When a major incident hits a critical application, a flow of processes are triggered, from Incident and Crisis Management through to the dusting off of the IT Disaster Recovery (ITDR) fail-over procedures.

Modern ITDR has evolved massively, with automation, cloud-native resiliency patterns and orchestration now reducing much of the complexity. However, many organizations still depend on more manual driven process to run their ITDR fail-over plans which can introduce hesitation when time matters most. Even when you have runbooks written, data replicated, and a secondary data center ready and waiting to absorb the workload, many teams still hesitate when the moment comes to pull the trigger on a fail-over.

Why does this happen? And why, despite having detailed Business Continuity Plans (BCP) and DR procedures in place do organizations pause at the very moment when swift action limits impact?

So What Are These Blockers?

Below I’ve listed some of the common reasons teams hesitate to initiate a fail-over. It isn’t a comprehensive list, but hopefully one where you may have seen the same scenarios play out.

The risk of manual error and human factors under pressure

Fail-over isn’t just pulling a lever or pushing a button to get everything running in DR, it is often a coordinated operational event involving many teams, steps, and dependencies. When the proverbial poo hits the fan, even the most confident engineers worry about making a mistake (who wouldn’t) that could make the situation worse. This fear alone can delay action by minutes or hours.

This hesitation is amplified when runbook steps are manual, teams aren’t aligned and there is uncertainty on what “good” looks like in DR.

Skills scarcity and the “bus factor”

In some organizations, knowing how to fail-over for a specific application is concentrated to just one or two people. If those individuals aren’t around, due to holiday, illness, or by being pulled into multiple incidents, teams may hesitate to fail-over without that person in the room. Over reliance on single points of failure can create resilience fragility.

Lack of up-to-date runbooks or ITDR plans

Even when a fail-over plan exists, it may not reflect the current architecture, integrations, or cloud services in use. They can get out-of-date quickly, and especially if they are only reviewed on a regular basis. If you can’t trust the documentation in front of you, then you’ll naturally hesitate. A stale runbook introduces more problems and causes further delays.

This is really a governance failure, not a documentation one.

Unclear or undocumented system dependencies

Many organizations will struggle here. An application will rarely run on its own without other dependencies. APIs, databases, authentication services. Missing one dependency can turn a quick recovery into a cascading failure. If teams aren’t confident they know the full dependency map, then hesitation again creeps in.  Understanding system dependencies can be a time consuming practice, but it is a worthwhile exercise to not only understand at a system level, but a wider business service level.

This isn’t just a technical task, understanding dependencies at the business service level is a core requirement of Operational Resilience, not just ITDR. When teams don’t understand the full chain, hesitation will undoubtedly creep in.

Dependencies need to be understood at both the system level, and the business service level.

Disappearing down the investigatory rabbit hole

Engineers are natural problem solvers. When an incident occurs, the first and right instinct is to diagnose, troubleshoot, and fix the root cause as quickly as possible. But how long do you spend on this path before you take a step back and think of the bigger picture.

Absolutely investigate and diagnose, but don’t spend too long dwelling on “I’ll just check this out, and this, and this….”. Before you know it, the fail-over option may have become a little riskier.
Without clear decision triggers, root cause analysis can become a trap.

Fear of the unknown

Failing over is often viewed as a “last resort” because of the amount of work and people involved in the process. If fail-over hasn’t been regularly tested, it becomes a leap into the unknown, and the unknown is scary (for me at least). Teams will worry about data consistency, configuration drift, or issues that may appear down the road once the system is in DR.

And in many cases, hesitation isn’t just about fail-over, it’s uncertainty around fail-back. If returning to the primary environment is less rehearsed or documented, that uncertainty can add another layer of hesitation.

Leadership Uncertainty

Not all hesitation comes from technical teams. Sometimes the pause comes from leadership uncertainty either with unclear ownership of the fail-over decision, concerns about customer impact, or lack of clarity around when the business wants the fail-over trigger pulled.

Even a few minutes of indecision at the top can slow technical teams who are ready to act.

How Do We Overcome These Blockers?

Reluctance to fail over isn’t a technical weakness, it’s often a symptom of underlying operational, cultural, and documentation gaps. The good news is that each blocker can be addressed with the right practices, governance, and mindset.

1. Turn runbooks into living, breathing documents

Updating them before or during an annual test creates dangerous assurance gaps. Runbook reviews should be built into the change management process, as well as architecture reviews and even deployments. This should keep them live and updated meaning they’ll be current and trusted.

Runbooks should evolve along with the environment it supports.

2. Practice fail-overs regularly

I like the saying “Confidence is built through repetition”. Even partial or non-production fail-overs build muscle memory, help reduce fear, and increase decisiveness during real incidents. Practice really does make (semi) perfect.

That’s not to say all DR tests need to be full-scale, but repetition in any scale of test reduces hesitation and normalises the process.

3. Reduce manual steps -automate where possible

Automation helps in a lot of ways, from reducing the amount of over complicated steps in a runbook, to removing hesitation. From automating database fail-overs to CNAME changes you’ll have a fail-over that will lead to more predictable outcomes.

BUT, automation only works when the scripts are maintained and tested. Governance around your automation processes is critical.

4. Broaden knowledge and reduce reliance on “the expert”

Cross-training, shadowing, and rotating DR responsibilities give multiple people input in the fail-over process. Avoid any single points of failure, including human.

5. Map and validate dependencies frequently

Use service mapping, CMDB tools, BIA reviews and real-world testing to understand what connects to what. Clearer understanding = faster decision-making.

6. Establish triggers for switching from troubleshooting to recovery

To avoid the investigatory rabbit hole, define thresholds for when troubleshooting ends, and fail-over begins. No progress after X minutes, potential SLA breach predicted or customers impact being escalated are all triggers that can help remove the “lets try one more thing” mindset.

7. Treat fail-over as a business decision, not just a technical one

When leadership understands recovery paths and consequences, decisions happen faster. Fail-over should be strategic, not a gamble.

Why Embracing Fail-over Improves Resilience

Move away from treating fail-over as a last resort and be more on the front foot. It shouldn’t be treated as something to fear but embrace. Having robust and regularly tested processes in place will ease the fear.

A clear understanding of recovery options means leadership can make clearer and faster decisions, reducing impact times.  Regular testing reveals gaps in documentation, dependencies and configurations. Repetition will reduce the fear. A more efficient, quicker, smoother fail-over becomes a competitive advantage, not a risk.

Closing Thoughts

Fail-over is often seen as a last resort, but confidence in fail-over comes from preparation, practice, as well as culture. When teams start to normalize fail-over, they can stop fearing it.

When they test regularly, they stop hesitating.

And when an organization sees fail-over as a strategic tool and not a risk, recovery becomes faster, smoother and far better equipped to protect its most critical services.

Resilience isn’t built in the middle of an incident or crisis, it’s built way before.  Every test strengthens capability.  Every lesson increases confidence.  And every successful fail-over brings an organization one step closer to true operational resilience.

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This article was originally published on LinkedIn and is republished with permission.