The hidden cost of “almost automated” deployments
There’s nothing quite as frustrating as hearing “We’re almost there” when it comes to DevOps automation.
For most enterprises using PEGA, especially in complex, regulated environments like telecom, “almost automated” really means:
- Partial scripts that break mid-way.
- Teams are stuck doing sunrise and sunset checks manually.
- Rollbacks that aren’t rollbacks at all (just a rushed “fix forward” scramble).
- A deployment process so fragile it feels like defusing a bomb with oven mitts.
our client was no different. Their PEGA AOM and VADR systems had become a labyrinth of partial automations, manual file drops, and endless approvals.
When 14+ engineers are stuck pushing buttons, no one’s innovating
Let’s put some numbers on it.
At one point, our client had 17 separate pipelines in its PEGA deployment chain: 12 for AOM and 5 for VADR. But only PEGA artefacts were automated; SQL scripts and CSV files still needed manual intervention.
14+ people were directly involved every time they pushed an update. That meant:
- Long hours on calls coordinating manual steps.
- Higher chance of human error.
- Slow response to production issues.
- Engineers who should be building value are stuck babysitting deployments.
They needed a system that didn’t just look good in a slide deck but actually worked reliably in the real world.
Phase 1: Proving the concept (but still chained to manual tasks)
The first push was to introduce PEGA Deployment Manager (PDM).
Code deployment? Automated.
Configuration files and database updates? Still manual.
This partial fix did reduce some of the friction, but didn’t break free from the core problem: too many manual dependencies.
It was like adding an electric starter to a car that still had flat tires. Better, but not good enough to win any races.
Phase 2: The real leap , End-to-end Azure DevOps automation
Our client knew they had to go further.
Phase 2 wasn’t about tinkering; it was about rethinking deployments from the ground up:
- Code and package deployments are now fully handled by Azure DevOps pipelines, integrated tightly with PEGA’s PRPCServiceUtils.
- CSV and file deployments? Automated. Files pushed from SharePoint to S3 are picked up and deployed instantly, with no human in the loop.
- SQL and database scripts? Automated and version-controlled. No more manual approvals at midnight or rushed fixes.
- Rollbacks? Properly integrated, tested, and reliable.
Even restarts and sanity checks have been moved to automated pipelines. Python scripts run server restarts and log cleanups seamlessly. Automated sanity reports pull data from CloudWatch, AppDynamics, and PEGA; then roll it up in one clear, consolidated email.
The final piece? A transparent Azure DevOps dashboard that gave leaders a real-time, no-excuses view into every pipeline, every environment, every deployment.
How our client Quietly Rewired Its Entire Software Delivery Model, By Ditching Manual PEGA Deployments
This isn’t a story about shaving a few hours off a release cycle. It’s about removing friction that teams had accepted as normal for far too long.
When our client moved to a fully automated, end-to-end deployment model for PEGA, it forced a shift that went beyond engineering. It reshaped how product, operations, and delivery teams worked together,and what they expected from their own processes.
Here’s what actually changed.
1. No More Crowds Around the Button
Before automation, deployments looked like this:
- Fourteen engineers involved
- CSV files passed around like hot potatoes
- SQL scripts manually reviewed
- People chasing approvals
- Artefacts manually pushed
- Everyone hoping it wouldn’t break in production
That wasn’t resilience. It was ritual. Every extra person added more surface area for errors,and more chances for something to fall through the cracks. With a fully automated pipeline, those tasks didn’t get reassigned. They got removed.
No one had to “own the deployment” anymore. It ran in the background. Quietly. Predictably.
The engineering team got their time back,to write code, fix real problems, and stop treating Friday releases like a dare.
2. Rollback = One Click, Not One Crisis
Ask any team what “rollback” really means and you’ll usually get some version of:
“We just fix it forward and pray.”
our client changed that by baking rollback into their deployment pipeline,not as a last-minute patch, but as a normal, tested, version-controlled step.
When something went wrong, the response wasn’t:
“Okay, everyone get on a call.”
It was:
“Just hit revert.”
No scavenging through old backups. No rewriting scripts. No late-night war rooms.Just one confident step back to a known-good state.
3. The Speed Boost That Didn’t Come at the Cost of Sleep
It’s easy to talk about velocity. It’s harder to show how that speed actually helped.
For our client, deployment lead times dropped by over 60%. But that wasn’t the headline.
The real impact showed up when:
- A critical update reached customers in days, not weeks
- A partner integration was fixed before it even became a problem
- A new feature went live while competitors were still gathering approvals
Speed mattered because it was sustainable. It didn’t rely on heroics. It didn’t come at the cost of sleep. It was baked into the system.
4. From “Let’s Hope We’re Covered” to Actual Audit Readiness
In regulated industries, manual processes aren’t just inefficient.
They’re dangerous.
Every undocumented fix, every email-based approval, every untracked config change is a liability waiting to surface during an audit,or worse, a breach investigation.
Before automation, our client’s compliance trail was scattered:
- Half in spreadsheets
- Some in email chains
- Some just… lost
Now?
Every deployment step is logged.
Every change is version-controlled.
Every approval has a timestamp and an owner.
If the auditors show up tomorrow, the answer isn’t.
“Let us pull together some reports.”
It’s:
“Here’s the full record.”
Risk didn’t vanish, but it became visible and manageable.
And that changed how everyone,from compliance officers to security teams,slept at night.
5. Finally, Everyone’s Looking at the Same Dashboard
Here’s how it used to work:
The engineering lead sent a Slack update.
The release manager shared a spreadsheet.
The PM forwarded an email.
And the exec still had no idea what stage the deployment was in.
Now, our client has a single source of truth.
With Azure DevOps dashboards and real-time deployment tracking, leaders can:
- See what’s going live today
- Check which releases passed quality gates
- Spot where something’s stuck, before it becomes a blocker
No more piecing together the truth from four different channels.
No more surprises in Monday standups.
This kind of visibility builds trust , because everyone’s reading from the same page.
Operations isn’t chasing updates. Business isn’t left in the dark.
And engineers don’t waste time explaining what’s already visible on the board.
The bigger win: unlocking engineering focus
When you remove repetitive manual work from talented engineers, you’re not just freeing up a few hours; you’re fundamentally changing the trajectory of what your teams can accomplish.
At our client, DevOps engineers had become the last line of defense in a system overloaded with manual checks and fragile processes. Every deployment cycle meant long calls, manual CSV file pushes, cross-team sign-offs, and the constant anxiety of “what if this breaks production?” Instead of building new capabilities or optimizing services for end users, they were stuck running playbooks that felt more like insurance policies than engineering work.
By automating the entire PEGA deployment lifecycle from code and package promotion to database and file configurations, including restarts and sanity checks, the engineers could finally shift their focus.
Here’s what that looked like in practice:
Proactive reliability engineering: Instead of reacting to incidents after each release, the team began investing in improving system resilience, strengthening rollback strategies, and tightening monitoring for early detection.
Accelerating innovation: Engineers were able to dedicate time to refining pipelines further, integrating advanced automated tests, and contributing to platform improvements that previously sat at the bottom of the backlog.
Enhanced cross-team collaboration: Freed from the grind of manual approvals and handoffs, DevOps engineers became strategic partners to development and product teams, influencing architecture decisions and delivery timelines from the start, not just at the deployment gate.
Talent retention and morale boost: Top engineers don’t want to be button-pushers. By eliminating repetitive tasks, our client reduced burnout and increased satisfaction, turning DevOps roles into high-leverage, intellectually rewarding positions.
Faster customer-facing improvements: With operational friction removed, teams could push meaningful updates and new features to production faster and more confidently, directly impacting customer satisfaction and business agility.
In short, automation didn’t just make deployments faster; it fundamentally redefined the role of engineering within the business.
The DevOps team went from being perceived as “the deployment team” – always fixing, always patching – to becoming force multipliers who empower the entire organization to move at the speed of market demands.
That’s the real value: unlocking the strategic potential of your most skilled people, and finally letting them do the work they were hired (and want) to do.
What does this mean for you
If your team is still stuck in “almost automated” deployments, here’s what you’re paying for:
- Slow feature rollouts that frustrate business stakeholders.
- Higher operational costs from wasted engineering hours.
- Increased risk of errors, outages, and compliance violations.
- Talent attrition, as top engineers tire of being “click monkeys.”
What our client achieved with Sandhata wasn’t a magic overnight fix. It was a systematic, phased transformation that replaced manual drudgery with automation precision and turned deployment from a dreaded bottleneck into a competitive advantage.
Want to see where your real bottlenecks are hiding?
Most organisations think they know where their delays come from; they’re almost always wrong.
We’ve helped large enterprises (like our client) expose their hidden inefficiencies and rebuild pipelines that don’t just work, but work brilliantly.
If you’re tired of “almost automated” and ready for deployments that actually deliver, let’s talk.
One last thought
You don’t need more “best practices” slides. You need a concrete, step-by-step plan that actually sticks.
We know how to build it. Let’s make your deployments as fast, reliable, and invisible as they should be: https://www.sandhata.com/contact-us
Daniyal Rayn