OpenTelemetry vs Elastic APM - Which Monitoring Tool to Choose?

In today’s complex software landscape, observability has become essential. Developers and DevOps teams need tools that provide actionable insights into the health and performance of applications, ensuring smooth functionality and optimal user experience. As observability gains prominence, the choice between vendor-specific solutions like Elastic APM and open-source frameworks like OpenTelemetry becomes a key decision for organizations.

This article discusses OpenTelemetry and Elastic APM, highlighting their features, functionalities, and key differences to help you make an informed decision based on your organization's unique needs, available resources, and scalability requirements.

Understanding OpenTelemetry and Elastic APM

OpenTelemetry and Elastic APM are two widely used tools in observability and application performance monitoring (APM), each with its own approach and strengths.

OpenTelemetry as an Open-Source Observability Framework and Industry Standard

OpenTelemetry is an open-source observability framework designed to standardize the collection and transfer of telemetry data. It enables instrumentation across diverse services, applications, and platforms without locking users into a specific vendor solution.

As a vendor-neutral solution, it allows organizations to choose backend analysis tools, ensuring flexibility in technology stacks. This capability makes OpenTelemetry highly popular for cloud-native and microservices-based architectures where services often need compatibility across different tools and platforms.

Elastic APM as a Comprehensive Application Performance Monitoring Solution

Elastic APM (Application Performance Monitoring) is part of the Elastic Stack, an end-to-end solution that includes ElasticSearch, Logstash, and Kibana for data storage, processing, and visualization.

Elastic APM offers a vendor-specific, all-in-one approach to monitoring applications, featuring built-in instrumentation, analytics, and powerful visualization. Its close integration with ElasticSearch and Kibana makes it a strong choice for organizations using the Elastic Stack for log management, metrics, and distributed tracing.

Key Architectural Differences

Examining the fundamental architectural differences between OpenTelemetry and Elastic APM helps in selecting the right observability tool based on your organization's flexibility, integration, and data control requirements. Here’s a look at some of the architectural differences between both tools:

Decoupled vs. Tightly Coupled Architecture

• OpenTelemetry adopts a decoupled, vendor-neutral architecture where data collection is completely separated from storage and visualization. This means you can collect data once and send it to any supported backend system of your choice.
• In contrast, Elastic APM uses a tightly coupled architecture where all components are specifically designed to work within the Elastic ecosystem, binding data collection directly to Elasticsearch for storage and Kibana for visualization.

Data Protocols

• OpenTelemetry uses a standardized protocol (OTLP - OpenTelemetry Protocol) that allows for consistent data formatting and transmission across any system or vendor that supports the standard. This means the data format and collection methods remain the same regardless of where the data ultimately ends up.
• Elastic APM, on the other hand, uses a proprietary protocol specifically optimized for the Elastic Stack. While this enables deep integration and optimized performance within the Elastic ecosystem, it means the data is formatted and transmitted in a way that's primarily designed to work with Elasticsearch.

Data Collection and Flexibility

• OpenTelemetry uses a collector that can process, filter, and export telemetry data to various observability platforms, giving users control over data flow and reducing vendor lock-in.
• Elastic APM relies on specialized agents that send data directly to an APM Server, which forwards it to Elasticsearch. While this ensures smooth integration with Elastic components, it limits flexibility in backend choice.

Instrumentation Model

• OpenTelemetry uses a modular instrumentation model with pluggable components. It provides a set of standardized instrumentation libraries and APIs that can be selectively implemented and customized. This means you can choose which components to use, add custom instrumentation, and modify the data collection process based on your needs.
• Elastic APM uses a more rigid, agent-based instrumentation approach. Its agents are pre-configured and specifically designed to work with the Elastic Stack. While they offer automatic instrumentation that's easier to set up initially, they provide less flexibility in terms of customization and component selection.

Core Capabilities and Supported Technologies

Understanding the core capabilities and supported technologies of OpenTelemetry and Elastic APM is essential for selecting the right observability solution. They include:

Instrumentation Support

• OpenTelemetry provides broad instrumentation across a wide range of programming languages and frameworks, enabling flexible and scalable observability setups.
• Elastic APM supports various programming languages with built-in agents, offering seamless integration with applications and the Elastic Stack.

Distributed Tracing

• OpenTelemetry specializes in comprehensive distributed tracing that can be customized for complex, multi-cloud environments and integrated with different backends.
• Elastic APM offers robust distributed tracing capabilities tied closely with other Elastic Stack components for enhanced trace visualization and analysis.

Features and Capabilities

OpenTelemetry and Elastic APM offer distinct features and support options that cater to different observability needs and integration preferences. The table below highlights the key differences between the capabilities of these two tools:

Instrumentation Support and Language Coverage

• OpenTelemetry’s strength lies in its flexibility. It supports a wide range of programming languages like Java, Python, Node.js, .NET, and Ruby, making it ideal for polyglot environments. It also allows both automatic and manual instrumentation, giving developers full control over which sections of code to trace.
• Elastic APM also supports popular languages (Java, Go, Node.js, Python, Ruby) and provides language-specific agents that are easy to set up, especially for common frameworks like Spring, Django, and Express. Auto-instrumentation is heavily featured, with minimal manual setup required.

Data Collection Methods and Telemetry types

• OpenTelemetry collects traces, metrics, and logs. This triad enables full observability, with traces tracking request flows, metrics providing system health data, and logs offering detailed contextual insights.
• Elastic APM primarily focuses on traces and logs but also gathers some system metrics (like CPU, memory). Elastic APM agents automatically collect these data types, making setup easier for teams with limited instrumentation experience.

Elastic APM doesn’t require manual instrumentation to track basic traces, but you can add custom spans where needed using the APM agent.

Integration Capabilities with Other Tools

• OpenTelemetry is known for its vendor-neutrality, OpenTelemetry integrates easily with popular tools like Jaeger, Prometheus, Zipkin, and Grafana Tempo. This flexibility allows developers to choose their preferred storage and visualization tool, making OpenTelemetry a solid choice for multi-cloud environments.
• Elastic APM is designed to work seamlessly within the Elastic Stack, it integrates naturally with Elasticsearch for data storage and Kibana for visualization. If your organization is already using the Elastic Stack, Elastic APM provides a streamlined experience with optimized data flow.

Performance Overhead Considerations

• OpenTelemetry is lightweight by design but requires careful configuration to manage sampling rates and prevent high data volumes from impacting application performance. The OpenTelemetry Collector can buffer and preprocess data to minimize overhead.
• In the case of Elastic APM, Elastic has built efficiency into its agents with smart sampling and rate limiting, but OneAgent can introduce some overhead, particularly in resource-constrained environments. Elastic APM allows configuration adjustments to optimize for performance versus data granularity.

Making the Choice: Decision Factors

When choosing between OpenTelemetry and Elastic APM, it’s crucial to weigh each solution’s flexibility, support, ease of use, and cost-effectiveness in relation to your organization's needs.

Here’s a comparison table that will help you to understand the practical aspects of selecting either OpenTelemetry or Elastic APM based on their organization’s specific needs and resources.

Vendor Lock-in Considerations and Flexibility

• OpenTelemetry: Highly vendor-neutral, allowing you to choose your preferred backend for telemetry data storage, analysis, and visualization. This flexibility makes OpenTelemetry a preferred option for organizations seeking independence from specific vendors and willing to invest time in setting up compatible infrastructure.
• Elastic APM: As part of the Elastic Stack, Elastic APM is optimized for Elasticsearch and Kibana. While it can be integrated with other tools, Elastic APM is best suited for organizations already invested in Elastic's ecosystem or looking for a centralized stack solution.

Ecosystem and Community Support Comparison

• OpenTelemetry: Being open-source and backed by the Cloud Native Computing Foundation (CNCF), OpenTelemetry has a large, active community and is widely adopted. This community-driven approach means regular updates, extensive documentation, and support for a variety of languages and platforms.
• Elastic APM: The Elastic APM solution benefits from strong, centralized support from Elastic. It includes official documentation and customer support, making it reliable and well-suited for organizations preferring vendor-backed solutions.

Learning Curve and Implementation Complexity

• OpenTelemetry: The flexibility of OpenTelemetry brings a steeper learning curve, as organizations must select and configure compatible backends and dashboards, often requiring specialized knowledge. It’s ideal for teams with dedicated DevOps or SRE staff comfortable with customization.
• Elastic APM: Elastic APM offers a streamlined onboarding experience with minimal setup, especially if you’re already using the Elastic Stack. Automatic instrumentation and built-in dashboards make it approachable for teams new to observability and monitoring.

Cost Implications and Resource Requirements

• OpenTelemetry: While OpenTelemetry itself is open-source, additional costs can accrue based on the backend solution chosen for data storage and visualization. If using managed backends like AWS X-Ray, Jaeger, or Grafana Cloud, costs may scale with data volume and retention requirements.
• Elastic APM: Elastic provides both self-managed and managed options (Elastic Cloud), allowing you to choose between infrastructure costs (self-hosted) or subscription fees (Elastic Cloud). The integrated setup can save costs on multiple tools but may lead to higher costs as data volume increases.

Integration Possibilities

Integrating OpenTelemetry with Elastic APM provides users the flexibility of OpenTelemetry's instrumentation while leveraging Elastic's robust data storage and visualization. Here’s a breakdown of how OpenTelemetry and Elastic APM can complement each other:

Using OpenTelemetry with Elastic APM

OpenTelemetry can be seamlessly integrated with Elastic APM through the OpenTelemetry Collector and Elastic's native OTLP support. Organizations can configure OpenTelemetry-instrumented applications to send their telemetry data (traces, metrics, and logs) to an OpenTelemetry Collector, which then forwards this data to Elastic APM Server using the OTLP exporter.

Since Elasticsearch 7.13, the APM Server has built-in support for ingesting OTLP data, allowing organizations to leverage OpenTelemetry's vendor-neutral instrumentation while still benefiting from Elastic's powerful storage, analysis, and visualization capabilities in Kibana. This hybrid approach enables teams to maintain flexibility in their instrumentation strategy while utilizing Elastic's robust observability platform, effectively getting the best of both worlds - OpenTelemetry's standardized data collection and Elastic's comprehensive analysis tools.

Native OTLP Support in Elastic

Elastic APM now includes native support for OpenTelemetry Protocol (OTLP), simplifying direct integration. This compatibility allows OpenTelemetry to send traces, metrics, and logs directly to Elastic, utilizing Elastic’s APM Server as an OTLP receiver.

Benefits

• Avoids data conversion and processing issues.
• Reduces the need for additional configuration.
• Provides seamless visualization of OpenTelemetry data in Kibana’s APM dashboards.

Hybrid Approach Benefits

A hybrid approach where OpenTelemetry is used for data collection and Elastic APM handles data storage and analysis can offer significant benefits. This approach allows:

• Flexibility in choosing and combining observability tools.
• The ability to migrate gradually from Elastic APM's proprietary agents to OpenTelemetry without disrupting existing systems.
• Better vendor flexibility, allowing for multi-cloud, hybrid, or open-source-friendly architectures while still taking advantage of Elastic's advanced analytics.
• The separation of concerns between telemetry collection and backend storage, providing users more control over data flow.

Migration Strategies

If you’re looking to transition from Elastic APM to OpenTelemetry, here are a few recommended steps:

• Phased Migration: Start with services where Elastic’s native agents are less efficient or don’t support. Gradually add OpenTelemetry for those services to assess the setup.
• Dual Reporting: Enable both Elastic APM agents and OpenTelemetry instrumentation in critical services. Compare data and evaluate how well each system serves your needs.
• Backend Transition: If considering a complete shift to OpenTelemetry, set up a separate OpenTelemetry-compatible backend. Over time, redirect telemetry from Elastic to the new backend.

Alternative Approach: Using SigNoz

SigNoz is an open-source observability platform that offers full-stack monitoring, allowing teams to track application performance and troubleshoot issues in real time. It is designed to be a lightweight and easy-to-deploy solution for distributed systems, providing powerful insights into traces, metrics, and logs.

SigNoz provides a compelling open-source alternative that bridges the gap between OpenTelemetry's flexibility and Elastic APM's functionality, offering users full-stack observability through native OpenTelemetry support. Here’s a breakdown of how SigNoz can serve as an alternative:

• Open-Source and Self-Hosted: Unlike Elastic APM’s proprietary licensing, SigNoz is fully open-source, giving users control over data privacy, scalability, and customization.
• Native OpenTelemetry Compatibility: SigNoz natively supports OpenTelemetry for both tracing and metrics, making integration straightforward and eliminating the need for custom instrumentation or conversions.
• Full-Stack Observability: By combining traces, logs, and metrics in one interface, SigNoz provides insights into application performance across the stack, from infrastructure to application-level dependencies.

Key Benefits of SigNoz

Here are some of the benefits of using SigNoz for your observability needs:

• Flexibility with Data Storage: You can choose where to store your telemetry data—SigNoz supports both time-series and SQL databases, allowing for scalability and cost-effectiveness.
• Ease of Migration: Migrating to SigNoz is simplified by its support for OpenTelemetry standards, enabling users of OpenTelemetry or Elastic to transition smoothly.
• Complete Dashboarding and Alerting: Integrated dashboards and alert configurations enable custom views and proactive monitoring, which are essential for teams managing complex distributed systems.

Key Takeaways

• OpenTelemetry offers vendor independence and standardization. OpenTelemetry is an open-source framework that ensures flexibility by supporting multiple backends, allowing users to avoid vendor lock-in.
• Elastic APM includes powerful features like code profiling, which provides deeper insights into application performance.
• Both OpenTelemetry and Elastic APM support OTLP (OpenTelemetry Protocol), enabling hybrid observability setups where both tools can work together.
• When selecting an observability solution, it’s important to align with your organization's long-term monitoring and analysis needs, considering factors like scalability and integration options.

FAQs

Can I use OpenTelemetry with Elastic APM?

Yes, Elastic APM supports OTLP ingestion, allowing you to use OpenTelemetry instrumentation with Elastic's backend.

What are the main differences in data collection?

OpenTelemetry uses standardized collectors and exporters, while Elastic APM uses proprietary agents optimized for the Elastic Stack.

Which solution has better enterprise support?

Elastic APM provides dedicated enterprise support, while OpenTelemetry relies on community support and your chosen backend vendor.

How do implementation costs compare?

OpenTelemetry is free and open-source, but requires backend infrastructure. Elastic APM includes backend costs within Elastic Cloud or self-hosted deployments.