Add Support For Label Based Discovery On Other Kubernetes Objects
Understanding the Current Limitations
At present, label-based discovery is only supported for pods within Kubernetes. This means that while developers can leverage this feature to instrument their pods, they are unable to do the same for other Kubernetes objects. To address this limitation, we propose extending label-based discovery support beyond pods to other Kubernetes objects.
The Importance of Label-Based Discovery
Label-based discovery plays a crucial role in enabling efficient DevOps workflows for instrumentation. By deploying Beyla with a specific option to instrument services bearing a certain label, developers can streamline their instrumentation processes. Initially, the daemonset remains dormant, waiting for the customer to redeploy their services with the required labels for instrumentation. This approach offers several benefits, including:
- Efficient Instrumentation: Label-based discovery enables developers to instrument their services efficiently, without requiring manual intervention.
- Flexibility: By using labels, developers can easily identify and instrument specific services, without affecting other services in the cluster.
- Scalability: As the number of services grows, label-based discovery helps maintain a scalable and manageable instrumentation process.
Extending Label-Based Discovery Support
To extend label-based discovery support beyond pods, we need to consider the following:
- Identifying Supported Objects: Determine which Kubernetes objects will be supported for label-based discovery. This may include deployments, stateful sets, daemon sets, and other objects.
- Implementing Label-Based Discovery: Develop a mechanism to discover and instrument supported objects based on their labels. This may involve creating a custom controller or modifying existing controllers to support label-based discovery.
- Integrating with the Beyla Helm Chart: Ensure that the Beyla helm chart is updated to support label-based discovery for the newly supported objects.
Benefits of Extended Label-Based Discovery Support
By extending label-based discovery support beyond pods, we can:
- Enhance Instrumentation Efficiency: Developers can instrument their services more efficiently, without requiring manual intervention.
- Improve Flexibility: Developers can easily identify and instrument specific services, without affecting other services in the cluster.
- Increase Scalability: As the number of services grows, label-based discovery helps maintain a scalable and manageable instrumentation process.
Implementation Roadmap
To implement extended label-based discovery support, we propose the following roadmap:
- Research and Planning: Conduct research to identify the supported objects and develop a plan for implementing label-based discovery.
- Development: Develop the custom controller or modify existing controllers to support label-based discovery.
- Testing: Thoroughly test the implementation to ensure it works as expected.
- Integration with the Beyla Helm Chart: Update the Beyla helm chart to support label-based discovery for the newly supported objects.
- Deployment: Deploy the updated Beyla helm chart to production.
Conclusion
Extending label-based discovery support beyond pods is crucial for enabling efficient DevOps workflows for instrumentation. By implementing this feature, developers can instrument their services more efficiently, without requiring manual intervention. We propose a roadmap for implementing extended label-based discovery support, which includes research and planning, development, testing, integration with the Beyla helm chart, and deployment. By following this roadmap, we can enhance instrumentation efficiency, improve flexibility, and increase scalability for developers.
Q: What is label-based discovery, and why is it important?
A: Label-based discovery is a feature that allows developers to instrument their services based on specific labels. This feature is important because it enables efficient DevOps workflows for instrumentation, allowing developers to streamline their instrumentation processes and improve scalability.
Q: What are the current limitations of label-based discovery in Kubernetes?
A: Currently, label-based discovery is only supported for pods within Kubernetes. This means that developers can leverage this feature to instrument their pods, but they are unable to do the same for other Kubernetes objects.
Q: What are the benefits of extending label-based discovery support beyond pods?
A: Extending label-based discovery support beyond pods offers several benefits, including:
- Efficient Instrumentation: Developers can instrument their services more efficiently, without requiring manual intervention.
- Flexibility: Developers can easily identify and instrument specific services, without affecting other services in the cluster.
- Scalability: As the number of services grows, label-based discovery helps maintain a scalable and manageable instrumentation process.
Q: Which Kubernetes objects will be supported for label-based discovery?
A: We propose supporting the following Kubernetes objects for label-based discovery:
- Deployments: Developers can instrument deployments based on specific labels.
- Stateful Sets: Developers can instrument stateful sets based on specific labels.
- Daemon Sets: Developers can instrument daemon sets based on specific labels.
- Other Objects: We will consider supporting other Kubernetes objects based on customer feedback and requirements.
Q: How will label-based discovery be implemented?
A: We will implement label-based discovery using a custom controller or by modifying existing controllers to support label-based discovery. The implementation will be designed to be scalable and efficient, allowing developers to instrument their services quickly and easily.
Q: How will the Beyla helm chart be updated to support label-based discovery?
A: We will update the Beyla helm chart to support label-based discovery by adding new configuration options and modifying existing configuration options to work with the new label-based discovery feature.
Q: What is the expected timeline for implementing extended label-based discovery support?
A: We propose the following timeline for implementing extended label-based discovery support:
- Research and Planning: 2 weeks
- Development: 6 weeks
- Testing: 4 weeks
- Integration with the Beyla Helm Chart: 2 weeks
- Deployment: 2 weeks
Q: What are the next steps for implementing extended label-based discovery support?
A: The next steps for implementing extended label-based discovery support are:
- Research and Planning: Conduct research to identify the supported objects and develop a plan for implementing label-based discovery.
- Development: Develop the custom controller or modify existing controllers to support label-based discovery.
- Testing: Thoroughly test the implementation to ensure it works as expected.
- Integration with the Beyla Helm Chart: Update the Beyla helm chart to support label-based discovery for the newly supported objects.
- Deployment: Deploy the updated Beyla helm chart to production.
Q: How can customers provide feedback and suggestions for implementing extended label-based discovery support?
A: Customers can provide feedback and suggestions by contacting our support team or by submitting a feature request through our issue tracker. We value customer feedback and will consider it when implementing extended label-based discovery support.