Climb the five steps of a continuous delivery maturity model

Continuous Delivery 3.0 Maturity Model (CD3M) is a framework for assessing an organization’s maturity in implementing continuous delivery practices, created by the Netherlands National Institute for the Software Industry (NISI). It was created in light of recent trends and best practices in software development, such as cloud native and DevOps. Containers are a common runtime destination for CI/CD pipelines, and if they’re in use at this first stage of the continuous delivery maturity model, development teams have usually adopted Docker images defined by a Dockerfile.

Setting
up a CI/CD system enables you to automatically test and deploy new pipeline
implementations. This system lets you cope with rapid changes in your data and
business environment. You don’t http://cofepublic.net/?rz=kp have to immediately move all of your processes
from one level to another. You can gradually implement these practices to help
improve the automation of your ML system development and production.

Maturity model

When this model is established not only can you automate build, test and deployment even further but you can also build in traceability and information transparency to the pipeline and e.g. automatically generate information like release notes and test plans. Automatic reporting and feedback on events is implemented and at this level it will also become natural to store historical reports connected to e.g. builds or other events. This gives management crucial information to make good decisions on how to adjust the process and optimize for e.g. flow and capacity. At this level the work with modularization will evolve into identifying and breaking out modules into components that are self-contained and separately deployed. At this stage it will also be natural to start migrating scattered and ad-hoc managed application and runtime configuration into version control and treat it as part of the application just like any other code. The level of automation of these steps defines the maturity of the ML process,
which reflects the velocity of training new models given new data or training
new models given new
implementations.

An optional additional component for level 1 ML pipeline automation is a
feature store. A feature store is a centralized repository where you
standardize the definition, storage, and access of features for training and
serving. A feature store needs to provide an API for both high-throughput batch
serving and low-latency real-time serving for the feature values, and to support
both training and serving workloads. The engineering team might have their own complex setup for API configuration,
testing, and deployment, including security, regression, and load and canary
testing. In addition, production deployment of a new version of an ML model
usually goes through A/B testing or online experiments before the model is
promoted to serve all the prediction request traffic.

Similar to Continuous Delivery Maturity Model

DevOps teams need to learn more advanced techniques and tools while they master the basics. Therefore, start by defining a basic CD process and developing some simple scripts, but simultaneously research, learn and test more complicated processes and advanced tools. Advanced practices include fully automatic acceptance tests and maybe also generating structured acceptance criteria directly from requirements with e.g. specification by example and domains specific languages.

• So, if the entire CD process can launch with one command, why are there still two higher levels of CD maturity?
• If you manage many ML pipelines in production, you need
  a CI/CD setup to automate the build, test, and deployment of ML pipelines.
• Testing illustrates the inherent overlap between continuous integration and continuous delivery; consistency demands that software passes acceptance tests before it is promoted to production.
• Software teams are left scrambling to understand their software supply chain and discover the root cause of failures.

Tobias is currently implementing Continuous Delivery projects at several customers. The principles and methods of Continuous Delivery are rapidly gaining recognition as a successful strategy for true business agility. ” How do you start with Continuous Delivery, and how do you transform your organization to ensure sustainable results. This Maturity Model aims to give structure and understanding to some of the key aspects you need to consider when adopting Continuous Delivery in your organization. This section discusses the components that you need to add to the architecture
to enable ML continuous training. An ML system is a software system, so similar practices apply to help guarantee
that you can reliably build and operate ML systems at scale.

Stage 5: DevOps experts optimize CD

At this stage in the model, the participants might be in a DevOps team, or simply developers and IT operations collaborating on a joint project. TESTING 
Automatically testing newly developed features to avoid tedious work. FOUNDATION
Developing on a CD 3.0 platform, but the cycle is poorly automated. The organization and it’s culture are probably the most important aspects to consider when aiming to create a sustainable Continuous Delivery environment that takes advantage of all the resulting effects.

IT can once again start pushing innovation instead of restraining it by expensive, slow, unpredictable and outdated processes. There are many ways to enter this new era and here we will describe a structured approach to attaining the best results. While agile methodologies often are described to best grow from inside the organization we have found that this approach also has limitations. Some parts of the organization are not mature enough to adapt and consequently inhibit development, creating organizational boundaries that can be very hard to break down. The best way to include the whole organization in the change is to establish a solid platform with some important prerequisites that will enable the organization to evolve in the right direction. This platform includes adopting specific tools, principles, methods and practices that we have organized into five key categories, Culture & Organization, Design & Architecture, Build & Deploy, Test & Versification and Information & Reporting.

A maturity model describes milestones on the path of improvement for a particular type of process. In the IT world, the best known of these is the capability maturity model (CMM), a five-level evolutionary path of increasingly organized and systematically more mature software development processes. At the base stage in the maturity model a development team or organization will typically practice unit-testing and have one or more dedicated test environments separate from local development machines. This system and integration level testing is typically done by a separate department that conducts long and cumbersome test periods after development “code freeze”. At beginner level, the monolithic structure of the system is addressed by splitting the system into modules. Modules give a better structure for development, build and deployment but are typically not individually releasable like components.