microservices adoption   anti-patterns   software delivery metrics  

Anti-pattern: microservices as the goal

In a previous post, I described the Microservices are a magic pixie dust anti-pattern. Another anti-pattern that I’ve observed is an organization making the adoption of microservices the goal. An executive might, for example, announce a microservices transformation initiative and expect every development team to “do microservices”. Development teams then scramble to “do microservices”. Perhaps, a team’s annual or quarterly bonus is affected by how well they “do microservices”. In an extreme case, it might be depend on how many microservices they have deployed.

Consequences

On the one hand, adopting microservices is a major undertaking and high-level support is essential. But on the other hand, the problem with making microservices the goal is that it ignores other obstacles to rapid, frequent and reliable software delivery including:

  • Inefficient processes and practices - waterfall process, manual testing, manual deployment
  • Silo’d organization - e.g. development hands off code to QA for testing.
  • Poor software quality - the application is a big ball of mud, the code is anything but clean, etc.

An organization that suffers from these problems might not benefit from adopting microservices. It might even make things worse. Also, requiring a team to adoption microservices, risk imposing an architecture on a development team even when it does not make sense for their application.

A better approach

A much better goal is to increase the velocity, frequency and reliability of software delivery. Specific, there are four key metrics to track and improve:

  • Lead time - time from commit to deploy
  • Deployment frequency - number of deploys per day per developer
  • Failure rate - how often deployments fail
  • Recovery time - time to recover from an outage

Each application development team is then responsible for improving these metrics for their application. Sometimes the microservice architecture plays a key role in improving this metrics. But there are other things that can be done to improve these metrics. For example,

  • Increasing lead time - eliminate wasteful work, automation, etc.
  • Increasing deployment frequency - automated testing and deployment, etc
  • Reducing failure rate - automated testing, automated deployment, GitOps, etc.
  • Reducing recovery time - improved monitoring, automating recovery, etc.

To learn more


microservices adoption   anti-patterns   software delivery metrics  


Copyright © 2023 Chris Richardson • All rights reserved • Supported by Kong.

About Microservices.io

Microservices.io is brought to you by Chris Richardson. Experienced software architect, author of POJOs in Action, the creator of the original CloudFoundry.com, and the author of Microservices patterns.

Chris helps clients around the world adopt the microservice architecture through consulting engagements, and training workshops.

Learn how to create a service template and microservice chassis

Take a look at my Manning LiveProject that teaches you how to develop a service template and microservice chassis.

New virtual bootcamp: Distributed data patterns in a microservice architecture

My virtual bootcamp, distributed data patterns in a microservice architecture, is now open for enrollment!

It covers the key distributed data management patterns including Saga, API Composition, and CQRS.

It consists of video lectures, code labs, and a weekly ask-me-anything video conference repeated in multiple timezones.

The regular price is $395/person but use coupon JUNVCEJE to sign up for $195 (valid until February 1st, 2023). There are deeper discounts for buying multiple seats.

Learn more

Signup for the newsletter


LEARN about microservices

Chris offers numerous resources for learning the microservice architecture.

Training classes

Chris teaches comprehensive workshops, training classes and bootcamps for executives, architects and developers to help your organization use microservices effectively.

Avoid the pitfalls of adopting microservices and learn essential topics, such as service decomposition and design and how to refactor a monolith to microservices.

Delivered in-person and remotely.


Get the book: Microservices Patterns

Read Chris Richardson's book:

Example microservices applications

Want to see an example? Check out Chris Richardson's example applications. See code

BUILD microservices

Ready to start using the microservice architecture?

Consulting services

Engage Chris to create a microservices adoption roadmap and help you define your microservice architecture,


The Eventuate platform

Use the Eventuate.io platform to tackle distributed data management challenges in your microservices architecture.

Eventuate is Chris's latest startup. It makes it easy to use the Saga pattern to manage transactions and the CQRS pattern to implement queries.

ASSESS your architecture

Assess your application's microservice architecture and identify what needs to be improved.

Consulting services

Engage Chris to conduct an architectural assessment.



Join the microservices google group

Topics

Note: tagging is work-in-process

anti-patterns   ·  application api   ·  application architecture   ·  architecting   ·  architecture documentation   ·  dark energy and dark matter   ·  deployment   ·  development   ·  devops   ·  docker   ·  implementing commands   ·  implementing queries   ·  inter-service communication   ·  loose coupling   ·  microservice architecture   ·  microservice chassis   ·  microservices adoption   ·  microservicesio updates   ·  multi-architecture docker images   ·  observability   ·  pattern   ·  refactoring to microservices   ·  resilience   ·  sagas   ·  security   ·  service api   ·  service collaboration   ·  service design   ·  service discovery   ·  service granularity   ·  service template   ·  software delivery metrics   ·  success triangle   ·  team topologies   ·  transaction management   ·  transactional messaging

All content


Posts

24 Jul 2017 » Revised data patterns