@crichardson Microservices rules: what good looks like Chris Richardson Founder of Eventuate.io Founder of the original CloudFoundry.com Author of POJOs in Action and Microservices Patterns @crichardson [email protected] http://adopt.microservices.io Copyright © 2024. Chris Richardson Consulting, Inc. All rights reserved July 2024

@crichardson “Our application is ‘****’, it's so complex and so dif fi cult to change” Architect of ancient legacy application Developer of a young microservices application

@crichardson Presentation goal 11 rules that prevent an organization from making a mess of its microservice architecture

@crichardson About Chris http://adopt.microservices.io

@crichardson About Chris https://chrisrichardson.net/

@crichardson Agenda Development rules for fast fl ow A really brief overview of software architecture Rule: use a rational design process Architecture rules Rule: Track and improve software metrics and KPIs

@crichardson The software delivery feedback loop Development Production Changes Feedback Users

@crichardson Traditional software delivery, especially outsourced IT projects Changes Feedback Long Infrequent Occasional e.g. every 1 or 2 years Development Production Feedback Users

@crichardson Volatile Uncertain Complex Ambiguous Building complex applications Often using new, unfamiliar technologies + Infrequent feedback = Risk of building the wrong application, the wrong way

@crichardson Fast fl ow for business succe$$ Development Production Continuous stream of small changes, many times a day Continuous feedback and learning https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/developer-velocity-how-software-excellence-fuels-business-performance Users

@crichardson O VID -19 https://www.ft.com/content/f9356bdc-3102-11ea-a329-0bcf87a328f2 https://www.ft.com/content/3f498e64-1aa6-11ea-97df-cc63de1d73f4 https://techcrunch.com/2019/06/18/the-rise-of-the-gig-economy-helps-london-based-insurtech-zego-to-raise-42m/ The success triangle Process: DevOps/Continuous Delivery & Deployment Organization: Network of small, loosely coupled, product teams IT must continuously deliver a stream of small changes to customers Businesses must be nimble, agile and innovate faster S/W VUCA Architecture: ??? Enables Enables

What is DevOps? Set of principles and practices where developers, testers (dev) and IT operations (ops) collaborate and communicate to deliver software rapidly, frequently, and reliably http://itrevolution.com/devops-handbook Three ways Flow Feedback Learning

@crichardson Rule #1: Practice continuous delivery/deployment The ability to get changes into production safely and quickly in a sustainable way. Code (Git) repository is the source of truth Software is always releasable Developers commit frequently - e.g. daily - to trunk Highly automated https://continuousdelivery.com/

@crichardson Rule #2: Implement a fast deployment pipeline Production Fast, automated deployment pipeline Developer laptop Application repository 15 minutes

Rule #3: Apply Team Topologies: organizing for fast fl ow https://teamtopologies.com/key-concepts Stream-aligned team, e.g. Order Management Team Requirements Develop Test Deploy Code in production Work High trust/psychological safety: Small 5-9 people, long lived Stream-aligned team Platform team Facilitating Collaboration Sometimes Sometimes Enabling Team Platform team API Tools Complicated Subsystem team Stream-aligned team API XaaS Mostly

@crichardson Rule #4: Provide a great DevEx “Developer experience (DevEx) encompasses how developers feel about, think about, and value their work.” Happier developers = more productive developers https://premium.microservices.io/doing-more-with-less-part-1-improving-developer-experience-devex/

@crichardson DevEx framework DevEx Work environment than minimizes interruptions, meaningful work, … Minimize - simplify environment, automate, good documentation, … Fast feedback from colleagues, tools, deployment pipeline, production, users, … Feedback Flow Cognitive load https://queue.acm.org/detail.cfm?id=3595878 Great

@crichardson Agenda Development rules for fast fl ow A really brief overview of software architecture Rule: use a rational design process Architecture rules Rule: Track and improve software metrics and KPIs

@crichardson About software architecture “The software architecture of a computing system is the set of structures needed to reason about the system, which comprise software elements, relations among them, and properties of both.” Documenting Software Architectures, Bass et al Development • Maintainability • Testability • Deployability • … Non-functional requirements Runtime • Scalability • Performance • Availability • … Satis fi es Architecture Focus

@crichardson Architectural requirement: loose coupling Order Management Customer Management Develops Develops Unaffected by changes to the other Conway’s law Loosely coupled = work independently Loosely coupled Degree of design-time coupling = probability of lockstep changes

@crichardson Architectural requirements: testability and deployability Production Automated deployment pipeline >= 1 commit / developer / day Must be fast running Must be reliable Must be testable using automated tests deployment Must be locally testable commit

@crichardson Architecting for DevEx https://queue.acm.org/detail.cfm?id=3595878 Loose coupling Testability Deployability Observability Simplicity

@crichardson Architecture is multi-dimensional https://microservices.io/post/architecture/2024/04/14/architecture-is-multi-dimensional.html Loose design-time coupling Testable Deployable Written by developers Built and tested by deployment pipeline

@crichardson De fi ning components = grouping subdomains ≪subdomain≫ Customer management ≪aggregate≫ Customer ≪subdomain≫ Order management ≪aggregate≫ Order Customer Team Order Team Application Component ≪subdomain≫ ≪subdomain≫ ≪subdomain≫ ≪subdomain≫ How to group subdomains into components? Component Component Deployable, Executable, e.g. WAR fi le, executable JAR, … • Loosely coupled • Testable • Deployable Module, eg. JAR fi le

@crichardson Monolithic architecture: one component Production Fast, automated deployment pipeline Application repository Developer laptop App

@crichardson Microservice architecture: two or more components Production Deployment pipeline Service Repo Deployment pipeline Service Repo Deployment pipeline Service Repo Independently deployable Loosely coupled Svc Svc Svc

@crichardson Which best fi ts your application and organization? #itDepends

@crichardson Agenda Development rules for fast fl ow A really brief overview of software architecture Rule: use a rational design process Architecture rules Rule: Track and improve software metrics and KPIs

@crichardson Architecture = series of design decisions https://premium.microservices.io/a-service-should-exist-to-solve-a-problem/

Understand the context Define the problem Define evaluation criteria Find candidate solutions Evaluate the trade-offs Pick the best solution Document decision 1 2 3 4 5 6 7 Rational decision making Rule #5: use a rational design process Irrational @FamousDev says X is good/bad X looks like a cool, new thing to try X would look good on my resume I’ve used X in my past 5 jobs Magical thinking: we can neglect architecture … https://microservices.io/post/architecture/2023/03/13/better-decision-making-with-patterns.html Requires knowledge Only you know this

@crichardson Grouping subdomains into components: together or separate? ≪subdomain≫ Customer management ≪aggregate≫ Customer ≪subdomain≫ Order management ≪aggregate≫ Order Attraction Repulsion Generated by system operations Simple components Team autonomy Fast deployment pipeline … Dark energy: an anti- gravity that’s accelerating the expansion of the universe Dark matter: an invisible matter that has a gravitational effect on stars and galaxies. https://www.nasa.gov/feature/goddard/2020/new-hubble-data-explains-missing-dark-matter Simple interactions Prefer ACID or BASE Minimize runtime coupling … https://microservices.io/post/architecture/2023/03/26/dark-energy-dark-matter-force-descriptions.html

@crichardson Dark energy forces: reasons to use microservices https://microservices.io/post/architecture/2023/03/26/dark-energy-dark-matter-force-descriptions.html Service Service «Subdomain» A «Aggregate» X «Subdomain» B «Aggregate» Y Simple components Team autonomy Fast deployment pipeline Support multiple technology stacks Segregate by characteristics Repulsive dark energy forces Characteristics: • Resource requirements • Regulations, e.g. SaMD/PCI • Business criticality/tier • Security, e.g. PII, … • DDD core/supporting/generic • ...

@crichardson But your context determines relevance of dark energy forces to you Force: reason to use microservices What determine relevance to your application Team autonomy ∝Number of teams Fast deployment pipeline Build time ∝ size/complexity of app Build frequency ∝ rate of Git pushes Multiple technology stacks Need multiple technologies? Segregate by characteristics Business criticality Have high availability subdomains? Regulations Regulated subdomains? …

@crichardson IF you have this DevEx… Large monolith • High cognitive load • Less autonomy • More meetings • Slow feedback Single classpath, Large code base, Slow deployment pipeline, … Simple (e.g. ACID txns) development BUT You

@crichardson …THEN adopt microservices to have this DevEx Service Small part of a large application Service … Service … Service … collaborators A P I • Less cognitive load • More autonomy incl. technical • Less meetings • Faster feedback You A P I A P I A P I Service … Service … clients

How many services? MICROservices != little services Excessively fi ne-grained, overly complex architectures are far too common A service should exist to solve a tangible problem https://microservices.io/post/antipatterns/2019/05/21/antipattern-more-the-merrier.html https://premium.microservices.io/a-service-should-exist-to-solve-a-problem/

@crichardson Fine-grained architecture: risk of poor DevEx Right-sized Service A P I Fine- grained Service API Good ✅ Bad ❌ Focus on collaboration logic Focus on domain logic

@crichardson Dark matter forces: reasons NOT to distribute subdomains https://microservices.io/post/architecture/2023/03/26/dark-energy-dark-matter-force-descriptions.html Subdomain A «Aggregate» X Subdomain B «Aggregate» Y Service A Service B Simple interactions Efficient interactions Prefer ACID over BASE Minimize runtime coupling Minimize design time coupling Attractive dark matter forces SystemOperation() Generates Risk of higher cognitive load Requires stable domain

@crichardson Designing an architecture = making trade-offs Con fl icting forces Therefore Some services/ operations will have an optimal design Others will be suboptimal but good enough Subdomain A «Aggregate» X Subdomain B «Aggregate» Y Service A Service B Attraction Simple, efficient interactions Prefer ACID over BASE Minimize runtime coupling Minimize design time coupling Simple components Team autonomy Fast deployment pipeline Support multiple technology stacks Segregate by characteristics Repulsion Dark energy Dark matter Metaphor for Metaphor for Fine-grained services Monolith

@crichardson Assemblage: an architecture de fi nition process that’s powered by dark energy and dark matter* https://microservices.io/post/architecture/2023/02/09/assemblage-architecture-de fi nition-process.html Subdomain A «Aggregate» X Subdomain B «Aggregate» Y Service A Service B Dark energy Dark matter * metaphor overload

@crichardson Agenda Development rules for fast fl ow A really brief overview of software architecture Rule: use a rational design process Architecture rules Rule: Track and improve software metrics and KPIs

@crichardson Architecture rules #6 Design loosely coupled services #7 Design independently deployable services #8 Design testable services #9 Develop observable services #10: Big/risky change => smaller/safer changes De fi ning characteristics of microservices

Rule #6: Design loosely (design-time*) coupled services * vs runtime and build-time coupling https://microservices.io/post/architecture/2023/03/28/microservice-architecture-essentials-loose-coupling.html Customer Service Customer Subdomain Order Service Order Subdomain API Stable Infrequent lock step changes

The problem with tight design- time coupling Changing services in lock step reduces productivity: API changes/evolution Complexity of non-atomic changes of independently deployable services Coordination between teams Worst case: distributed monolith! Therefore: Tightly coupled subdomains should be packaged together Order Service Customer Subdomain Order Subdomain Package together

Design iceberg services Implementation DB API Small, stable API Large, complex implementation Change https://microservices.io/post/architecture/2023/03/01/geometry-of-microservices.html

@crichardson Rule #7: design independently deployable services https://microservices.io/post/architecture/2022/05/04/microservice-architecture-essentials-deployability.html Production Order Service Order Service Deployment pipeline Test in isolation Test Service Test Double Service Sole criteria for release Includes contract- testing to enforce API interoperability Deploy automatically

@crichardson Why independently deployable services? De fi ning characteristic of the microservice architecture Testing a service in isolation Simpler testing set up using test doubles Fast Reliable Testing services together = distributed monolith = downsides of both with few of the bene fi ts By de fi nition: the output of a deployment pipeline is deployable

@crichardson Rule #8: Design testable services Automated - tests must be automated Fast - tests must execute quickly to provide fast feedback Reliable - tests must not be fl aky: failing test = real problem Locally executable - tests must run on a developer's laptop to provide fast feedback. Isolated - tests must use test doubles for the service's dependencies

@crichardson Rule #9: develop observable services Key Health check invoker, e.g. monitoring service Invokes Observable Service Health Check API Health Check API pattern Log file Logging server Log aggregation pattern Exception Reporter Exception Tracking Service Exception Tracking pattern Audit Database Adapter Audit Logging pattern Metrics Exporter Metrics service Application Metrics pattern Distributed Tracing Exporter Distributed tracing server Distributed tracing pattern Logging Aggregation Pipeline Logging Adapter Pattern Developer responsibility Operations responsibility Auditing Database Pattern Participant

Why observable services? (Fast) feedback is a foundation of DevEx and DevOps Quickly detect, diagnose and fi x production issues http://itrevolution.com/devops-handbook Flow Feedback Learning

@crichardson Rule #10: Big/risky change* => smaller/safer changes * Architecture changes, migrations

@crichardson Example: Incrementally migrate from a monolith to microservices Monolith Time Monolith Service Monolith Service Service Monolith Service Service Service Service …. Monolith Service Service Service Service Service Service Service Service Service Service Service Service Service Service Service Service …. Strangler application The strangler application grows larger over time The monolith shrinks over time Service Service Service Service Service Service Service Service New features

Why is the Strangler Fig application pattern better than a big bang rewrite? Acknowledges that modernization is a process of discovery Immediate bene fi t from services Enables agility Early and continuous feedback and learning https://microservices.io/post/refactoring/2023/06/21/strangler- fi g-application-pattern-incremental-modernization-to-services.md.html

@crichardson Agenda Development rules for fast fl ow A really brief overview of software architecture Rule: use a rational design process Architecture rules Rule: Track and improve software metrics and KPIs

@crichardson DORA metrics: measuring performance https://dora.dev/ Metric Description Elite performance Deployment frequency How frequently changes are pushed to production Each commit Lead time Time from commit to deploy < 1 hour Change failure rate How frequently a change breaks production Very low Time to restore service How long to recover from a failed deployment Very short Move fast, don’t break things

@crichardson Assess DevEx https://queue.acm.org/detail.cfm?id=3595878

@crichardson Capture architecture metrics Key focus: design-time coupling between services Predict from design metrics Analyze inbound/outbound dependencies Observe actual issues Commits for multiple services for the same JIRA issue Frequency of breaking API changes

Organizational KPIs Software delivery performance impacts business success THEREFORE: Every leader including CxOs should pay attention Category KPI Delivery Lead time Deployment frequency DevEx Perceived ease of delivery Perceived productivity Architecture Degree of loose design-time coupling

Summary: microservices rules Development rules for fast fl ow Continuously deliver/deploy Implement fast, automated deployment pipelines Organize into small, autonomous, loose-coupled teams Provide a great developer experience (DevEx) Architecture rules Design independently deployable services Design loosely coupled services Design testable services Develop observable services Big/risky change => smaller/ safer changes Rule: Track and improve software metrics and KPIs Rule: Use a rational design process

@crichardson @crichardson [email protected] http://adopt.microservices.io Questions?