google.cloud/extensions/audit
2025-07-22 16:18:19 -06:00
..
README.md Adding audit extension doc 2025-07-22 16:18:19 -06:00
taxonomy.jq Indirect node counting taxonomy query file 2025-07-22 16:18:19 -06:00

Indirect Node Counts in Ansible Collections

Overview

In the context of Ansible automation, indirect node counts refer to the practice of calculating or verifying the capacity or availability of computing nodes through external systems or controllers, rather than directly querying the nodes themselves. This approach is especially useful in complex, public cloud, or on prem environments .

This file explains:

  • What indirect node counts are
  • Why they are required
  • What they enable
  • Their value

What Are Indirect Node Counts?

Rather than connecting directly to each node to assess its state of automation(e.g., Service, DB, VM, etc), indirect node counts leverage tools like ** APIs**, or other management layers to obtain usage information.

In an Ansible role or collection, this might involve:

  • Querying a cloud service for the list of DBs or VMs and their status of if they are being automated

Why Are They Required?

Directly connecting to every node:

  • Is inefficient in large-scale environments
  • May be prohibited due to security, network segmentation, or policy
  • Doesn't scale across multiple clusters or providers
  • Often leads to incomplete or stale data

Using indirect node counts via cluster managers:

  • Enables centralized insight into resource usage
  • Works well in managed or disconnected environments
  • Allows non-invasive assessment (e.g., read-only API access)

What Does It Do?

In practical terms, using indirect node counts in an Ansible collection:

  • Enables guardrails to verify into knowing what you are automating
  • Reduces operational risk and improves predictability of automation workflows

Why This Is a Good Practice

Benefit Description
Scalable Works across many clusters and environments
Secure Limits direct access to sensitive nodes
Efficient Avoids per-node polling, uses cached or aggregated data
Integrated Leverages our existing Certified and Validated collections
Reliable Provides consistent data source for automation decisions