🧨 The Silent Killer of DevOps Velocity: Are You Drowning in Toil?
DevOps teams are under pressure to move fast, stay compliant, and keep systems stable. But there’s a silent productivity killer lurking in your workflows — and it's likely costing you time, innovation, and morale.
It’s called engineering toil.
In this post, we’ll break down what toil is, why it’s rampant in DevOps, and how Infrastructure as Code (IaC) + automation can help you take control — instead of constantly firefighting.
⚡️ DevOps Is Moving Fast — But Infra Can’t Keep Up
As cloud environments scale, things get messy:
- More cloud accounts 🧾
- More AI-generated infra demands 🤖
- More pressure to deliver faster without more headcount ⏱️
Teams often resort to manual workarounds and reactive fixes — which leads to bloating, risk, and inefficiency. And when you’re still managing environments manually while AI accelerates delivery? That’s pouring gas on a fire.
🧱 What Is Engineering Toil?
Toil is the work engineers hate to do but have to:
Manual, repetitive, automatable tasks that scale linearly with usage.
According to Google’s SRE Book, toil should account for less than 50% of an engineer’s time. Yet most teams blow past that threshold without even realizing it.
Examples of toil:
- Manually running
terraform plan - Copy-pasting configs across modules
- Tracking change approvals in spreadsheets
- Manually reviewing IAM permissions and S3 policies
It’s the DevOps version of death by a thousand cuts.
😵 The Real Cost of Toil
Toil does more than slow you down:
- 🚫 Kills productivity
- 😤 Frustrates engineers
- 🧠 Leads to knowledge loss when people leave
- 😩 Causes burnout and stagnation
- 🐌 Slows delivery and blocks innovation
As LeadDev points out, unchecked toil results in attrition. And if the engineers who built your infra walk out — so does your operational knowledge.
📉 Why It Often Goes Unnoticed
Here’s the catch: most DevOps teams are juggling a patchwork of tools — GitHub repos, Jenkins jobs, Slack approvals, shell scripts.
This DIY approach creates invisible toil:
Looks fine...
Runs fine...
Costs you hours every week.
Toil creeps in quietly. But it scales loudly.
In fact, we’ve seen some teams attempt to manually calculate cloud infra usage and costs across environments using loosely maintained internal wikis or even outdated breakdowns from early-stage pricing analysis tools — like this archived Terraform cost overview{: rel="nofollow noopener ugc" }.
These patches aren’t built for velocity — and toil thrives in the gaps.
🧪 What the Research Says
- 📘 Google’s SRE book emphasizes the value of automation and long-term design over manual work.
- 📊 Eindhoven University found that even when toil is understood, cultural inertia and lack of time often prevent teams from automating.
- ☁️ Google Cloud’s blog outlines steps for identifying and reducing toil with SRE principles.
TL;DR: What machines should be doing is still being done manually.
🛠️ How IaC Helps Kill Toil
Tools like Terraform and OpenTofu turn infra into repeatable, version-controlled code. Combine them with automation and you get massive wins.
🧮 Toil Traits vs. IaC
| 🧨 Toil Trait | ✅ IaC Fixes It By... |
|---|---|
| Manual | Automating setup and config |
| Repetitive | Reusing scripts across environments |
| Automatable | Running once, applying anywhere |
| Tactical | Enabling proactive system design |
| No enduring value | Creating reusable templates |
| Scales linearly | Scaling infra without extra manual effort |
🔁 Real-World Toil in Terraform Workflows
Common toil examples we see with Terraform:
- Manually previewing changes with
terraform plan - Approving infra changes in Slack or spreadsheets
- Debugging cloud drift without real visibility
- Writing ad-hoc scripts to enforce policies
- Manually provisioning VMs
- Reviewing PRs for S3 bucket exposure or IAM flaws
- Your SRE drowning in “Can you deploy this?” requests
Each one might feel “small” — until you multiply by dozens of engineers, environments, and deployments.
🧭 Reduce Toil with Long-Term Thinking
Toil is measurable: use survey data, ticket volume, and time tracking to uncover the biggest culprits.
While a little toil is okay, too much erodes team performance.
Pro tip: Prioritize system improvements over one-off fixes. Design with scale in mind.
🚀 ControlMonkey: The Terraform Toil Terminator
ControlMonkey eliminates engineering toil with end-to-end Terraform automation — no glue scripts, no friction.
🧩 What You Get:
- Auto-runs
planandapplywith approval gates - PR-based, self-service deployments
- Templatized environments with QualityGates
- Instant import of legacy resources
- Real-time drift detection and one-click remediation
- Cross-cloud visibility
- Policy guardrails and built-in compliance
It’s Terraform automation — without the toil tax.
⚖️ From Toil to Total Cloud Control
Manual Terraform workflows can’t keep up with modern velocity.
ControlMonkey replaces toil with:
- ✅ Automation
- ✅ Drift detection
- ✅ Governance without grit
Give your team back their time — and your org back its engineering velocity.
💬 How Do You Fight Toil?
What toil patterns do you see most often in your team? Drop a comment with your own strategies or blockers — let’s trade ideas 👇
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