Runbooks For Operations

Why this matters

Schedulers (Airflow, ADF, Prefect, cron) run critical data pipelines. When a job fails at 02:00, people need a clear, safe set of steps to recover quickly. A good runbook turns panic into repeatable action, reduces downtime, and prevents guesswork. As an ETL Developer, you will write and maintain these runbooks so on-call responders can diagnose, fix, and communicate issues confidently.

Concept explained simply

A runbook is a short, structured, step-by-step guide that tells someone: what broke, how to confirm it, how to fix it, and how to prevent it next time. It is not a novel; it’s the minimum practical instructions to restore service safely.

Mental model

• Symptom: What you see (alert, error message, metric spike).
• Impact: Who/what is affected (SLAs, downstream tables, dashboards).
• Immediate actions: Safe things anyone can do now to stabilize (pause, mute noisy alerts, clear stuck runs).
• Diagnosis: Short checks to find the root cause (logs, inputs, credentials, capacity).
• Remediation: The fix (rerun, backfill, redeploy, rotate secret).
• Validation: How to verify success (row counts, data freshness, DAG state).
• Communication: Who to notify and what to say.
• Prevention & follow-up: How to avoid repeat incidents.
• Escalation: When and to whom to hand off.

Runbook essentials (include these sections)

• Title & Last updated
• Scope: Which pipeline(s), environment(s), and scheduler(s)
• Triggers/Symptoms: Common alerts, error text
• Business Impact: Affected data products and SLAs
• Immediate Safe Actions
• Diagnosis Steps
• Remediation Steps
• Rollback/Undo (if applicable)
• Validation Checklist
• Communication Template
• Escalation Matrix
• Prevention/Follow-up tasks
• Access/Permissions needed

Worked examples

Templates you can copy

Title: [Pipeline Name] Runbook
Last updated: [YYYY-MM-DD]
Scope: [Env, Scheduler, DAG/Job IDs]

Triggers/Symptoms:
- [Alert name or error text]
- [Metric threshold]

Business Impact:
- [Affected tables/dashboards]
- [SLA and severity]

Immediate Safe Actions (do first):
- [Pause downstream / stop retries / mute noisy alerts]

Diagnosis:
1) Check logs at [task/job]
2) Verify inputs [path/object/row counts]
3) Validate credentials/connectivity

Remediation:
- If [condition A]: do [steps]
- If [condition B]: do [steps]

Rollback/Undo (if any):
- [How to revert changes]

Validation Checklist:
- [Task green / table row count / freshness OK]

Communication Template:
"Incident: [pipeline] [status]. Impact: [what]. ETA: [time]. Owner: [name]."

Escalation:
- After [X mins] or [criteria], page [team/person]

Prevention/Follow-up:
- [Alert improvements, guardrails]

Access Required:
- [Secret manager, scheduler UI, warehouse role]

[Time] [Pipeline/Job]: [Issue summary]
Impact: [Data/products affected]
Cause (suspected): [Cause]
Action: [What you did]
ETA/Next update: [Time]
Owner: [Name or rotation]

How to write a runbook in 10 minutes

1. Write the symptom and the one-sentence impact.
2. List 3 immediate safe actions anyone can do.
3. Add the top 3 diagnosis checks (inputs, credentials, logs).
4. Define the two most likely remediation paths with bullet steps.
5. Add a 3-point validation checklist.
6. Paste the Ops Note template for comms.
7. State escalation criteria (time or severity).

Common mistakes and how to self-check

• Too long, not actionable: Keep steps short; use bullets, not paragraphs.
• Missing validation: Always specify how to confirm success.
• No safe first actions: Stabilize before deep diagnosis.
• Assumes expert knowledge: Include exact paths, task names, and where to click.
• Forgets communication: Provide a ready-to-send message.
• No escalation rule: Define a time or symptom threshold to escalate.

Who this is for

• ETL Developers and Data Engineers operating scheduled pipelines.
• On-call responders for data platforms.
• Analyst engineers who publish data products on SLAs.

Prerequisites

• Basic understanding of your scheduler (e.g., DAGs, tasks, retries).
• Access to logs, storage, and warehouse environments.
• Familiarity with your team’s incident channel and escalation policy.

Learning path

• Start: Draft minimal runbooks for your top 3 pipelines.
• Next: Add validation metrics and partition checks.
• Then: Introduce backfill strategies and safe rollback steps.
• Finally: Standardize comms and escalation across pipelines.

Practical projects

• Create a runbook pack: three pipelines, each with diagnostics, remediation, and comms templates.
• Drill: Simulate a failure and run the playbook end-to-end with a teammate.
• Guardrails: Add a pre-publish validation task based on your runbook checks.

Exercises

Note: Anyone can do the exercises and test for free. Only logged-in users will have their progress saved.

1. Exercise 1: Draft a minimal runbook for a failed daily customer_orders pipeline due to a missing upstream file. Include: Symptoms, Impact, Immediate Actions, Diagnosis, Remediation, Validation, Communication, Escalation.
2. Exercise 2: Convert a verbose incident blurb into a concise Ops Note using the template provided above.
3. Exercise 3: Write a short decision tree (pseudocode or bullets) for choosing between rerun, backfill, or skip for a late partition.

Self-check checklist

• I named exact tasks/files/paths involved.
• I listed at least 2 safe immediate actions.
• I included a concrete validation step with numbers.
• I wrote a ready-to-send communication line.
• I specified when to escalate and to whom.

Next steps

• Add your runbooks to your team wiki or repo. Mark owners and last updated dates.
• Run a 30-minute tabletop incident review monthly to keep them current.
• Automate one validation check directly in your pipeline.

Mini challenge

Pick one critical DAG. In 15 minutes, write the minimal runbook using the template. Ask a teammate outside your team to follow it. If they get stuck, improve the step they stumbled on.

Quick Test

Try the quick test below. It’s available to everyone; logged-in users will have their score saved to their learning progress.