Continuous Delivery 3 0 Maturity Model Nederlands Instituut voor de Software Industrie


A basic delivery pipeline is in place covering all the stages from source control to production. The first stage of maturity in continuous delivery entails extending software build standards to deployment. The team should define some repeatable, managed processes that get code to production.

  1. They’re often named differently from one source to the next, but the core principles of each stage rarely vary too widely.
  2. IT can once again start pushing innovation instead of restraining it by expensive, slow, unpredictable and outdated processes.
  3. Testing illustrates the inherent overlap between continuous integration and continuous delivery; consistency demands that software passes acceptance tests before it is promoted to production.
  4. Thus, developers need the continuous delivery model for running tests and deploying/releasing.
  5. 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.

Continuous Integration

If there are practices you do not want to adopt you need to analyse the consequences of excluding them. It is also important to decide on an implementation strategy, you can e.g. start small using slack in the existing process to improve one thing at a time. However, from our experience you will have a better chance of a successful implementation if you jump start the journey with a dedicated project with a clear mandate and aggressive goals on e.g. reducing cycle time.

DevOps Testing: Strategies, Tools, and More for Successful Evaluations

One of the most popular DevOps maturity models involves five core phases. They’re often named differently from one source to the next, but the core principles of each stage rarely vary too widely. DevOps means taking a data-driven approach to the management of the entire SDLC. So, automation is a critical component because it frees up the team to operate strategically rather than getting bogged down in manual processes. Software developers and the operational teams that support them are under more pressure than ever to deliver higher quality faster. In an increasingly competitive SaaS world, data security issues and downtime present more business risks than ever.

Information & Reporting

Every company is unique and has its own specific challenges when it comes to changing the way things work, like implementing Continuous Delivery. This maturity model will give you a starting point and a base for planning the transformation of the company towards Continuous Delivery. After evaluating your organization according to the model you need to set the goals and identify which practices will give your organization the best outcomes.

Agile Conferences

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to shorten the development lifecycle. For me, perhaps the most interesting effect of continuous delivery is the cost reductions it brings about by reducing the amount of time spent on non-value add activities such as integration and deployment. In continuous delivery, we perform the activities that usually follow “dev complete”, such as integration, testing and deployment (at least to test environments) — continuously, throughout the development process. To address the challenges of this manual process, MLOps practices for CI/CDand CT are helpful.

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. This means no manual testing or verification is needed to pass acceptance but typically the process will still include some exploratory testing that feeds back into automated tests to constantly improve the test coverage and quality. If you correlate test coverage with change traceability you can start practicing risk based testing for better value of manual exploratory testing. At the advanced level some organizations might also start looking at automating performance tests and security scans. Moving to intermediate the level of automation requires you to establish a common information model that standardizes the meaning of concepts and how they are connected. 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.

DevOps maturity also means that processes across software development and all the operational components that support it are efficiently integrated. It allows all arms of the team to work together faster and gain the agility needed to produce quickly and effectively. DevOps maturity is how organizations can assess how far their implementation of a complete continuous delivery maturity model DevOps model has progressed. It involves assessing the implementation of specific DevOps processes and practices and measuring their effectiveness. The most effective improvement processes, whether they streamline manufacturing operations or speed up software development, describe the path to desired improvements — not just the end state.

The goal is to create a trustworthy and automated process that delivers software from the developer to the user. In turn, the programmer, getting rid of almost all the manual work, works more productively. By partnering with a trusted provider like Full Scale, you can harness the power of DevOps and gain access to a team of skilled developers who can help you achieve your business goals. Although it includes novel methods to enhance processes, DevOps hurdles are not entirely unfamiliar. The DevOps Maturity Model is at the heart of this transformative methodology. It’s a powerful framework to assess your current practices, identify areas for improvement, and unlock your team’s full potential.

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 this level reporting is typically done manually and on-demand by individuals.

See how Atlassian’s Site Reliability Engineers do incident management and practice ChatOps for conversation-driven development. To excel in ‘flow’ teams need to make work visible across all teams, limit work in progress, and reduce handoffs to start thinking as a system, not a silo. An optional additional component for level 1 ML pipeline automation is afeature store. A feature store is a centralized repository where youstandardize the definition, storage, and access of features for training andserving. A feature store needs to provide an API for both high-throughput batchserving and low-latency real-time serving for the feature values, and to supportboth training and serving workloads.

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.

MLOps level 0 is common in many businesses that are beginning to apply ML totheir use cases. This manual, data-scientist-driven process might be sufficientwhen models are rarely changed or trained. In practice, models often break whenthey are deployed in the real world. The models fail to adapt to changes in thedynamics of the environment, or changes in the data that describes theenvironment. For more information, seeWhy Machine Learning Models Crash and Burn in Production.

A mature DevOps team can also be more confident in the quality of their product. With automation and streamlined processes, issues are identified and addressed at a much faster rate. This includes bugs in software functionality and wider issues with security threats and system vulnerabilities. Senior developer and architect with experience in operations of large system. Strong believer that Continuous Delivery and DevOps is the natural step in the evolution of Agile and Lean movement.

We see DevOps as a lifecycle with each phase flowing into the other to break down silos and inform key stakeholders along the way. You plan the work, then build it, continuously integrate it, deploy it, finally support the end product and provide feedback back into the system. Amplifying feedback can help you catch failures before they make it downstream, and accelerate your time to resolution. One easy way to speed up feedback is by automating notifications so that teams are alerted to incidents or bugs when they happen.