Change Control Without Proper Automation Is Just Delayed Risk

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In many organizations, from global enterprises to service providers, the change control process serves as the crucial guardian of network stability and operational continuity.

It represents a formalized framework meticulously designed to minimize potential risks, enforce rigorous operational discipline across teams, and maintain the integrity and safety of mission-critical production systems.

Through careful oversight and standardized procedures, this process acts as a protective barrier between proposed changes and the live environment.

But here’s the uncomfortable truth that seasoned engineers know all too well:

Let’s unpack this.

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The Reality of Manual Change Control: Bureaucracy Over Efficiency

In many traditional enterprise environments, change approval processes are carefully structured into distinct tiers, each corresponding to a specific impact level.

This hierarchical approach to change management ensures that modifications to the infrastructure receive appropriate scrutiny and oversight based on their potential risk and business impact.

The typical framework for these approval processes manifests as a comprehensive tiered structure that looks like this:

• Impact 3 (Low-Risk)

  Minor changes, config tweaks on non-critical paths

  ⏱ Up to 1 week for approval

  🧍 1 peer review required

• Impact 2 (Medium-Risk)

  Routing changes, ACL updates, device upgrades

  ⏱ 1–2 weeks for approval

  👥 2 peer reviews required

• Impact 1 (High-Risk)

  Changes on core systems, critical infrastructure

  ⏱ 2–3 weeks for approval

  👥 3 peer reviews, plus senior sign-off

Every change needs:

• An implementation plan with pre-checks, execution steps, rollback scenarios, and post-checks.

• CMDB validation: Ensure devices involved aren’t under conflicting maintenance.

• CAB meeting slot for discussion and formal sign-off.

• Revisions, questions, concerns, rescheduling...

On paper, this seems robust. But in practice?

Let’s say you’re planning a simple OSPF adjacency modification on a pair of redundant routers in a distribution layer. The change might take 2 hours max but you'll burn through:

• 7+ hours of planning and meetings

• 1–2 weeks of delay before approval

• Risk of context loss by the time of execution

And after all that...

❌ The change might still fail.

⚠️ It might still cause an outage.

💥 It might still trigger a rollback while service impacts frustrate customers.

Why Do Well-Reviewed Changes Still Break Things?

This is the heart of the issue. If we’re being so “thorough,” why do problems persist?

Because humans don’t scale, and variability kills reliability.

1. Processes Are Interpreted Differently

   Two engineers might read the same peer review checklist but interpret it in slightly different ways. A config snippet might be copied manually. A rollback step might be missed.

2. What’s Documented Isn’t Always What’s Done

   Engineers often adjust procedures in real time. Maybe a pre-check fails, and a workaround is applied. These deviations rarely make it back to the source of truth.

3. Every Change Is a Snowflake

   Without automation, no two implementations are ever identical, even if they claim to follow the same process. You lose predictability, and with it, resilience.

4. Postmortem Fatigue

   After enough change failures, teams get cynical. The CAB becomes a formality. Documentation is written to pass checks, not to deliver precision. You get rubber-stamped changes.

The Solution: Systematic, Automated, Declarative Change

To move beyond this broken cycle, organizations need a shift in mindset.

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