A Maturity Model for Continuous Delivery

Here is an interesting rough systematization in a table view of Continuous Delivery process. It is composed by Sveinung Dalatun and Stein Inge Morisbak employees of a Norwegian company named Bekk. They called this table A Maturity Model for Continuous Delivery. This model was published once in a Norwegian paper magazine called “The Developer” number 3 year 2013. There is a short description-article following the Model published in The Developer. The are Some quite interesting thoughts there.

1. While implementing Continuous Delivery we need to priorities.
It is important to focus on our efforts on the greatest bottlenecks in our delivery process. Yo identify this bottleneck it can be helpful to visualize our value stream and focus our attention on the steps that are most error prone or slow.

2. We should try to keep the overall maturity level fairly even as most categories at the same level either depend on or complement each other.

3. We should not skip levels or try to implement them all at once. As in any other agile approach we should introduce changes in an incremental and iterative way.

4. Silo organisations are bad.
Business silos, just like agricultural silos hold something important and make it hard to get at. That’s good when you’re protecting wheat and corn from rain & snow. But it’s bad when you’re trying to innovate across departments and divisions.
Silos causes ineffective handsoffs, less insight in the whole, misunderstandings. No one can get their work done before others have completed theirs. Since the silos “own” the stuff they are in charge of, the don’t let others touch it.

5. Technology components stack.
When stack is put together in a “loose” fashion it is easy to replace one part with another when something better comes along.

6. Builtin quality assurance.
To be able to shorten delivery time we have to ensure that quality assurance is built into continues delivery process itself in an automated way. Handing you code over to a test department or spending two days of testing each time you release becomes impossible.

7. Deployment automation.
Nothing has any value unless it’s in production.
Automate both deploy and roll-back.
Deploy without downtime.

Process & Organisation Technology Quality assurance Deployment routines Configuration management Build & CI
Advanced Self organised and cross functional.

The team can solve any task.

Releases continuously.

Continuous improvement.

DevOps!

Loosely coupled architecture.

It is easy to replace technology for the benefit of something better (Branch by abstraction).

All testing automated.

Almost all testing is automated, also for non-functional requirements.

Testing of infrastructure code.

Health monitoring for applications and environments and proactive handling of problems.

One-click deploy.

Everybody (including the customer) can deploy with one click.

0-downtime deploy.

Feedback on database performance and deployment for each release.

Infrastructure as code.

Fully automated provisioning and validation of environments.

Orchestration of environments.

Build/deploy pipeline.

Same binary is deployed to all environments.

Continuous improvement and automation of repeating tasks.

Optimised for rapid feedback and visualisation of integration problems.

Intermediate Pull-based process.

Measurement and reduction of cycle time.

Continuous focus on process improvement.

Always production ready code.

Simple technology.

In depth knowledge about each technology; why it is used and how it works.

All of the used technologies are easy to configure and script against.

Technology that makes it simple to roll back and forth between database versions.

Automated functional tests.

Automated acceptance- and system tests.

Tests are written as part of requirements specification.

All stakeholders specify tests.

Automated deploy.

Same process for deploy to all environments.

Feature toggling to switch on/off functionality in production.

Release and rollback is tested.

Database migration and rollback is automated and tested for each deploy.

Database performance is monitored and optimised.

Application configuration control.

All application configuration in version control.

The application is configured in one place.

Continuous integration

Continuous integration of source code to mainline.

All changes (code, configuration, environments, etc.) triggers the feedback mechanisms.

Artifact repository.

Reuse of scripts and tools.

Generation of reports for the build.

Builds that fail are fixed immidiately.

Baseline Agile 101.

Improved communication with business.

Releases after each iteration.

Developers have access to production logs.

Best-of-breed.

Chooses technology stack based on what is best for each purpose.

Chooses preferably Open Source.

Avoids products that causes vendor lock-in.

Automated technical tests.

Automated unit- and integration tests.

Repeatable deploy.

Documented and partially automated deploy.

Database changes are scripted and versioned.

Dependency control.

Dependencies and libraries are defined in version control.

CI-server

Automation of builds/tests on CI server.

Can recreate builds from source code.

Big challenges Silo organisation.

People who in some way depend on each others work are not sitting together.

Infrequent releases.

Developers do not have access to production logs.

“Enterprise” infrastructure.

Technology that can only be configured via a GUI.

Large “enterprise” suites claiming they can solve all your problems.

Manual testing.

Test department.

Testing towards the end, not continuously.

Developers do not test.

Manual deploy.

Deployments require many manual steps.

Manual and unversioned database migrations.

Manual configuration.

Manual configuration in each environment and on each server.

Manual routines

Manual routines for builds.

Lack of artifact repository.

Lack of reports.