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Modern Day Microservices Delivery - Code & Come...

Modern Day Microservices Delivery - Code & Comedy 2017

Microservices shed a new light on application lifecycle management
and software delivery. The increased complexity of distributed engineering requires advanced testing and automation, resulting in a mostly different setup. Join this talk to get insights on how a typical delivery chain can be improved to suit microservices, using tools such as Spinnaker and Jenkins pipelines.

Andreas Evers

February 08, 2017
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  1. High-performing IT organizations deploy 200x more frequently with 2555x shorter

    lead times they have 3x fewer failures and recover 24x faster - Puppet labs state of devops report 2016
  2. Chaos Tests CDCT Unit Tests Integration Tests SLA Tests Technical

    Analysis Intake Business Workshops Conceptual Design Functional Design Prototyping Commit & Push Quality Tests Build Locally Aggregate / Analyze Logs Monitor Validate Hypotheses Canary Tests A/B Tests User Research Co-Creation User Testing User Stories Visual Design Write Tests & Code End to End Tests Unit Tests Integration Tests Penetration Tests Load & Stress Tests Smoke Tests Deploy 2 Test Environment Notify Review & Merge
  3. Objective: Resiliency Practice: Chaos Monkey Chaos Tests CDCT Unit Tests

    Integration Tests SLA Tests Technical Analysis Intake Business Workshops Conceptual Design Functional Design Prototyping Commit & Push Quality Tests Build Locally Aggregate / Analyze Logs Monitor Validate Hypotheses Canary Tests A/B Tests User Research Co-Creation User Testing User Stories Visual Design Write Tests & Code End to End Tests Unit Tests Integration Tests Penetration Tests Load & Stress Tests Smoke Tests Deploy 2 Test Environment Notify Objective: Improve throughput; increase visibility and transparency Practice: Scrum or Kanban Objective: Code quality; faster refactoring; reduced maintenance cost; faster feedback Practice: Test-driven development Review & Merge Objective: Engineers from other teams can contribute code changes they need Practice: Pull request contribution model Objective: Eliminate waste; faster time to value Practice: Work in small batches Objective: Eliminate handoffs Practice: Product owner embedded in the team Objective: Any change can be deployed into production at any time Practice: Unattended automation with a CI/CD pipeline Objective: Achieve extreme agility with instant feedback from real users Practice: Test on production Objective: Learn and improve from failures Practice: Blameless postmortems Objective: Easily detect measurable signals as needed to run your experiments Practice: If it moves, measure it Objective: Improve decision making, reduce uncertainty and enable continuous improvement Practice: Transparency Objective: All team members have the necessary knowledge to do a given task Practice: Pair Programming