Let’s talk about a recent success story I had with one of my clients. This company brought me in to fix a major development-process mess (through no fault of their own—they’d hired dev agencies that promised a lot and delivered very little). In just three months, we turned the organization’s performance around, and the results spoke for themselves through the lens of DORA metrics.
But before we dive into the transformation, a quick disclaimer: DORA metrics should never be taken in isolation. They’re an awesome way to measure certain aspects of performance—like deployment frequency, lead time, time to restore, and change failure rate—but they don’t tell the whole story. You have to pair them with broader engineering maturity models and real-world business goals to get the complete picture.
What Are DORA Metrics?
DORA (DevOps Research and Assessment) metrics look at four main things:
1. Deployment Frequency (DF): How often you deploy code changes.
2. Lead Time for Changes (LT): The time it takes from a developer committing code until that code runs in production.
3. Time to Restore Service (TTR): How quickly you can fix production issues once they’re discovered.
4. Change Failure Rate (CFR): How often a deployment causes a problem that requires a quick fix or rollback.
These four numbers give you a quick snapshot: fast, stable, and reliable teams generally score better. But remember: it’s only a snapshot.
The Starting Point: Low Performance
When I stepped into this client’s organization, they scored poorly by every DORA metric. Why? The dev agencies they had relied on were, let’s just say, telling tall tales. The process was slow, the code was unreliable, and any deployment felt like walking on eggshells.
The Goal
The mission was simple: Become an “Elite” performer by DORA standards while also building a robust, self-sustaining engineering culture.
The Fix in Three Months
1. Deployment Frequency: Multiple Times a Day
The first big improvement was continuous integration and continuous delivery (CI/CD). Essentially, the code is automatically tested and deployed every time new changes are pushed.
But the real kicker was automated core functionality testing—automated tests that simulate the entire ecosystem using Docker Compose. With these comprehensive tests, the team felt confident enough to deploy whenever needed—multiple times a day, if the business required it.
2. Lead Time for Changes: Cut Down by Confidence
Shortening the lead time required both technology and a shift in mindset:
• Automated testing meant people didn’t have to worry about accidentally breaking something unseen.
• Smaller-scope tickets meant no more enormous, month-long projects. Bite-sized tasks got built, tested, and released faster.
By tackling smaller pieces of work, we reduced the time from “idea” to “code in production” significantly.
3. Time to Restore Service: Under an Hour (Most of the Time)
Mistakes happen. Bugs slip through. The question is, how fast do you fix them? We introduced exception tracking—a system that actively alerts developers when something goes wrong, linking the error to the specific commit or release.
1. A developer (or the whole team) sees an alert in Slack.
2. They click on it, see exactly which piece of code is causing the problem, and fix it.
3. They deploy the fix—often within an hour.
If the issue is really critical or can’t be fixed immediately, we have a fallback: roll back to a previous version. Each version is tagged with a unique commit “fingerprint,” making rollbacks basically a click away.
4. Change Failure Rate: Testing + Team Ownership
We minimized deployment failures with two main strategies:
• Automated tests that caught issues before they went live.
• Team ownership so every dev felt responsible for the quality of their code.
We also reinforced the idea that failure isn’t something to hide—if something breaks, it’s a chance to learn and make sure it doesn’t happen again.
Why an FCTO (Fractional CTO) Model Works
You might be wondering how we pulled off this transformation in three short months. The secret is: the team does the work. My role is to guide them with strategy, coach them on best practices, and empower them to succeed long after I’m gone. Here’s the play-by-play:
1. Assess: Figure out what’s really going on—processes, tech stack, team capabilities, business needs.
2. Plan: Lay out a step-by-step strategy that ties DORA metrics and other maturity models to real-world goals.
3. Execute: Train the team on new tools, processes, and techniques.
4. Empower: Let the team lead, while I provide support and course-correction as needed.
With the right approach, even a “lost cause” organization can make a massive turnaround in performance and reliability in just a few months.
Wrapping Up
If your organization is wrestling with poor performance or painfully slow deployment times, there’s a path to becoming an elite performer—and it doesn’t have to take years. With the right strategy and guidance, a major transformation is absolutely within reach.
That’s one of the many positive impacts an FCTO can have on your organization. If you’d like to see these kinds of results, let’s chat!
Glossary (Layman’s Terms)
• DevOps Research and Assessment (DORA):
A research group that identified four key metrics (deployment frequency, lead time, time to restore, change failure rate) to gauge the health and speed of software development teams.
• Deployment Frequency (DF):
How many times your team pushes changes to the live product within a certain period (daily, weekly, etc.). Higher frequency usually means your team can deliver features and fixes quickly.
• Lead Time for Changes (LT):
The time it takes from writing code to having it live in the product. The shorter the better—less waiting around and faster user feedback.
• Time to Restore Service (TTR):
How fast you can fix an issue once it’s identified. Think “broken production” to “back online.” Shorter times indicate good responsiveness and strong processes.
• Change Failure Rate (CFR):
The percentage of changes that cause a problem (like bugs or downtime) that needs immediate action. A low rate means your team rarely introduces serious issues.
• CI/CD (Continuous Integration/Continuous Delivery):
Automated processes for building, testing, and deploying software whenever new code is added. Makes deployments more frequent and less risky.
• Automated Testing:
A way for the computer to run tests on your code automatically. It ensures that new changes don’t break anything that was already working.
• Docker Compose:
A tool that allows you to spin up multiple, connected software services on your local machine (or in a testing environment) so you can test how they work together before going live.
• Commit:
When a developer finalizes changes to their code, effectively “saving” that version in a system that tracks all past versions (like Git).
• Exception Tracking:
A service that actively monitors your software in real time for errors and alerts you exactly where and why something failed (instead of you having to dig through endless logs after the fact).
• Slack:
A popular messaging app used by many teams for instant communication, including alerts from tools like exception tracking.
• Rollback:
Reverting to a previous version of the software if a new update breaks something major and can’t be fixed right away.
• Commit SHA:
A unique “fingerprint” for each version of the code, allowing you to see exactly what changed, when, and by whom—and to revert to that version if needed.
• FCTO (Fractional CTO):
A Chief Technology Officer (CTO) you hire part-time. They guide strategy, processes, and best practices without being a full-time employee.
If you have any questions or would like to explore how a fractional CTO can help your team, feel free to reach out!
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