Catalog
concept#DevOps#Software Engineering#Reliability

Automation

Automation refers to automating repetitive tasks and processes using software, scripts or tools to reduce manual work and human error.

Automation shapes repetitive technical and organizational workflows so they run reproducibly, reliably and efficiently without manual intervention.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

CI/CD servers (e.g. Jenkins, GitLab CI)Configuration management tools (e.g. Ansible, Terraform)Monitoring and observability tools

Principles & goals

Idempotence: Repeatable actions without side effects.Automate what is reproducible and error-prone.Transparency: Actions, logs and results must be visible.
Build
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Faulty automation can cause widespread outages.
  • Overreliance on automation reduces human oversight.
  • Security flaws in automation scripts compromise systems.
  • Write idempotent automation tasks
  • Integrate comprehensive logging and metrics
  • Version configuration and automation artifacts

I/O & resources

  • Process descriptions and runbooks
  • Script and configuration libraries
  • Monitoring and telemetry data
  • Reproducible artifacts and deployments
  • Action and audit logs
  • Automated remediation actions or escalation tickets

Description

Automation shapes repetitive technical and organizational workflows so they run reproducibly, reliably and efficiently without manual intervention. It includes orchestration, script- and tool-based execution as well as policies for error handling and monitoring. The aim is consistency, scalability and faster lead times.

✔

  • Reduced human errors and higher consistency.
  • Faster lead times and more frequent releases.
  • Better scalability through reproducible processes.

✖

  • Initial effort to set up and maintain automation.
  • Not all decisions can be safely automated.
  • Complexity can be shifted into automation logic.

  • Pipeline lead time

    Time from commit to successful deployment.

  • Change failure rate

    Share of deployments that fail after a change.

  • MTTR (Mean Time to Recovery)

    Average time to recover after an incident.

Automated deployment with Ansible

Infrastructure and applications described as playbooks and provisioned reproducibly.

CI/CD with Jenkins

Jenkins executes builds, tests and deployments according to pipeline definitions.

Cloud autoscaling

Cloud provider scales resources automatically based on metrics.

1

Identify and prioritize processes

2

Set up an automation pilot with clear success criteria

3

Develop and test scripts and playbooks

4

Roll out incrementally with monitoring and feedback

⚠️ Technical debt & bottlenecks

  • Outdated scripts without tests
  • Hardcoded configurations in automation logic
  • Insufficient modularization makes changes hard
Manual approvalsComplex legacy processesInsufficient test coverage
  • Automatically deleting resources without safeguards
  • Untested changes pushed directly into production pipelines
  • Sensitive data stored in plaintext in automation scripts
  • Hidden dependencies between automation steps
  • Insufficient rollback strategies
  • Lack of observability for automated actions
Scripting and automation techniquesKnowledge of CI/CD and orchestration toolsUnderstanding of logging, monitoring and fault diagnosis
Reproducibility of deploymentsFast, safe delivery of changesObservability and fault detection
  • • Security policies and access rights
  • • Compatibility with existing systems
  • • Organizational acceptance and governance