Continuous Deployment Chorzów

Methods of delivering software are constantly evolving in order to increase speed to market without sacrificing reliability and stability. Mastering development end to end, from version control to production, and building production-ready code is now more important than ever. Continuous deployment takes it one step further. This method for delivering software automates the final step to production and enables faster feedback and safer releases.Based on years of work with medium to large organizations at Thoughtworks, author Valentina Servile explains how to perform safe and reliable deployments with no manual gate to production. You'll learn a framework to perform incremental, safe releases during everyday development work, structured exclusively around the challenges of continuous deployment in nontrivial, distributed systems. Complete with interviews and case studies from fellow industry professionals.Close the feedback loop and leverage the production environment to manage your end-to-end development lifecycle efficiently. This book helps you:Take observability, performance, test automation, and security into account when splitting work into incrementsCreate a daily development plan that takes immediate deployments to production into accountDeploy work in progress to production incrementally without causing regressionsUse patterns to refactor live functionality and alter persistence layersTest and release features in production using different feature toggle configurations Spis treści: Foreword Preface Who This Book Is For What You Need to Read This Book What This Book Will Cover Conventions Used in This Book OReilly Online Learning How to Contact Us Acknowledgments I. Continuous Deployment 1. Continuous Deployment Deploying Every Few Months or Years Deploying Every Few Days Deploying Continuously eXtreme Programming If It Hurts, Do It More Often Smaller, less-painful batches Incentive for automation DevOps The Barrier Between Dev and Ops Joining Dev and Ops Automation, Automation, Automation Continuous Integration Continuous Delivery A Final Gate to Production One Step Further: Continuous Deployment Implementation Implications Is It Dangerous? Summary 2. Benefits One-Piece Flow and Lean Manufacturing Origins of Lean Manufacturing Batch production One-piece flow Reducing batch sizes Lowering transaction costs Lean and Software Development Inventory in software Batches in software Lowering transaction cost in software One commit = one artifact with continuous integration One commit = one preproduction deployment with continuous delivery One commit = one production deployment with continuous deployment Continuous flow ratio DORA Metrics Throughput Metrics Deployment frequency Lead time for changes Stability Metrics Mean time to recover Change failure rate Shifting Quality Left How Continuous Deployments Force a Quality Shift to the Left The Effects of Automating Quality Gates Summary 3. The Mindset Shift Defining a Change Versus Applying a Change Hiding Work in Progress Version Control Branches Execution Branches Feature toggles Implementation Benefits What about static feature toggles? Expand and contract Implementation Benefits Feature toggles versus expand and contract by type of change A conclusion on hiding work in progress Distributed Systems Contracts Between Systems Formal contracts Informal contracts Contracts Between Paths to Production Adding New Features: When Order Matters With a gate to production: Order of deployment Without a gate to production: Order of development Feature toggles Refactoring: When Timing Matters With a gate to production: Timing of deployment Without a gate to production: Timing of development Antipattern: Delaying integration Antipattern: Pausing pipelines Expand and contract A Deployment Is Not a Release Releases Deployments Differences Overlap End-to-End Delivery Life Cycle Without Continuous Deployment Doing QA Done Implications With Continuous Deployment Doing QA Done Implications Summary 4. You Must Be This Tall Cross-Functional, Autonomous Teams Fast Decision Making Implementation Autonomy Frequent Integration Short-lived branches Short-lived branches versus feature branches Trunk-based development Frequent Code Reviews Pull requests Pair programming Psychological safety Automated Code Analysis Test Automation The testing pyramid model The Swiss cheese model Test-first Outside-in What about legacy? Zero-Downtime Deployments Blue/green deployments Rolling deployments Canary deployments Deployment strategies and manual steps Antipattern example: Blue/green as a QA tool Antipattern example: Partial deployments as a canary release tool Observability and Monitoring Alerts Information versus noise Stakeholder Trust How Do We Convince the Boss? When Are We Ready? Summary 5. Challenges Systems That Are Sensitive to Deployments Interruption of Long-Running Processes Mitigation: Switch to messaging or event-based architectures Instances whose job is to complete jobs Sticky Sessions Mitigation: Keep state external Invalidation of Client-Side Caches Mitigation: Be deliberate about your caching policies Scaling Interruptions Mitigation: Keep application startup time low Mitigation: Introduce more generous scaling policies Mitigation: Perform pre-scaling A Constant Stream of Cold Instances Mitigation: Use external caches User-Installed Software Desktop Applications Mitigation: Introduce self-applying updates Mobile Apps Mitigation: Shift control to the server side Web views Progressive web apps Server-driven UIs Appliances and Other Devices Libraries and Frameworks Regulated Industries Cognitive Load Overly Busy Path to Production Mitigation: Break your monoliths Mitigation: Rethink your teams and domains Inattention During Deployments Mitigation: Use good alerting Mitigation: Keep your pipelines fast Mitigation: Shift mindset around development Breadth of Knowledge Required Mitigation: Introduce comprehensive training programs Steep Onboarding Curve Mitigation: Use pair programming and mob programming Scheduling Development Work Mitigation: Core development hours Mitigation: Perform team code reviews Summary II. Before Development 6. Slicing Upcoming Work Horizontal Versus Vertical Slicing Horizontal Slicing Vertical Slicing With Continuous Deployment Effective Vertical Slicing MVP INVEST Small Slices Example: The Groceroo Company The Feature: Last-Minute Items The User Interface The Admin Interface The Problems of Implementing with Horizontal Slicing Task 1: Persistence layer Task 2: Backend layer Create and modify items Add to basket logic Task 3: Frontend layer Carousel Admin interface Feature toggle Implementation with Vertical Slicing User story 1: Add a simple carousel User story 2: Make the carousel configurable User story 3: One-click add to basket User story 4: Add to basket by different quantities Summary 7. Building for Production Deployability Requirements Hiding with Feature Toggles New top-level toggle New nested toggle Under existing toggle Hiding with Expand and Contract Alternative system Alternative operation Alternative field Generify field type Hiding in Version Control Branch Unhidden Pausing the Pipeline Testability Requirements High-Level Automated Tests Manual Exploratory Testing Observability Requirements Maintaining Logs and Metrics Maintaining Dashboards and Alerts Security Requirements New User Input Storing New Data New Dependencies New Infrastructure Performance Requirements New Network Requests Data Size Persistence Layer A (More) Complete User Story Template Example: Adding CFRs to Groceroo User Stories User Story 1: Add Simple Carousel Deployability requirements Testability requirements Observability requirements Security requirements Performance requirements User Story 2: Admin Area Deployability requirements Testability requirements Observability requirements Security requirements Performance requirements User Story 3: Add to Basket Button Deployability requirements Testability requirements Observability requirements Security requirements Performance requirements User Story 4: Quantity Selector Deployability Testability Observability Security Performance Summary III. During Development 8. Adding New Features Our User Story The Groceroo Application Current State Target State Frontend Backend Persistence How Do We Get There? Feature toggles Multiple layers: Outside in Implementing with a Feature Toggle Deployment 1: Introducing the toggle Deployment 2: Adding code in the UI layer Deployment 3: Adding code in the backend layer Deployment 4: Adding code in the persistence layer Release Deployment 5: Toggle cleanup Summary 9. Refactoring Live Features Our Task The Product Identifier System The Problem The Solution Current State Frontend Backend Persistence Target State Frontend Backend Persistence How Do We Get There? Expand and Contract Multiple Layers: Inside Out Implementing with Expand and Contract Outer Expand Phase: The Product Table Deployment 1: Expand the product table Migrating the POST /product Endpoint Deployment 2: Expanding the POST /product endpoint Deployment 3: Migrating the POST /product endpoint Deployment 4: Contracting the POST /product endpoint Migrating the GET /product Endpoint Deployment 5: Expanding the GET /product endpoint Deployment 6: Migrating the GET /product endpoint Deployment 7: Contracting the GET /product endpoint Migrating the Basket Table Deployment 8: Expanding the basket table Deployment 9: Expanding the POST /basket endpoint Deployment 10: Migrating the POST /basket endpoint Deployment 11: Contracting the POST /basket endpoint Deployment 12: Contracting the basket table Outer Contract Phase: Cleaning Up the Product Table Deployment 13: Contracting the product table Summary 10. Data and Data Loss Our Task The Problem The Solution Current State Persistence Backend Target State Persistence Backend How Do We Get There? Failure Mode: Simultaneous Change Failure Mode: Simple Expand and Contract Solution: Temporary Database Trigger Solution: Double-Write Step 1: Expand the database column Step 2: Double-write to both columns Step 3: Synchronize the data Step 4: Migrate write and read the columns Step 5: Contract the columns Solution: Double-Read Step 1: Expand the database column Step 2: Double-read and migrate write to both columns Step 3: Synchronize the data Step 4: Migrate the read Step 5: Contract the old column Implementing with Double-Write Deployment 1: Expand the Database Column Deployment 2: Double-Write to Both Columns Deployment 3: Synchronize the Data Deployment 4: Migrate Write and Read to Both Columns Deployment 5: Contract the Columns Implementing with Double-Read Deployment 1: Expand the Database Column Deployment 2: Double-Read and Migrate Write the Columns Deployment 3: Synchronize the Data Deployment 4: Migrate Read the Column Deployment 5: Contract the Columns NoSQL Migrate on Read Migrate on read forever Migrate on read and convert on write Custom Batch Update Conclusion on NoSQL Summary IV. After Development 11. Testing in Production Why You Should Test in Production Data Volume Accuracy Data Shape Accuracy Realistic Request Patterns Realistic Incoming Traffic Volume Realistic Outgoing Traffic Volume Realistic Size and Number of Servers Realistic Application Configuration Realistic Network Configuration Real Version of Other Teams Services Real Version of Third-Party Services Lower Cost Better Data Hygiene How to Test in Production Feature Toggle Activation Strategies Query parameters Where to use When to use Request headers Where to use When to use Cookies Where to use When to use User identifier Where to use When to use User roles Where to use When to use Challenges Managing test data Hiding test data Preventing test data leakages Debugging frontend code The case for source maps in production Life After Staging Summary 12. Releasing Antipattern: Big Bang Releases Comparing Before Versus After States Comparing Simultaneous States Antipattern: Partial Releases Through Partial Deployments Using Feature Flags for Releases Coordinating Feature Flag Releases in Distributed Systems Antipattern: Independent Flag State for Each Service Propagating Flag State Down the Call Chain Centralized Feature Flag State Canary Releases By Traffic Percentage By Device Per-device toggle Backend-controlled toggle By Country By User Segment A/B Testing Analytics Experiment Best Practices Test one variable at a time Avoid test parallelism Have a sufficient sample size Schedule Delivery Around Experiments Types of A/B Tests Tests with two variants Split or redirect tests Multivariate tests Full factorial Fractional factorial Do You Need a Canary Release or an A/B Test? Summary Conclusion and Next Steps V. Case Studies Case Study: AutoScout24 AutoScout24s Context Adoption of Continuous Deployment at AutoScout24 Overcoming Organizational Obstacles Overcoming Technical Obstacles AutoScout24s Implementation of Continuous Deployment How AutoScout24 Makes Continuous Deployment Safe Code review process Test automation Zero-downtime deployments Observability How AutoScout24 Supports Junior Engineers Case Study: OTTO OTTOs Context Adoption of Continuous Deployment at OTTO Working with Organizational Barriers Working with Technical Barriers OTTOs Implementation of Continuous Deployment OTTOs Path to Production How OTTO Makes Continuous Deployment Safe Team culture Resilience patterns Test automation Deployment strategy The four-eyes principle How OTTO Supports Junior Engineers with Continuous Deployment Links and Resources Case Study: N26 N26s Context Adoption of Continuous Deployment at N26 Working Within Industry Regulations Working with Technical Barriers N26s Implementation of Continuous Deployment How N26 Makes Continuous Deployment Safe Test automation Deployment strategy Four-eyes principle Observability How N26 Supports Junior Engineers Links and Resources Case Study: ClimatePartner ClimatePartners Context Adoption of Continuous Deployment at ClimatePartner ClimatePartners Implementation of Continuous Deployment How ClimatePartner Makes Continuous Deployment Safe Test automation Zero downtime Feature toggles Observability Four-eyes principle Testing in production How ClimatePartner Supports Junior Engineers with Continuous Deployment Case Study: Motability Operations Motability Operations Context Adoption of Continuous Deployment at Motability Operations Working with Organizational Barriers Working with technical barriers Motability Operations Implementation of Continuous Deployment How Motability Makes Continuous Deployment Safe Test automation Zero-downtime deployments Continuous code reviews Observability Feature flags Encouraging contributions How Motability Operations Supports Teams Junior engineers Hiring Onboarding Case Study: REA Group REAs Context Adoption of Continuous Deployment at REA Overcoming organizational barriers Overcoming technical barriers REAs Implementation of Continuous Deployment How REA Makes Continuous Deployment Safe Test automation Zero-downtime deployments Code reviews Observability How REA Supports Junior Engineers with Continuous Deployment Case Study: Maze Mazes Context Adoption of Continuous Deployment at Maze Overcoming Organizational Challenges Overcoming Technical Challenges Mazes Implementation of Continuous Deployment How Maze Makes Continuous Deployment Safe How Maze Supports Junior Engineers with Continuous Deployment Case Study: TravelPerk TravelPerks Context Adoption of Continuous Deployment at TravelPerk TravelPerks Implementation of Continuous Deployment How TravelPerk Makes Continuous Deployment Safe Hiding with work in progress Code reviews Automated tests Zero downtime Observability How TravelPerk Onboards Engineers to Continuous Deployment Index