Continuous Delivery Pipeline: A Gentle Introduction

Continuous Delivery Pipeline: A Gentle Introduction

You may streamline your software distribution with the help of a continuous integration/continuous delivery pipeline. A new version of the application is built, tested (through continuous integration), and then safely deployed through the Continuous Delivery pipeline.

Automated pipelines facilitate rapid iteration of products by removing human error, standardizing developer feedback loops, and eliminating unnecessary steps.

What is a Continuous Delivery Pipeline?

CI, which stands for “Continuous Integration,” is a technique used in software development in which changes to the codebase are merged several times daily by all developers. CD refers to the practice of fully automating the software release process, which builds on Continuous Integration.

Continuous Integration (CI) is a software development methodology in which any code change results in an immediate automatic build and test sequence for the associated project, with the results of which the developer(s) involved receive immediate feedback.

Infrastructure provisioning and deployment are part of the Continuous Delivery Pipeline, and they might be manual and involve numerous steps. It’s crucial that all of these steps are automated, with each execution being logged and made available to the entire team.

Components of Continuous Integration and Continuous Deployment

Although a CI/CD pipeline may seem unnecessary, that is not the case. In essence, it is an executable specification of the activities required by any developer working on the delivery of a new version of a software product. Engineers would still need to conduct these processes manually, but their output would be much lower without an automated pipeline.

There are a few standard phases that apply to the majority of software releases:

When a stage fails, the concerned developers are often notified immediately (by email, Slack, etc.). The rest of the crew is informed following each successful release to production.

Root Cause Analysis

The majority of the time, a pipeline is kicked off by a code repository. When code is modified, the CI/CD tool is alerted and the appropriate pipeline is executed. Workflows initiated by the user or on a predetermined timetable are another typical source of activation, as are the outputs of other pipelines.

Phase of Construction

By bringing together the code and all of its prerequisites, we create a version of our product that can be deployed and shipped to customers. A program written in Java, C/C++, or Go must be compiled before it can be run, whereas programs written in Ruby, Python, or JavaScript do not require compilation.

This stage of the CI/ Continuous Delivery pipeline creates the Docker containers necessary for deploying cloud-native software in any language.

When a project is unable to complete the build phase, it is an indication that there is a serious issue with the configuration of the project that needs to be fixed quickly.

Preliminary Examination

At this stage, we put our code through its paces by means of automated tests, which ensure its correctness and the correctness of the product’s behavior. The testing phase is a failsafe that keeps bugs that are simple to reproduce from reaching the general public.

Developers are tasked with the task of creating tests. The optimal practice for creating automated tests is to do it in tandem with developing new code, a process known as a test or behavior driven development.

This stage can run anywhere from a few seconds to several hours, depending on how big and complicated the project is. The testing phases of many large-scale projects consist of both unit tests and integration tests, with the latter focusing on the user experience. As a general rule, the execution time of a comprehensive set of tests can be cut in half by parallelizing them.

The failure of the testing phase reveals bugs in the code that the developers did not anticipate. During this phase, developers need to be able to get feedback rapidly so that they can keep their brains in the zone and solve the problem at hand.

Set up in waves

Now that we have a fully tested, deployable version of our code, we can move forward with its release. There are typically a number of environments in which a product may be deployed, including a “beta” or “staging” environment for internal usage by the product team and a “production” environment for actual end users.

Teams who have adopted the Agile development methodology often deploy work-in-progress manually to a staging environment for extra manual testing and review, and automatically deploy accepted changes from the master branch to production.

Cases of Continuous Integration and Continuous Deployment Systems

A project’s complexity is mirrored in its pipeline. Setting up even a basic pipeline with a single job that triggers every code change will alleviate a lot of stress for a team.

It’s simple to add new sequential or parallel work blocks to an existing pipeline on Semaphore. Manually or automatically based on bespoke conditions, promotions can be used to further expand pipelines.

An example pipeline for a basic program

Even a basic process can become a pipeline. The following is a sample pipeline for a Go project:

• Invokes compilation,
• Verifies the format of the source code

Dual-job simultaneous processing of automated tests:

• Combining Docker and Kubernetes for a CD pipeline

The use of Docker complicates CI/CD pipelines since each code build requires the creation and upload of a sizable container image. For many groups, the advantages of consistent deployment and simple developer onboarding are worth the effort.

A build, test, and deployment workflow for a microservice on a Kubernetes cluster:

If developers use Semaphore’s private Docker registry (included in the Enterprise Cloud plan), they can greatly improve the speed of their pipelines by eliminating the need to communicate with an external cloud registry at every stage of the pipeline’s continuous integration and continuous delivery process.

Integration and Continuous Delivery Pipeline for a Single Repository

When you’re working on multiple projects at once, it’s helpful to keep them all in one central location, or “monorepo.” There may be some connections between the projects, but in practice, they are usually handled by different groups.

In practice, it can be difficult to perform CI/CD with a single repository. Each commit would automatically trigger a pipeline to build, test, and release all of the projects in the monorepo. This would be a waste of time and money and a potential safety hazard.

One more way in which pipelines assist society

• Having a CI/ Continuous Delivery Pipeline does more good than just making an existing process slightly more efficient:
• This means that developers can keep their attention on writing code and watching how it operates in production without having to worry about anything else.
• All working versions of the system are easily accessible to those responsible for quality assurance and product development.
• Bringing out new versions of a product is not a source of anxiety.
• Anytime, anywhere access to logs of all code modifications, tests, and deployments.
• Reverting to a previous build in the event of an issue is as simple as clicking a button.
• A culture of learning and accountability can flourish in an organization with a quick feedback loop.

What are the Qualities of an Effective Pipeline?

Rapidity, consistency, and precision are the hallmarks of an excellent CI/Continuous Delivery pipeline.

• Speed

Rapidity can take many forms:

To what extent do we learn whether or not our work is correct, and how quickly? Code pushes to CI are the equivalent of asking a developer to join a meeting while they’re in the middle of solving an issue if they take longer than it takes to get a cup of coffee. There will be an inevitable decrease in productivity among developers as a result of the context shifts.

How long does it take to build, test, and deploy a single code commit? With a one-hour CI/deployment cycle, for instance, the engineering team can only do a maximum of seven deploys per day. As a result, rather than the quick change that businesses need, developers choose less frequent and more dangerous deployments.

Question: “Do our continuous integration/ continuous delivery pipelines scalable to meet development demands in real-time?” The number of pipelines that can be active at once is traditionally low with CI/CD pipelines. Devs have to wait in line for CI/CD to become accessible during peak times of the day, while resources remain idle for the majority of the time. Semaphore 2.0’s “serverless” operating philosophy and pay-as-you-go pricing model are two major new features that increase developer efficiency.

We need to know:

• How quickly can we install a new pipeline? Having trouble expanding your CI/CD infrastructure or reusing your current setup is a major source of friction that slows down your development. Writing software as a collection of microservices is the most effective way to take use of today’s cloud architecture, but this approach necessitates the frequent launch of new continuous integration and continuous delivery pipelines. Having a programmable CI/CD tool that integrates with current development workflows and stores all CI/CD configurations as code that can be reviewed, versioned, and restored is the solution.

• Why high-velocity continuous integration and delivery is critical to the success of cloud-native applications.

Reliability

No of the input, the output from a dependable pipeline remains constant throughout time. Developers are very irritated when failures occur intermittently.

Maintaining and expanding a CI/CD infrastructure that can supply a growing team with clean, identical, and isolated resources on demand is a difficult task. What works effectively for a single project or a small group of developers sometimes falls apart as the team size, the number of projects, or the underlying technology landscape expands or evolves. New users typically come to Semaphore from a self-hosted CI/CD solution, and one of the most common complaints we hear is how unstable the former solution is.

Accuracy

A shift toward automation of any kind is welcome. While the CI/CD pipeline accurately runs and visualizes the entire software delivery process, additional work remains. For this reason, it’s important to use a CI/CD solution that can model both simple and complicated workflows, making it nearly difficult for human error to creep into routine operations.

For instance, it is typical practice to automate the CI stage but keep deployment as a human operation, usually conducted by a single person on the team. This barrier can be eliminated if a CI/CD tool can simulate the deployment sequence required, perhaps through the use of secrets and multi-stage promotions.

In order to ensure consistency, it is recommended to utilize the same setting consistently. Once the environment for the subsequent pipeline run has been altered, the integrity of the CI/CD pipeline is compromised. Each process should initiate from a pristine, secure setting.

Integrated testing for reliability. For instance, every major programming language has free and open-source tools that perform static code analysis, such as reviewing code for style and vulnerabilities. By integrating these tools into your CI/CD workflow, you can devote more time and energy to strategic problem-solving.

Incorporate code-editing requests. A continuous integration and deployment pipeline need not be restricted to just one or two branches. A contributor can find problems before it goes through peer review, or even before it is integrated with the master branch, by running the standard set of tests against every branch and pull request. As a result of this method, merging pull requests is no longer noteworthy.

Every pull request needs to be reviewed by other developers. New code still needs to be reviewed, and a CI/CD pipeline can’t do that by itself. It’s better to establish the norm that every pull request requires another pair of eyes and make exceptions only when it makes sense than the other way around when the change is so minor that peer review is a waste of time. A strong and ego-less engineering culture of collaborative problem-solving is built on the foundation of peer code review.

Conclusion

We believe that the purpose of the life cycle of a software project is to get software into the hands of target users and clients as soon as possible. We also believe that the sooner you can get feedback from users, the sooner you can improve the software to meet the needs of those users. In order to do that, you need to be able to quickly deploy your project to production and have it running with real data as quickly as possible. In this blog, we’re going to talk about how we do that at Enteros.

About Enteros

​Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of RDBMS, NoSQL, and machine learning database platforms.