• Home
  • BVSSH
  • Engineering Enablement
  • Playbooks
  • Frameworks
  • Good Reads
Search

What are you looking for?

Standard : Operational tasks are automated before they become recurring toil

Purpose and Strategic Importance

This standard ensures recurring operational tasks are automated before they become a burden, preserving engineering focus for high-value work. It helps teams scale sustainably and avoid burnout from repetitive manual effort.

Aligned to our "Automate everything possible" policy, this standard improves efficiency, consistency, and system reliability. Without it, teams risk wasted effort, growing technical debt, and reduced capacity for innovation.

Strategic Impact

  • Improved consistency and quality across teams
  • Reduced operational friction and delivery risks
  • Stronger ownership and autonomy in technical decision-making
  • More inclusive and sustainable engineering culture

Risks of Not Having This Standard

  • Slower time-to-value and increased rework
  • Accumulation of inconsistency and process debt
  • Reduced trust in engineering data, systems, or ownership
  • Loss of agility in the face of change or failure

CMMI Maturity Model

  • Level 1 – Initial: Operational tasks are handled manually and repeatedly. Toil accumulates, reducing team focus and morale, with no process for identifying automation opportunities.

  • Level 2 – Managed: Some teams begin automating common tasks, but efforts are inconsistent and reactive. Automation depends on individual initiative and is not tracked.

  • Level 3 – Defined: Teams proactively identify and automate recurring tasks. Practices for detecting and addressing toil are documented and adopted across teams.

  • Level 4 – Quantitatively Managed: Toil and automation metrics are tracked. Teams monitor frequency and effort of operational tasks, using data to prioritise automation efforts and reduce manual overhead.

  • Level 5 – Optimising: Automation is embedded in engineering culture. Teams continually refine their systems to eliminate toil, and automation opportunities are fed into roadmaps, platform improvements, and shared tooling.


Key Measures

  • Adoption rates and coverage across teams
  • Impact on delivery metrics, quality, or team health
  • Evidence of ownership, governance, or learning loops
Associated Policies
  • Automate everything possible
Associated Practices
  • Code Reviews & Pull Requests
  • Compliance-as-Code
  • Configuration as Code
  • Data Mesh
  • Immutable Infrastructure
  • Infrastructure as Code (IaC)
  • Security as Code
  • Serverless Architecture
  • Continuous Delivery (CD)
  • Continuous Deployment
  • Continuous Integration (CI)
  • GitOps
  • Security Testing in CI/CD
  • Developer Environment Automation
  • InnerSource Development
  • Operational KPIs for Dev Teams
  • Twelve-Factor App
  • Drift Detection & Correction
  • Health Checks & Readiness Probes
  • Log Correlation for RCA
  • On-Call Rotation Health Checks
  • Runbooks and Playbooks
  • Self-Healing Systems
  • Automated Incident Response
  • Feedback Loops from Ops to Dev
  • Real-time Event Streaming
  • Automated Rollbacks
  • Deployment Freeze Windows
  • Deployment Pipelines
  • Ensemble Testing
  • Load & Performance Testing
  • Shadow Testing in Production
  • Test Data Management
  • Observability-Driven Design
  • Async Collaboration Norms
Associated Measures
  • Deployment Frequency
  • Mean Time to Recovery (MTTR)
  • Automated Remediation Rate

Technical debt is like junk food - easy now, painful later.

Awesome Blogs
  • LinkedIn Engineering
  • Github Engineering
  • Uber Engineering
  • Code as Craft
  • Medium.engineering