🚨 What is Toil in SRE?
Toil is a term coined by Google SREs to describe a specific class of operational work that is manual, repetitive, automatable, and scalable with service growth — but not with team growth.
💡 Toil is the work you do that doesn’t scale and adds no enduring value.
📘 Official Definition (from Google SRE Book)
“Toil is the kind of work tied to running a production service that tends to be manual, repetitive, automatable, tactical, reactive, and lacking enduring value.”
Reference: Google SRE Book – Eliminating Toil
🧩 Key Characteristics of Toil
| Characteristic | Description |
|---|---|
| Manual | Performed by humans instead of automation |
| Repetitive | Occurs often and follows a predictable pattern |
| Automatable | A script or tool could handle it |
| Tactical | Immediate fix, not a long-term solution |
| Reactive | Triggered by alerts/incidents |
| Non-durable | Leaves no lasting improvement to the system |
✅ Examples of Toil in SRE
| Example | Why it’s Toil |
|---|---|
| Manually restarting failed pods | Repetitive, automatable |
| Fixing disk full alerts every week | Predictable, non-durable |
| Reconfiguring firewall rules by hand | Can be automated via Terraform or scripts |
| Responding to noisy alerts | Reactive, not value-adding |
| Generating weekly reports manually | Easily scriptable |
| Approving routine access requests | Better handled with IAM automation or workflows |
🚫 Not All Operational Work is Toil
| Work Type | Toil? | Why |
|---|---|---|
| Designing alerting strategy | ❌ | Strategic, not repetitive |
| Writing Terraform modules | ❌ | Automates infrastructure |
| Debugging complex outages | ❌ | Requires deep thinking, high-value |
| Reviewing architectural changes | ❌ | Adds long-term value |
🧠 Why Toil is Bad
- Burns out engineers
- Distracts from innovation
- Delays projects
- Doesn’t scale
- Leads to boredom and attrition
Google recommends that SREs should spend <50% of their time on Toil, and ideally much less.
🔧 How to Identify Toil in Your Environment
| Signal | Interpretation |
|---|---|
| You’re doing it more than twice a month | Candidate for automation |
| Your incident postmortems are repetitive | Root cause not fixed |
| You can document it easily | You can probably automate it |
| Onboarding involves lots of manual steps | It’s Toil |
| SOPs require step-by-step human execution | Replace with scripts/pipelines |
🛠️ How to Reduce or Eliminate Toil: A Practical Tutorial
🔹 1. Catalog Your Repetitive Tasks
Create a list of all recurring activities:
- Weekly report generation
- Alert acknowledgements
- Manual deployment steps
- Restarting services
🔹 2. Score Each Task on “Toil Scale”
Create a scoring matrix:
| Task | Manual | Repetitive | Automatable | Urgency | Toil Score |
|---|---|---|---|---|---|
| Restarting pods | ✅ | ✅ | ✅ | High | 3 |
| Debugging memory leak | ❌ | ❌ | ❌ | High | 0 |
| Weekly CPU report | ✅ | ✅ | ✅ | Low | 3 |
Focus on tasks with highest Toil Score.
🔹 3. Automate Using Tools
| Tool | Use Case |
|---|---|
| Bash/Python | Small scripts to start |
| Ansible | Automate infra/config |
| Terraform | Infra provisioning |
| Jenkins/GitHub Actions | CI/CD workflows |
| Prometheus + Alertmanager | Alerting automation |
| PagerDuty/Opsgenie | Auto-remediation hooks |
| Runbooks + Automation | Click-to-run fixes |
🔹 4. Introduce Auto-Remediation
Example: Auto-restart failed pods in Kubernetes
apiVersion: v1
kind: Pod
metadata:
name: resilient-app
spec:
containers:
- name: app
image: my-app
livenessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 3
periodSeconds: 5
With liveness probes, Kubernetes eliminates the need for manual restarts.
🔹 5. Alert Intelligently
Bad:
- “Disk usage > 80%”
Good:
- “Disk usage projected to reach 100% in 3 hours”
Even better:
- Automatically clean up temp files or notify owner before alerting.
Use suppressions, alert deduplication, and runbook links to avoid Toil from noisy alerts.
🔹 6. Measure Toil Reduction
Track metrics like:
| Metric | Example Tool |
|---|---|
| Time spent per incident | Jira, PagerDuty logs |
| # of repeated manual tasks | Custom spreadsheet |
| Alert volume per on-call | Prometheus |
| Automation coverage | CI/CD stats |
Create a Toil Dashboard to monitor improvements.
💼 Real-World Example: Toil Reduction Project
Problem:
Every on-call SRE had to:
- Manually restart a failing job
- Archive logs to S3
- Email stakeholders
Solution:
- Created a Jenkins pipeline triggered via API
- Used
kubectlto auto-restart job - Uploaded logs via
aws s3 cp - Sent Slack messages using Webhooks
Result: 80% reduction in manual toil during on-call.
📊 Summary: SRE Toil Elimination Mindset
| Step | Description |
|---|---|
| Identify | Use logs and retros |
| Quantify | Track frequency and time |
| Prioritize | Automate high-toil tasks first |
| Automate | Use the right tool for the task |
| Monitor | Show visible reduction |
🔚 Final Thoughts
Toil is the silent killer of productivity and innovation in SRE. Reducing toil:
- Boosts engineer happiness
- Improves system reliability
- Frees time for strategic projects
“If you do something more than twice, automate it.”