Introduction
A DBA’s honest story about production, pressure, and finally having guardrails
If you’ve worked as a DBA in production for a few years, you’ll eventually learn a quiet truth that nobody really prepares you for:
When things go wrong in the database, the DBA is always the last line of responsibility.
It doesn’t matter who asked for the change.
It doesn’t matter how urgent it was.
It doesn’t matter whether it came from a developer, a manager, or even leadership.
When production misbehaves, people don’t ask who requested the change.
They ask, “What happened to the database?”This blog is not about tools.
It’s about how CI/CD changed that reality for MySQL teams — technically, operationally, and just as importantly, professionally.
Why are DBAs Suddenly Dealing With GIT and Jenkins
For a long time, DBAs and CI/CD lived in different worlds.
Developers worked in Git. They had pull requests, approvals, commit history, and pipelines that clearly answered three questions:
- Who made the change?
- What exactly changed?
- When did it happen?
Databases didn’t have that luxury.
Most MySQL changes happened through chat messages, emails, or hallway conversations:
“Can you just add this index quickly?”
“We need to delete some bad data — it’s urgent.”
“This ALTER should be safe, right?”
And DBAs did what DBAs always do — they helped.
The problem wasn’t willingness.
The problem was lack of a system that recorded intent, ownership, and impact.
As systems grew and outages became more expensive, this informal model stopped scaling. The same change that once affected thousands of rows now affected hundreds of millions. The same mistake that once caused a brief slowdown now caused hours of degradation.That’s when CI/CD stopped being a “developer thing” and became a database survival tool.
Why MySQL Production Changes Are Risky (Even When You Know Better)
One of the most frustrating things about MySQL incidents is that they rarely look dramatic.
The server is up.
CPU is not pegged.
Disk is not full.
And yet, the application is crawling.
That’s because MySQL often fails politely.
An ALTER TABLE doesn’t throw an error if it can’t get a metadata lock. It waits. While it waits, new queries also wait. From the outside, it looks like slowness. From the inside, it’s a traffic jam.
Even “online” schema changes are not magic. They still read data, still write data, still generate binlogs, and still push work onto replicas. The cost is distributed over time, which makes it harder to notice — but not smaller.
Replication makes everything worse in subtle ways. The primary moves on quickly, giving a false sense of safety. Replicas absorb the cost later, quietly falling behind. By the time lag is visible, the application has already noticed inconsistent behavior.This is why MySQL production changes are risky by design, not by operator error.
Common MySQL Production Outage Triggers (The Ones We Pretend Are Rare)
If we’re being honest, most MySQL outages come from a short, familiar list.
Someone runs an ALTER TABLE on a large table during business hours.
Someone executes a DELETE without fully understanding how many rows it touches.
Someone adds an index under pressure to fix a slow query.
Replication lag builds slowly while writes continue uninterrupted.None of these actions are reckless. They’re often done with good intentions, under real pressure. The danger is not the action itself — it’s the lack of visibility and governance around it.
MySQL Changes: Without vs With CI/CD (Where Accountability Changes)
This is where CI/CD fundamentally changes the game — not just technically, but socially.
Without CI/CD
A request comes in. It’s urgent.
A DBA runs the change directly on production.
Days later, something breaks. Maybe replication lag spikes. Maybe a query plan changes. Maybe performance degrades slowly.
Now the questions start:
- “Who did this?”
- “Why was this change done?”
- “Was this approved?”
And the uncomfortable truth is:
there’s often no clear answer.
The change happened. The context is gone. The accountability collapses. And the DBA ends up carrying the blame — not because they were careless, but because the system had no memory.
With CI/CD
Every change goes through a proper channel.
There is a record of:
- Who initiated the change
- What exactly was changed
- When it was executed
- Who approved it
- What validations ran before execution
When someone asks questions later, the answers exist.
Not as explanations — as evidence.
This alone dramatically changes how DBAs experience production work.
CI/CD Architecture For MySQL(What Actually Matters)
A MySQL CI/CD pipeline is not about automation for its own sake. It’s about forcing clarity.
When schema and data changes live in version control, they stop being invisible. When pipelines enforce checks, they stop being optional. When approvals are required, responsibility becomes shared.
Instead of reacting to outages, teams start having conversations before changes happen:
“Is this safe on a table this size?”
“Can this wait until replicas are healthy?”
“Do we need an online migration here?”CI/CD doesn’t eliminate risk.
It moves risk into daylight.
CI/CD Tooling Map for MySQL (Why This Is Not About Jenkins)
It’s easy to get distracted by tools. Git, Jenkins, gh-ost, pt-osc, Online schema change utilities.
But tools are just containers. What matters is the behavior they enforce.
A good MySQL CI/CD pipeline behaves differently depending on context. A small lookup table is treated very differently from a 500-million-row transactional table. A change during off-peak hours is treated differently from one during peak traffic.This context-awareness is not intelligence built into tools.
It’s DBA experience encoded into rules.
Real Production Outage Scenarios
Scenario #1: ALTER TABLE & Metadata Locks (A Familiar Pain)
Let me describe a real production scenario.
An ALTER TABLE was requested to add a column. The table was large, but the change was assumed to be safe. The ALTER was started during moderate traffic.
Unbeknownst to anyone, a reporting query had been running for hours. The ALTER waited for a metadata lock. New queries queued behind it. Within minutes, connection pools filled up. The application became unresponsive.
Nothing crashed. Nothing failed loudly.
It just stopped working.
After implementing CI/CD, the same change was later blocked automatically. The pipeline detected table size and forced an online migration during a low-traffic window. The outage never happened again.
Scenario #2: Large DELETE / UPDATE (The Slow Burn)
In another case, a data cleanup was requested on an “emergency” basis. Millions of rows needed to be deleted. The DELETE ran in a single transaction.
Undo logs grew rapidly. Purge lagged. Reads slowed down. Replication fell behind. Performance degraded gradually over hours.
Rollback wasn’t an option — it would’ve taken even longer.
With CI/CD in place later, similar cleanup requests were forced to run in controlled batches. The system stayed responsive. The risk didn’t disappear — but it became manageable.
Scenario #3: Replication Lag (The Silent Problem)
Replication lag is dangerous because it rarely triggers panic early.
We’ve seen cases where a schema change looked perfectly fine on the primary. Hours later, read replicas were minutes behind. Users started seeing inconsistent data. The issue wasn’t immediately obvious.Once CI/CD started enforcing replication health checks and throttling, these situations became visible before users noticed. Sometimes the safest decision was simply to wait — and waiting saved hours of cleanup.
When CI/CD Is Bypassed (Because Reality Exists)
No system is perfect.
During real incidents, CI/CD will be bypassed. Someone will log into production. A fix will be applied directly. This is not failure — it’s reality.
What matters is what happens next.
With CI/CD, drift is detected. Changes are reconciled. History is restored. Order returns.
Without it, inconsistencies pile up silently, waiting to explode later.
Rollback Reality (Where Responsibility Gets Heavy)
Rollback is often spoken about casually, but MySQL rollback is anything but casual.
Some operations cannot be undone. Some rollbacks are slower and more disruptive than the original change. Some mistakes require restores and long recovery windows.CI/CD doesn’t promise easy rollback.
It promises better decisions before rollback becomes necessary.
Limitations of CI/CD for MySQL (And Why That’s Healthy)
CI/CD significantly reduces operational risk, but it does not eliminate all challenges associated with MySQL production changes. It cannot compensate for
- poor schema design
- unbounded data growth
- fundamentally unsafe queries
Large tables, legacy schemas, and tight coupling between application logic and database structure still require careful planning beyond automation. Additionally, CI/CD pipelines rely on the quality of the rules encoded within them. Incorrect assumptions, incomplete validations, or missing operational context can lead to false confidence.
Human review, capacity planning, and experienced DBA oversight remain essential to handle edge cases that automation alone cannot anticipate.
CI/CD cannot replace judgment. It cannot understand business urgency. It cannot feel pressure.
But it can slow us down just enough to think — and sometimes that pause is the difference between a controlled change and a production incident.
Precautions When Implementing CI/CD for MySQL
CI/CD must be designed to protect production, not impress leadership. Safety gates must be mandatory. Rules must evolve. Humans must remain in the loop.
If CI/CD feels boring, it’s probably doing its job.
Key MySQL-Specific Takeaways
If you’ve read this far, you already understand the core message: MySQL outages are rarely random. They’re almost always the result of uncontrolled change. CI/CD doesn’t eliminate risk, but it creates memory, accountability, and shared responsibility.
And for DBAs, that changes everything.
Conclusion
DBAs didn’t ask to become experts in Git or Jenkins.
Production demanded it.
CI/CD, when applied thoughtfully to MySQL, doesn’t just protect the database — it protects the people responsible for it.
And that’s something most of us didn’t realize we needed until we finally had it.
“This blog is based on a recent technical webinar conducted by GenexDBS, where we shared real MySQL production experiences and how CI/CD helped us move from firefighting to controlled change management.“