Each part of CI/CD (Continuous Integration and Continuous Delivery) represents different goals and disciplines that need to be achieved. And to muddy the waters even more, there's Continuous Delivery and Continuous Deployment, which again have two distinct goals.
There seems to be no shortage of “consistent” terms in the DevOps world. Just like Kleenex for tissues or Coca-Cola for soft drinks, "CI/CD" is a common eponym to describe your entire software delivery pipeline. However, each part of CI/CD (Continuous Integration and Continuous Delivery) represents different goals and disciplines that need to be achieved. And to muddy the waters even more, there's Continuous Delivery and Continuous Deployment, which again have two distinct goals.
Publications that were once quarterly now appear with the advent of sillyagile developmentto get incremental features as fast as possible. The infrastructure and procedures must be in place to allow changes to propagate quickly. As with any technology, don't let the semantics get in the way, but the tools and practices for each technology are aligned differently. Regardless of the continuous journey you are on, automation is key to achieving the goals of each continuous pillar to reduce human intervention.
What is the difference between Continuous Integration, Continuous Deployment and Continuous Delivery?
The entire goal of the software delivery pipeline is to get your ideas into production. As altruistic as it sounds, there are certainly many steps to doing it. For a software developer, your external customers don't care how you delivered something once they have access to the feature. Comparing this vibe to a DevOps engineer, their internal customers (development teams) care about how something is deployed, as this process directly affects them and feature deployment.
Starting with a code change or new code, the journey to production can go through many different environments and confidence-building exercises before going into production. The only constant in technology is change, so the whole process starts all over again as soon as a version is released. Beginning with the introduction of a new feature, the changes will go into production.
continuous integrationis build automation. Depending on your versioning/versioning strategy, code changes for a bug fix or new feature should be merged/committed into a branch in the source code repository. It doesn't matter which side of the mono-repo vs. multi-repo argument is found on, a build and eventually release artifacts are created as part of the ongoing integration processes.
Because it matters
As a software engineer, you rarely work alone. Integrating its features/bug fixes into the application is a common task for a software developer. For the newly trained software engineer who only has experience with group projects, it may take some getting used to. The ability to bring ideas together quickly is the great benefit of continuous integration. In modern systems, the building and packaging steps can be different. For example, in JAVA development, JAVA compilation produces a JAR file. This JAR file is then packaged into a Docker image for deployment.
The three pillars that continuous integration solves are that builds are repeatable, consistent and available. With software, we strive to make practices repeatable; A swapped out build allows for this, which in turn becomes consistent. Modern continuous integration platforms allow for build scaling (having builds available when you need them instead of tying your local machine to them).
With continuous integration, keeping automated builds fast is crucial. Because this process runs multiple times a day, with triggers around each commit or combination, the time it takes to wait for results can quickly decrease. A challenge with continuous integration is to overcome other continuous pillars, such as B. Overloading continuous integration platforms in continuous delivery.
Trust in built and deployable packages is different from trust in deployment and subsequent release. You need to be strategic about where you apply parts of your test suite to avoid overloading the continuous integration process. A spanner in the sand should be that continuous integration addresses artifact-centric trust building (e.g. unit tests and artifact scans). Tests that consider other artifacts and dependencies and/or the application infrastructure are better suited to the continuous delivery process. Once the build is checked into a central repository, the next step in getting your idea into production is the promotion/deployment process.
Continuous deployment, as the name suggests, focuses on delivery; the installation and actual distribution of the bits. During a deployment, the application binary/package can traverse the topology in which the application or application infrastructure needs to serve the traffic. In the traditional sense, continuous deployment focuses on automating deployment across environments or clusters. As you progress through environments from non-production environments to test environments and finally to production, the number of endpoints you deploy increases. Continuous deployment focuses on the path of least resistance to get software into the environments it needs.
With modern platforms like Kubernetes, the separation of environments may not be physical compared to older or traditional machine-based platforms. A namespace (software separation) may be all that separates development from production, although the good principles of distributed systems still apply whichever platform you choose. With distributed systems, the topologies to which changes must be propagated can be large, even in pre-production environments.
Because it matters
The days of boxed SCP and shipments of binary distributions are all but over. Because continuous integration provides a deployable artifact, continuous deployment can bring that artifact to additional environments. The low-hanging fruit may be, as soon as a new artifact is created, immediately deploy that artifact to a development and/or QA integration environment to begin integration testing. Especially with modern paradigms like immutable applications and infrastructure, where every change is rebuilt, the number of deployments will increase significantly.
Deployments consist of two pairs: the install/activate pair and the uninstall/deactivate pair. From a pure delivery perspective, using continuous delivery is the de facto standard. With a rolling deployment, old application nodes can be replaced at incremental intervals, usually one at a time, until all nodes have the new version. The updated application instance or node is removed from the load balancer pool and added back to the pool after the installation is complete.
Having a clear map of the topology, especially when the infrastructure is elastic or on-demand, is key to understanding where your artifacts are going. Like continuous integration goals, keeping implementation fast is a good goal. The semblance of speed can be there when certain tasks need to be performed in parallel (ie, ramping up the infrastructure so artifacts can be served).
Understand that continuous deployment and continuous delivery have slightly different goals. Continuous delivery overlaps with continuous deployment on the deployment front, but we must be careful not to overload deployment systems to build trust and security, which are critical to continuous delivery.
Technology is fallible because people make technology. The steps to building trust are critical for any engineering team making change.continuous deliveryIt automates the steps to safely push changes into production. While continuous deployment focuses on the actual deployment, continuous delivery focuses on the release and the release strategy. An elusive goal would be to “press a button” for changes to go into production. This “push of a button” is continuous delivery.
Because it matters
The road to a release can be a snowflake. Because software is the culmination of multiple teams' decisions, it can be difficult to go through all the necessary steps and modifications required to propagate/support changes or new features. Continuous delivery entails all the testing steps, incremental/environment deployments, and validation steps to safely push changes into production.
Put simply, good pipelines are fast, secure, and repeatable. However, there is no one-size-fits-all solution when it comes to continuous delivery. A pragmatic continuous delivery approach is crucial for adoption. There is likely to be a wide range of technology options and platforms within any organization that are likely to precede the continuous delivery process.
Harness recently conducted a survey of the patterns organizations are using with oureBook on Pipeline Patterns. Your pipeline structure tends to follow what drives it. Pipelines are driven by environments, tests, services, results, or people. The form of the pipeline follows the function.
The only anti-pattern to be aware of is the human-driven one. Without automation, processes would be human-centric. As the gap begins to close, the manual steps will fade into a continuous deployment pipeline. The benefit of capturing all the necessary steps in a continuous delivery pipeline is that you can easily identify bottlenecks and invest in automation at the bottleneck.
One of the most difficult elements to automate is the validation/promotion of implementations. When test suites are run, the results are binary: it is a pass-or-fail test and no further implementation progress is required. Verifying whether a deployed application is successful or not can raise a variety of concerns and areas to check. Especially when implementing aCanary-StartIn a multiple incremental deployment strategy, this validation can and should be done post-deployment as well. Correlating key data/metrics from different monitoring, observability, and performance management solutions can be tedious, especially when trying to establish a baseline. The harness platform takes the guesswork out of this scenario.
How they work together in software delivery
There's a reason why "CI/CD" is often referred to together. Simply put, having a pipeline of artifacts that can be safely deployed is software deployment. If an organization had only a single artifact, created every few months, and deployed only a few nodes, and could tolerate downtime during maintenance, no investment would be required. Unfortunately, this scenario has not existed for generations.
Your continuous integration process maintains a repository of deployable artifacts that can be deployed. Your continuous delivery process orchestrates all required deployment and trust building/release activities and may invoke your continuous deployment infrastructure as new artifacts/changes traverse environments/clusters. The ability to deploy a release quickly and securely allows organizations to become more agile with modern software deployment capabilities. As the paradigm changes rapidly, questions will inevitably arise.
FAQ der DevOps-Community
Here are some questions we found in various DevOps communities that can help further describe the similarities and differences.
What makes the difference between deployment and release in the continuous delivery pipeline?
A deployment is an act of installing/activating the software/binaries. If an existing version is present during a deployment, the previous version will be uninstalled/disabled. A release is the culmination of all activities so that changes can safely go into production. As part of a release, there is a deployment component. Various release strategies, such as B. a controlled release, use incremental deployment strategies. Releases are usually signed and a record is kept of all events leading to a change or new version of the application (the new stable version).
What is the Continuous Delivery Deployment Pipeline Checklist?
Without getting into the semantics of the difference between an implementation and a software release, a checklist for a successful implementation verifies that features are as expected. Roughly speaking, the expectation from a technical perspective would be not to violate any type of SLA/SLI/SLO. From a functional perspective, success would be if there was adoption and no decline in usage. The validation steps in the checklist can ensure that the QA team's goals (code/test coverage) are met and that changes are investigated during, for example, a dip test. Have the changes met expectations and quality standards, and are they available to meet scaling needs? Harness helps automate the entire checklist.
Automate the build and test process with Harness
The harness platform gives you a full point-to-point connectionCI/CD channelingso that your ideas really make it safely into production. Whether you're deploying on multiple disparate infrastructure components or want to orchestrate multiple steps of reliable development and test automation, Harness can help your development team achieve a push of a button.
If you haven't already done so, please feel free to do soRegistrationOrder the strap platform today. If you're not at this stage yet, feel free to read on. We have a great eBook for you atPiping patternwhat can be useful.