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# Building tools to manage cross-cutting concerns in Kubernetes

**[ITNEXT](https://daily.dev/sources/itnext)** · 8 min read · 1 upvotes · 0 comments

## Summary

A suite of Kubernetes workload management tools built on ConfigHub demonstrates the 'configuration as data' approach to handling cross-cutting concerns. Four tools are introduced: workload-manager (best practices enforcement), scheduling-manager (node selectors/affinity/tolerations), observability-manager (Prometheus ServiceMonitor and OpenTelemetry sidecar), and autoscale-manager (HPA/KEDA). Unlike configuration-as-code approaches requiring template edits and re-rendering, these tools operate directly on materialized configuration stored in a database, enabling composable and interoperable automation. Tools run in dry-run mode by default for agent-friendliness, support guardrails via triggers, and can analyze, generate, validate, and enforce desired postures across multiple clusters without cloning git repos or creating PRs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://itnext.io/building-tools-to-manage-cross-cutting-concerns-in-kubernetes-by-using-confighub-6bd64afcdd69>

## Questions this post answers

### What is the difference between configuration as code and configuration as data in Kubernetes tooling?

Configuration as data stores fully materialized Kubernetes configuration in a database so tools can read and mutate it directly via APIs, while configuration as code requires cloning repos, rendering templates (helm, cdk8s, tanka), running policy checks, committing fixes, and re-rendering for every affected environment. ConfigHub uses the data model, letting tools like workload-manager or autoscale-manager change configuration directly without repo cloning or pull requests.

_Developers weighing config-as-code versus config-as-data workflows can find deeper Kubernetes tooling discussion on daily.dev._

### How do I create a PodDisruptionBudget for a Kubernetes workload without writing YAML by hand?

A tool like cub-workload can generate one automatically: running 'ensure-pdb appchat-prod/frontend --max-unavailable "10%"' produces a dry-run PodDisruptionBudget matching the workload's namespace and labels, similar to how kubectl expose infers settings, making it simpler than kubectl create pdb. The change is only committed and applied to clusters after explicit approval.

_Anyone automating PDBs and other Kubernetes hardening steps can track more workflow patterns like this on daily.dev._

### Should I use HPA or KEDA for Kubernetes autoscaling?

Both are viable, and tooling exists to convert between them: the autoscale-manager tool checks and edits HorizontalPodAutoscaler and KEDA ScaledObject resources and can convert an existing HPA configuration to KEDA. The choice often depends on whether autoscaling needs to react to external event sources, which KEDA supports beyond HPA's built-in metrics.

_Teams deciding between HPA and KEDA for scaling policy can follow related Kubernetes autoscaling coverage on daily.dev._

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---

Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#iac](https://daily.dev/tags/iac)

[View this post on daily.dev](https://daily.dev/posts/building-tools-to-manage-cross-cutting-concerns-in-kubernetes-ksy5gqspn)

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