Boost Camunda Connectors: Utilize Native Metrics Recorder

Hey folks! Let's dive into a cool feature that's all about making life easier for Camunda connectors developers. We're talking about leveraging the native metrics recorder within the Camunda client itself, instead of having to build your own. This is a game-changer because it gives you a more consistent and streamlined way to track performance and get insights into your connectors. Let's break it down, shall we?

The Core Idea: Simplifying Connector Metrics

So, the main aim here is to help connectors developers tap into the built-in Camunda client metrics instead of creating separate metrics recorders. Think of it like this: your connector is a vital part of the Camunda ecosystem, and it needs to tell you how it's doing. Currently, the connectors are using their own custom metrics. This works, but it's not the most efficient or unified approach. Imagine a world where all your metrics are flowing through a single, well-defined channel. That's the promise of using the native metrics recorder.

This shift streamlines your development workflow, as you no longer need to maintain separate metrics implementations. It aligns with Camunda's best practices, allowing you to benefit from the platform's standardized approach to metric collection and monitoring. This includes features like consistent naming conventions, data aggregation, and integration with monitoring tools. Ultimately, this approach simplifies your connectors, giving you better insight without the added overhead. Pretty neat, right?

Understanding the Existing Landscape

To make this happen, we need to understand the current situation. We have to look at how metrics are currently handled in a standard job worker invocation within the plain Java client. Then, we explore how the Spring Boot Starter extends this functionality. Finally, we'll examine how connectors currently implement their own metrics. This knowledge is crucial for creating a smooth transition to the native metrics recorder. Let's delve into the code to grasp how these components interact and identify areas for improvement. This includes investigating the architecture and understanding its implications for integrating the native metrics recorder.

Specifically, we want to know what metrics a default job worker writes when it's running in the plain Java client. Also, we'll explore how the Spring Boot Starter builds on top of this. And finally, how the connectors currently extend and implement this.

Current Connector Metrics Implementation

The current implementation is located here: https://github.com/camunda/connectors/blob/main/connector-runtime/connector-runtime-spring/src/main/java/io/camunda/connector/runtime/metrics/ConnectorsOutboundMetrics.java. This shows how connectors are presently tracking metrics. It is essential to examine this implementation to understand the metrics being recorded, how they are recorded, and how to map them to the native Camunda client's recorder. Analyzing the existing system gives us a benchmark to help improve and integrate our approach.

Camunda Client Metrics Implementation

The Camunda client's metrics recorder is located here: https://github.com/camunda/camunda/blob/main/clients/camunda-spring-boot-starter/src/main/java/io/camunda/client/metrics/MetricsRecorder.java. This is the target for our integration. Understanding its capabilities and how it's used within the Spring Boot Starter is important. This is because the Spring Boot Starter offers a pre-built integration to the Camunda platform. The key here is to determine how to reuse and customize the metrics already being collected.

Design: A Layer of Abstraction for a Unified Approach

Ideally, we want to avoid concurrent implementations and create a layer of abstraction. This approach makes it easier to manage and update metrics in the future. By introducing a layer of abstraction, we prevent having multiple, possibly conflicting, implementations. Instead, all metrics will flow through a single, well-defined channel, improving consistency and making it easier to integrate with monitoring tools.

This abstraction layer will provide a consistent interface for recording metrics, ensuring that all connectors use the same mechanism. This can encompass methods for recording various metrics, such as execution time, error rates, and the number of processed messages. This also lets us change the underlying implementation without breaking the connectors. The flexibility provides benefits for everyone, enhancing the monitoring capabilities of the entire Camunda ecosystem.

Technical Requirements & Implementation Details

Note: While the original document doesn't explicitly state the technical requirements, we can extrapolate some essential needs based on the user story and the design goals.

• Integration with Existing Metrics: The new metrics recorder must seamlessly integrate with the existing Camunda client's metrics infrastructure. This includes compatibility with existing monitoring tools and dashboards. This also includes providing support for the different types of metrics that are important for connectors (e.g., execution time, error rates, and message counts).
• Abstraction Layer: There must be an abstraction layer for recording metrics. This layer provides a consistent interface for recording various metrics. The interface should have clear and concise methods. This abstraction layer should also handle any specific needs related to connector-specific metrics.
• Performance: Performance is important; the new implementation should not introduce any noticeable overhead. This is particularly important for high-volume connectors. Performance tests should be done, and metrics should be monitored to make sure that the performance requirements are met.
• Configuration: It should be easy to configure the metrics recorder. This includes the ability to enable or disable metric collection, configure the types of metrics being recorded, and customize the reporting frequency. This flexibility is key for adapting to different environments and use cases. These settings should be easily configurable via properties or environment variables.
• Documentation: Comprehensive documentation is important. It should include usage examples, configuration details, and explanations of the available metrics. The documentation should be clear and concise, with examples. This will allow developers to understand and quickly implement the new metrics recorder.

Moving Forward: QA, Testing, and Release

Dev -> QA Handover

The following is a list of items for the handover to Quality Assurance (QA):

• Resources: Link to the relevant code repositories (Camunda Client, Connectors, etc.) and any necessary documentation. The team must provide clear documentation and access to these items.
• Versions to Validate: Specify the versions of the Camunda Client, Spring Boot Starter, and Connectors to be used for testing. These versions must be explicitly stated to ensure consistent test results. This is required because different versions may have varying functionalities and behavior. Specifying versions assures compatibility across the board.
• Release Version: Indicate the version in which this feature will be released. This will assist the QA team to determine when they need to start testing, and to ensure that the release is appropriately coordinated.

QA Test Cases (Example)

Note: While the original document doesn't provide specific QA test cases, here's a basic example. The QA team can build on this.

• Unit Tests: Create unit tests to verify that the metrics recorder functions correctly. Unit tests will include validating that metrics are recorded when expected. Unit tests should also cover edge cases, such as handling errors.
• Integration Tests: Integration tests should verify the integration between the connectors and the metrics recorder. The tests will include sending various types of messages to connectors. Also, the tests must confirm that the correct metrics are collected.
• Performance Tests: Run performance tests to verify that the new implementation doesn't affect performance. These tests should measure the overhead of the metrics recording. In addition, the tests should compare performance metrics before and after the change.
• Functional Tests: Test the end-to-end functionality of the metrics recording. Include testing that ensures the metrics can be viewed. The team must also confirm that these metrics are correctly displayed in the monitoring dashboards.

Release and Beyond

Once the feature is tested and validated, the release process can begin. After the release, it's vital to monitor the metrics and collect feedback from developers. This will help with optimization, and any necessary improvements can be planned. The team will want to make future improvements based on user feedback. The metrics recorder can then be updated to meet evolving requirements.

Conclusion: A More Robust and Unified Camunda

So, by embracing the native metrics recorder in the Camunda client, we're taking a big step towards a more unified, efficient, and user-friendly experience for connector developers. It streamlines metric collection, enhances monitoring, and fosters consistency across the platform. This is a win-win for everyone involved in the Camunda ecosystem. The integration of the native metrics recorder enables better insights into connector performance. It also boosts the ease of troubleshooting and the overall health of the workflow applications.

As we continue to develop and refine this feature, remember that the goal is always to make Camunda better, simpler, and more powerful for all its users. So, let's keep the ideas flowing, the code clean, and the connectors humming! Cheers!