Architecting systems for continuous delivery 7/17/2018 6:32 AM Architecting systems for continuous delivery Marcel de Vries CTO, Xpirit © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Agenda Architectural concepts to solve bottlenecks Smaller shippable units Decreasing hard coupling between (sub) systems Enabling zero downtime deployments Different thinking around releases Different thinking around testing Further reading

Current Architectural Challenges of CD All software components need to be delivered as one cohesive set Partial updates not possible Better known as the monolith All changes are in one huge code repository Long lived branches, merge hell Test process takes 2 months to verify regression and new features We are forced to use technology and tools that don’t fit our needs

Smaller shippable units What is the architecture of your system? Monolith SOA ?

Monolith Dependencies Deployment strategy Scaling strategy Monitoring All software is tightly coupled. Most often the system is build in the same software technology (e.g. .NET with C#) Often one database with strong schema dependency Deployment strategy De-install, upgrade/migrate DB Schema, Install new version System will be unavailable during deployment Takes hours to complete Scaling strategy Scale up and out Monitoring Based on home grown monitoring tools

SOA Dependencies Deployment strategy Software can be in multiple technologies, communication via a Service Bus Strong dependency on message schema’s Strong dependency of services on Middleware technology Deployment strategy Per service De-install, upgrade/migrate DB Schema, Install new version System will be unavailable during deployment Takes hours to complete & coordinated effort Upgrades of ESB also requires coordinated effort

Which Service owns this page?

None!

Composition is key!

Microservices architecture

Decreasing hard coupling between (sub) systems Coincidental cohesion (worst) random Logical cohesion same in nature Temporal cohesion executed at a particular time Procedural cohesion part of fixed execution sequence Informational cohesion operating on the same data Sequential cohesion Output of one is used as input by another Functional cohesion (best) contributing to a single task

Defining Microservices Finding Autonomous Business Capabilities Low Coupling Components are completely insensitive to changes and errors in other components. No Coupling Error and changes seldom propagate errors and changes to dependent components Low Coupling Errors and changes in one component almost always propagate to other components High Coupling

Bounded contexts

Using events to decouple services Systems keep their own state Events are used to notify changes Systems use events to replicate data Each service will have it’s own data store Downsides: Latency in data changes No central control of business logic Challenge to reconcile in case of disaster

Cross-service coupling Smart endpoints, dumb pipes No intelligent middleware Technologies to look at: Queues (Azure, MSMQ, WebSphereMQ , ...) Service Bus (NServiceBus, Azure ServiceBus, ...) Language neutral data serialization (Google Protocol buffers, Apache Thrift)

Zero downtime deployments

Circuit Breaker Pattern Handle faults that may take a variable amount of time to rectify when connecting remote service or resource. This pattern can improve the stability and resiliency of an application.

Retry Pattern Enable an application to handle temporary failures when connecting to a service or network resource by transparently retrying the operation in the expectation that the failure is transient. This pattern can improve the stability of the application.

Reset your defaults

Classical Approach Automated Testing Unit testing Integration testing Manual testing CD tells us: Automate everything…. Move to more automation Manual testing -> Use of UI Automation tools

“There is no place like Production” Source: Brian Harry, Microsoft Technical Fellow

Choosing the right scale unit is crucial Testing in production SU1 SU2 SU3 Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Choosing the right scale unit is crucial to enable this concept Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Feature Customer segment A <1000 Customer segment B <10000 Customer segment C All other

Recap Decompose your system in more independent deployable units ABC’s Strive for functional Cohesion Adapt event driven style of communication Make services failure resilient Rethink the way systems are tested and implications on your systems architecture MSA is not the goal, it’s a means and you will pay a premium to get it in place!

Further reading Microservice architecture, Sam Newman Domain Driven Design, Eric Evans Microservices, Martin Fowler Continuous Delivery. Jez Humble Xpirit magazine

Xpirit mdevries@xpirit.com Fluentbytes.com @marcelv 7/17/2018 6:32 AM Xpirit All Photos used in this presentation come from unsplash.com mdevries@xpirit.com Fluentbytes.com @marcelv © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Xpirit xpir.it/XpiritMagazine mdevries@xpirit.com Fluentbytes.com Building a CD pipeline with VS 2015 Test Automation with CodedUI Testing Web Applications with CodedUI Introduction to Docker on Windows with Visual Studio 2017 All Photos used in this presentation come from unsplash.com mdevries@xpirit.com Fluentbytes.com @marcelv

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7/17/2018 6:32 AM © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.