Every cloud team knows the feeling: low-leverage, repetitive work that keeps the lights on but doesn’t move the business forward. We have a name for that— engineering toil.
And in today’s high-stakes, high-velocity cloud environments, toil isn’t just annoying. It’s expensive.
It eats up engineering time, slows delivery, and blocks innovation. It’s also avoidable.
What Is Engineering Toil?
Google’s SRE teams defined toil as:
“Manual, repetitive, automatable, tactical work that scales linearly with service growth.”
In plain terms? Work that machines should be doing. And if you’re running cloud infrastructure at scale without a purpose-built automation platform, you’re swimming in it.
Common Engineering Toil in Terraform and Cloud Workflows:
- Manually running terraform plan and apply
- Approving and tracking changes in Slack or spreadsheets
- Debugging drift without visibility
- Writing custom scripts to enforce policies
- Reviewing code for basic issues (open S3 buckets, bad IAM roles)
- Handling endless “can you deploy this?” tickets
Multiply that by every developer, every environment, every week—and you’re looking at serious drag.
Why Toil Happens and Why It Often Goes Unnoticed
Terraform was a great start. But what came next?
A patchwork of GitHub repos, Jenkins jobs, in-house scripts, and Slack approvals.That’s not a platform. That’s a DIY trap.And it’s where toil lives—and multiplies.
But here’s the thing: most teams don’t even realize how much toil they’re carrying.
How do you know if your team has a toil problem?
- Engineers are writing the same scripts over and over for different environments.
- PRs are getting held up over basic config issues.
- Your SREs are swamped with “can you deploy this?” tickets.
- Infrastructure knowledge is tribal, not templatized.
- Debugging drift or failed applies eats half your week.
If your cloud engineers are acting like infrastructure babysitters instead of builders? You’ve got toil.
And AI is about to make it worse—or better.
AI is already accelerating software delivery. That means more code, more changes, more infra to support it. If you’re still relying on manual processes, AI just adds fuel to the fire.
But if you’ve built a modern delivery platform—one that automates away the busywork and bakes governance into the process—AI becomes a multiplier for velocity, not chaos.
Toil creeps in quietly. But it scales loud. And the only way to stop it is to replace it.
The Cost of Toil
Engineering toil doesn’t just waste hours. It damages momentum and morale.
- Slower delivery: Every manual step adds latency.
- Lower morale: Engineers didn’t sign up to babysit infrastructure.
- Increased risk: Repetitive work leads to mistakes and burnout.
- Opportunity cost: Every hour spent on toil is an hour not spent on architecture, velocity, or innovation.
And with AI accelerating software velocity across the enterprise, your infrastructure better keep up—or get left behind.
How ControlMonkey Eliminates Engineering Toil
ControlMonkey was built to erase engineering toil from the Terraform workflow—end to end. We replace glue code and human handoffs with one control plane that does it all.
- Terraform Automation, Reimagined
Self-serve deployments. PR-based workflows. Policy enforcement baked in. No custom scripts. No friction.- Auto-runs plans and applies with approval gates
- Templatized environments via QualityGate
- Import legacy resources into Terraform in seconds
- Drift? Gone. Visibility? Total.
Our Cloud vs. Code Guarantee detects drift before it becomes a problem—and helps fix it automatically.- Real-time infra snapshots
- Drift alerts with context
- One-click remediation
- Governance Without Grit
- Compliance shouldn’t be manual. ControlMonkey enforces org policies before things break—without slowing anyone down.
- Role-based controls
- Guardrails to prevent misconfigurations
- Audit trails for every change
And unlike homegrown pipelines or partial tools, it all runs on a platform built for Total Cloud Control.
From Engineering Toil to Total Cloud Control
Toil doesn’t scale. And in today’s cloud, neither should your engineering team.
ControlMonkey eliminates Terraform toil by replacing manual glue with intelligent automation and proactive governance—giving engineers back their time, and your company back its velocity.
FQA - Engineering Toil, DevOps Toil and SRE Toil
Toil refers to repetitive, manual tasks that add little long-term value – like re-running scripts, debugging drift, or handling infra tickets. In software engineering, toil slows teams down and causes burnout.
Engineering toil in DevOps includes low-leverage tasks like manual Terraform applies, Slack-based approvals, and firefighting drift. These tasks scale with infra, but not with business value – making them a bottleneck.
Toil consumes SRE time with non-strategic tasks. Instead of improving system reliability, they’re stuck deploying code, debugging misconfigurations, or managing infrastructure manually.
According to Google’s SRE handbook, toil is work that is manual, repetitive, automatable, and scales linearly. Eliminating toil is a core tenet of site reliability engineering.
DevOps toil slows you down. Automation speeds you up. Replacing toil with automation means faster delivery, fewer production issues, and happier teams.
