specific interfaces for generating telemetry data.
• OpenTelemetry SDK: Provides default implementation of APIs, including data processors and exporters.
• Collector: A vendor-agnostic agent to receive, process, and export telemetry data.
• Instrumentation Libraries: Community-maintained libraries for common frameworks and platforms.

Supported Signal Types

• Traces: Distributed tracing for understanding request paths and latencies.
• Metrics: Time-series data such as CPU usage, memory, or application-specific counters.
• Logs: Structured log events enriched with context from traces.

OpenTelemetry works by allowing developers to instrument their code using standardized APIs. The collected data can then be exported to various backends, including APM platforms like Jaeger, Prometheus, Grafana, New Relic, or Datadog.

OpenTelemetry vs APM: What are the core differences?

How Does OpenTelemetry Integrate with APM Tools?

This is where the power of interoperability shines. OpenTelemetry acts as the data pipeline, and APM tools act as the destination for analysis.

Example Integration:

• Instrument Java application with OpenTelemetry SDK
• Deploy OpenTelemetry Collector with OTLP exporter
• Send traces and metrics to Datadog or New Relic

Benefits:

• Use one instrumentation strategy across environments
• Avoid vendor lock-in while enjoying APM visualization
• Maintain consistency across distributed microservices

Many APM vendors now accept OpenTelemetry data directly, often offering custom exporters, collectors, or native OTLP (OpenTelemetry Protocol) support.

What kind of data can you collect with APM?

APM tools are designed to collect a wide range of performance and diagnostic data to give you end-to-end visibility into how your applications behave in real time. Here's what you can typically collect:

1. Transaction Traces

• Break down of requests by component or service
• Response times and database query durations
• Call trees to identify slow operations or bottlenecks

2. Metrics

• Application-specific: request rate, error rate, latency
• System-level: CPU, memory, disk I/O, network usage
• Custom metrics for business KPIs

3. Logs

• Error logs, info logs, and custom logs tied to transactions
• Correlation with trace IDs for contextual debugging

4. Errors and Exceptions

• Stack traces, frequency, impacted users
• Root cause insights with code-level visibility

5. User Interactions

• Frontend performance: page load times, core web vitals
• Session replays or heatmaps (for some APMs like Atatus or New Relic)

6. Infrastructure Data

• Health of containers, hosts, and Kubernetes pods
• Correlation between app and infra issues

This combination of traces, metrics, and logs also called the three pillars of observability helps teams monitor the entire application lifecycle, from frontend UX to backend processing and infrastructure dependencies.

What kind of data can you collect with OpenTelemetry?

OpenTelemetry is designed to capture structured telemetry data:

• Spans and Traces with parent-child relationships
• Custom metrics: counters, gauges, histograms
• Log data enriched with trace IDs
• Context propagation: Distributed Context (baggage and correlation ID)

This standardization makes it easy to export data to any backend, like Jaeger for traces, Prometheus for metrics, or Loki for logs or to use an all-in-one observability platform like Atatus, which supports all three signals (traces, metrics, and logs).

What are the most common use cases of OpenTelemetry vs APM?

OpenTelemetry:

• Cloud-native microservices
• Kubernetes-native instrumentation
• Custom dashboards with Prometheus/Grafana

APM Tools:

• Monitoring monoliths or applications
• Enterprise teams with limited ops bandwidth
• Real-time alerting and anomaly detection
• Built-in incident response integrations (Slack, PagerDuty)

What challenges you might face with OpenTelemetry?

• Steeper learning curve: Requires configuration and understanding of observability principles.
• Data backend dependency: You need to integrate a storage/visualization tool (Jaeger, Prometheus).
• Lack of vendor support for newer frameworks: Community-dependent updates.

Still, it provides long-term value by aligning with open standards and reducing future migration complexity.

Is OpenTelemetry replacing APM?

No. OpenTelemetry is not a replacement for APM, it is a foundational building block. APM solutions still offer analytics, dashboards, and prebuilt visualizations that OpenTelemetry lacks.  

Traditional APM tools come with built-in collectors, dashboards, alerting systems, and advanced analytics. They make it easy to plug in and get insights quickly.

OpenTelemetry, on the other hand, focuses on standardizing data collection. It lets you gather telemetry data, traces, metrics, and logs in a vendor-agnostic, flexible way. You can send this data to any backend you like.

OpenTelemetry is shaping the future of APM by pushing vendors to adopt open standards. Most APM platforms like Atatus, Datadog, and New Relic now support OpenTelemetry natively.

How does OpenTelemetry integrate with APM tools?

OpenTelemetry integrates seamlessly with APM tools by acting as a data pipeline that collects, processes, and exports telemetry data (such as traces, metrics, and logs). Here’s how the integration typically works:

Instrumentation:

Developers instrument their applications using the OpenTelemetry SDKs and APIs. These libraries automatically collect telemetry data like traces (request flows), metrics (system performance), and logs (error details).

OpenTelemetry supports various languages and frameworks, so your applications can be instrumented in a consistent, vendor-agnostic way.

Exporting Data:

Once the application is instrumented, the collected telemetry data needs to be sent to a backend for visualization and analysis. OpenTelemetry uses exporters to send data to different backends.

Many APM tools, such as Atatus, Datadog, New Relic, and Dynatrace, support the OpenTelemetry Protocol (OTLP), which allows you to send your telemetry data directly to their platforms.

Collector:

OpenTelemetry can use a Collector as an intermediary component. The Collector receives, processes, and exports the telemetry data, allowing for operations like batching, filtering, and enriching before sending it to the APM tool.

This process can include transforming data formats or handling sampling to manage the volume of data being sent to APM systems.

Integration Points:

Many APM tools now provide native integrations or exporters for OpenTelemetry, allowing organizations to integrate their instrumentation with minimal friction. These integrations ensure that the data generated by OpenTelemetry can be visualized and analyzed using the APM platform’s dashboards, alerting systems, and analytics.

Interoperability:

The real strength of OpenTelemetry in the APM ecosystem is its interoperability. You can use OpenTelemetry to collect telemetry data from various services and applications, and export that data to multiple APM tools if needed. This avoids vendor lock-in while still gaining the benefits of advanced monitoring and analytics provided by APM tools.

How to choose between OpenTelemetry and APM?

Choosing between OpenTelemetry and an APM tool isn’t always about picking one over the other, it’s about understanding what you need right now and what you are planning for in the future.

Frequently Asked Questions (FAQs)

Is OpenTelemetry free to use?
Yes, OpenTelemetry is fully open-source under the Apache 2.0 license.

Can I use OpenTelemetry with Datadog or New Relic?
Absolutely. Most major APM vendors now support OpenTelemetry through exporters or native integrations.

Does OpenTelemetry offer its own dashboards or UI?
No, you will need a backend like Grafana, Jaeger, or an APM tool like Atatus for visualization.

What is OTLP in OpenTelemetry?
OTLP (OpenTelemetry Protocol) is the default protocol for exporting data in OpenTelemetry. It's supported by most collectors and exporters.

Can I monitor logs using OpenTelemetry?
Yes, but logging support is still evolving. Currently, traces and metrics are the most stable signals.

Which is better for Kubernetes monitoring, OpenTelemetry or APM?
OpenTelemetry offers more flexibility and is better suited for Kubernetes-native deployments.

What happens to telemetry data after it’s generated?
It is collected, enriched, transformed, exported, stored, and then visualized through dashboards and alerts in APM tools or observability platforms.