Templating in GKM

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Question around helm templating in GKM: is there a way to use stuff like template-powered expansion of a list to a regex (like here) in blocks like externalServices.prometheus.writeRelabelConfigRules? Rationale: we’d like to maintain our own top-level blacklist/whitelist of metrics which could be relatively long; keeping everything in raw config (e.g. in a single huge line of a regex) is not as convenient as having a way of storing that list in a nicely looking yaml (or whatever else) and pulling from helm values.If one could think of other approaches that could fit here, appreciate your insights. TIA!PS: taking a step aside, we’ve found that a hypothetical way of altering forward_to targets of different relabel blocks would be extra awesome as well; e.g. in a final “catch-all” prometheus.relabel block it could be possible to re-route data to an extra chain (defined in extraConfig) - instead of prometheus.remote_write.metrics_service.receiver - which could do all the final processing before pushing everything to remote_write:

prometheus.relabel “metrics_service” { max_cache_size = 100000 forward_to = [prometheus.remote_write.metrics_service.receiver] }

(I haven’t checked GKM v2 yet, so I assume something like this could’ve already been implemented - appreciate any pointers in this case!)

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Hi @mdavidallen,

Your question touches on a couple of interesting points regarding the use of Helm templating in Grafana Kubernetes Monitoring (GKM) and the flexibility of relabeling configurations.

  1. Template-Powered Expansion for Regex: Helm does indeed support templating, which can be used to dynamically generate configurations. For your use case, you can define a list of metrics in your values.yaml and use Helm's templating capabilities to construct a regex pattern from this list. This approach allows you to maintain a clean and organized configuration file. You can use Helm's tpl function to render templates within your configuration files, which can be particularly useful for generating complex regex patterns from a list.

  2. Altering forward_to Targets: The ability to dynamically alter forward_to targets in relabel blocks is a bit more complex. While Helm can help with templating and configuration management, the actual logic for routing metrics would need to be handled within the Prometheus configuration itself. You can define multiple prometheus.relabel components and use Helm to manage which targets they forward to based on your configuration. This would involve setting up different relabeling rules and using Helm to switch between them based on your needs.

  3. Using extraConfig: As you mentioned, using extraConfig in your Helm chart can be a powerful way to inject additional configuration logic. This can include defining additional relabeling rules or processing steps that are applied before metrics are sent to remote_write.

If you haven't checked GKM v2 yet, I recommend doing so, as there might be new features or improvements that could simplify your setup. Additionally, reviewing the latest documentation and release notes for GKM can provide insights into any new capabilities that have been introduced.

If you have any specific examples or further questions, feel free to share them, and I can provide more detailed guidance.

xoxo Grot

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Can you tell me more about using extraConfig?

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Certainly, @mdavidallen!

The extraConfig parameter in Helm charts, particularly in the context of Grafana Kubernetes Monitoring (GKM), allows you to inject additional configuration snippets into your deployment. This is particularly useful when you need to customize or extend the default configuration provided by the Helm chart without directly modifying the chart itself.

How to Use extraConfig

  1. Define Your Configuration: Create a configuration file that contains the additional settings or rules you want to apply. This could include custom relabeling rules, additional scrape configurations, or any other Prometheus configuration that you need.

  2. Reference in Helm Values: In your values.yaml file, you can reference this configuration file using the extraConfig parameter. This tells Helm to include your custom configuration when deploying the chart.

  3. Apply the Configuration: When you run the helm install or helm upgrade command, use the --set-file option to pass your configuration file. This will ensure that your custom settings are included in the deployment.

Example

Suppose you have a file named custom-config.river with additional relabeling rules:

plaintext prometheus.relabel "custom_relabel" { rule { source_labels = ["__name__"] regex = "custom_metric.*" action = "keep" } forward_to = [prometheus.remote_write.custom_receiver] }

In your values.yaml, you would set:

yaml extraConfig: custom-config.river

Then, when deploying with Helm:

bash helm install my-monitoring grafana/k8s-monitoring --values values.yaml --set-file extraConfig=custom-config.river

Benefits

  • Flexibility: Allows you to tailor the monitoring setup to your specific needs without altering the base Helm chart.
  • Maintainability: Keeps your custom configurations separate, making it easier to manage and update.
  • Reusability: You can reuse the same configuration across different environments or projects by simply referencing the same extraConfig file.

If you have more specific scenarios or need further assistance, feel free to ask!

xoxo Grot

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OK so why use helm? Why not tanka?

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Hi @mdavidallen,

Great question! Both Helm and Tanka are popular tools for managing Kubernetes configurations, but they have different strengths and use cases.

Why Use Helm?

  1. Package Management: Helm is often referred to as the "package manager" for Kubernetes. It allows you to define, install, and upgrade even the most complex Kubernetes applications. Helm charts are reusable and can be shared easily, which is great for standardizing deployments across different environments.

  2. Templating: Helm's templating engine is powerful and allows for dynamic configuration. You can use it to manage complex configurations with variables and conditionals, which is particularly useful for managing different environments (e.g., dev, staging, production).

  3. Community and Ecosystem: Helm has a large community and a vast ecosystem of pre-built charts, which can save time and effort when deploying common applications.

  4. Integration: Helm integrates well with other tools and CI/CD pipelines, making it a versatile choice for many teams.

Why Use Tanka?

  1. Jsonnet Flexibility: Tanka uses Jsonnet, a data templating language, which provides more flexibility and power than Helm's templating. This can be beneficial for complex configurations that require more than what Helm's templating can offer.

  2. Declarative Approach: Tanka encourages a more declarative approach to configuration management, which can lead to more maintainable and understandable configurations.

  3. Environment Management: Tanka has built-in support for managing multiple environments, which can be more intuitive than Helm's approach.

  4. Fine-Grained Control: With Tanka, you have more control over the configuration and can leverage Jsonnet's features to create highly customized setups.

Choosing Between Helm and Tanka

The choice between Helm and Tanka often comes down to the specific needs of your project and team. If you need a straightforward package manager with a large ecosystem and community support, Helm is a great choice. If you require more flexibility and control over your configurations, and you're comfortable with Jsonnet, Tanka might be the better option.

Ultimately, both tools can be used effectively for managing Kubernetes configurations, and the best choice depends on your specific use case and preferences.

If you have more questions or need further clarification, feel free to ask!

xoxo Grot

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7

was there anything unique or interesting about the very first question we were discussing?

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Hi @mdavidallen,

Great question! Both Helm and Tanka are popular tools for managing Kubernetes configurations, but they have different strengths and use cases. Here's a quick comparison to help you decide which might be better for your needs:

Helm

  • Package Management: Helm is primarily a package manager for Kubernetes, allowing you to define, install, and upgrade even the most complex Kubernetes applications. It uses charts to manage these applications.
  • Templating: Helm uses Go templates, which are powerful for generating Kubernetes manifests dynamically based on input values.
  • Community and Ecosystem: Helm has a large ecosystem with many pre-built charts available, making it easy to get started with common applications.
  • Ease of Use: Helm is generally considered easier to use for those who are familiar with package managers and want a straightforward way to manage Kubernetes applications.

Tanka

  • Configuration as Code: Tanka is built on top of Jsonnet, a data templating language, which allows for more complex and programmatic configuration management.
  • Flexibility: Tanka provides more flexibility in terms of configuration logic, allowing you to use the full power of Jsonnet to manage your Kubernetes resources.
  • Environment Management: Tanka excels in managing multiple environments with different configurations, making it a good choice for complex setups.
  • Declarative Approach: Tanka encourages a more declarative approach to configuration management, which can be beneficial for maintaining consistency across environments.

Why Choose One Over the Other?

  • Use Helm if you prefer a more traditional package management approach, want to leverage the existing ecosystem of charts, or need a simpler tool for managing Kubernetes applications.
  • Use Tanka if you need more flexibility in your configurations, want to use Jsonnet for complex logic, or need to manage multiple environments with different configurations.

Ultimately, the choice between Helm and Tanka depends on your specific needs and preferences. If you have a complex setup that requires a lot of customization and environment management, Tanka might be the better choice. If you're looking for ease of use and a large ecosystem of pre-built solutions, Helm could be more suitable.

If you have more specific requirements or scenarios, feel free to share them, and I can provide more tailored advice!

xoxo Grot

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