What is Continuous Deployment?

Imagine this scenario: It is Monday morning and your team uncovers a critical security vulnerability in your flagship product. Without hesitation, you cancel the rest of the day's meetings, and a sense of urgency fills the air as your team races to rectify the bug before it jeopardizes your business. Swift mobilization ensues, but unfortunately, your team's conventional deployment process proves to be a hindrance due to its sluggishness and complexity.

Days turn into weeks, and by the time your team had a patch ready, news of the vulnerability had spread, causing widespread concern among your user base. Trust in the product has eroded, and customers grow frustrated with the delay.

Your company's reputation suffers and faces an uphill battle to regain any lost ground. Morale among the team starts to wane, as they realize the missed opportunities and the toll it took on their once-thriving company.

You shake your head at your computer and realize this isn’t the first time this has happened. Your engineering team's approach to deploying software isn’t cutting it anymore; it’s far too manual and bugs are constantly being pushed to production.

This nightmare scenario can be avoided through the use of Continuous Deployment.

So what does an ideal workflow look like for your engineering organization?

Developers working on code would push the changes to version control systems such as GitHub, GitLab, or BitBucket. From there, automated tests are run by an integration server such as Jenkins or TeamCity. If all tests pass, the changes are then pushed into production with no manual intervention required from IT staff or other personnel, ensuring that changes to the code base get released quickly and effectively without having to wait for IT staff availability.

Once in production, the application can be monitored closely using tools such as New Relic or AppDynamics, allowing the organization to keep track of how the application is performing to spot any issues quickly and resolve them before they become major problems.

By reducing manual actions and automating processes like testing and deployment, organizations can benefit from faster release cycles while maintaining stability within their software applications.

Fast-paced engineering teams are reaping the rewards of Continuous Deployment, as demonstrated in the scenario above. This post will delve into the essence of Continuous Deployment, highlight its distinctions from Continuous Delivery, and outline five invaluable best practices for achieving seamless Continuous Deployment.

What is Continuous Deployment?

Continuous deployment is a modern and efficient software development practice that enables the automatic release of code changes into the production environment. It ensures that features are swiftly available to users as soon as they are ready. This approach not only reduces the time required for feature availability but also empowers developers to prioritize delivering value more rapidly.

In our scenario earlier, the lack of Continuous Deployment hindered the team’s ability to respond to user feedback effectively. Valuable insights and feature requests were piling up, leading to a growing disconnect between the team and their users. Meanwhile, competitors who had embraced Continuous Deployment were swiftly releasing updates, earning trust and loyalty from their customers.

Continuous Deployment on Kubernetes

Continuous Delivery (CD) aims to guarantee the secure and seamless deployment of your changes into production, promoting efficiency throughout the process. Kubernetes, with its capacity for swift deployment, particularly in a recreate strategy that replaces all Pods at once rather than incrementally, offers speed but may result in downtime.

This can be problematic for most of us who rely on uninterrupted workloads. When continuous delivery is properly implemented, developers always have a deployment-ready build artifact that has passed through a standardized testing process.

The trust-building procedures applications underwent before Kubernetes' introduction remain just as relevant.

Mainly, we have seen organizations face the following challenges when manually deploying applications on Kubernetes.

1.Running manual Kubernetes deployments is a complex and time-consuming process.

Even in a world with services like EKS, GKE, and AKS providing “fully” managed Kubernetes clusters, maintaining a self-service Kubernetes provisioning system is still challenging.

Toolchains like Terraform and Pulumi can create a small cluster fleet but don’t provide a repeatable API to provision Kubernetes at scale and can often cascade disruptive updates with minor changes not caught in review.

Additionally, the upgrade flow around Kubernetes is fraught with dragons, in particular:

• Most control planes require a full cluster restart to apply a new Kubernetes version to each worker node, which is a delicate process that can bork a cluster.
• Deprecated API versions can cause significant downtime, even a sitewide outage similar to what the team at Reddit saw this year.

Companies with larger deployments end up dedicating a team to manage rollbacks and keep track of old and new deployments. This process becomes more challenging and ultimately riskier when dealing with a large team and a complex application.

2. Kubernetes Codebases are Thorny

Kubernetes specifies a rich, extensive REST API for all its functionality, often declared using YAML. While it is relatively user-friendly, larger application codebases interacting with that YAML spec can frequently balloon into thousands of lines of code.

There have been numerous attempts to moderate this bloat, using templating with tools like Helm or overlays with Kustomize. We believe all of these have significant drawbacks, which impair an organization's ability to adopt Kubernetes, in particular:

• No ability to reuse code naturally (there is no package manager for YAML)
• No ability to test your YAML codebases locally or in CI (preventing common engineering practices for quickly detecting regressions)

Common software engineering patterns, like crafting internal SDKs or “shifting left,” are impossible with YAML as your standard. The net effect is going to be more bugs reaching clusters, slower developer ramp times, and just general grumbling throughout an engineering organization from clunky codebases.

3. Deployment Pipelines on Kubernetes are Poorly Supported

Kubernetes has a rich ecosystem of CD tooling, with the likes of Flux and ArgoCD, but most are built primarily for simple single-cluster deployment use cases out of a unique git repository. To use any of them, you still need lower-level Kubernetes management expertise to provision and administer the cluster to which they deploy.

In particular, we’ve noticed Kubernetes novices are quite intimidated by all the details of authenticating to the Kubernetes API, especially when using managed Kubernetes that goes through about three layers of Kubeconfig → IAM authenticator → bearer token auth + TLS at the control plane.

In order to get a CD system working, you’ll need to be capable enough to deploy something like Argo-CD to fully manage the Kubernetes auth layer to get the systems integrated and hardened. While this is not an insuperable task, it is probably enough friction to make people reconsider using an inferior tool like ECS for their containerized workloads.

And even if you get all that set up, you still need to be able to create a staged deployment pipeline from dev → staging → prod to allow for appropriate integration testing of your code before exposing it to users. That often requires hand-rolling a tedious, complex git-based release process and is manual enough that you can’t self-serviceably expose it to other teams.

Continuous Delivery vs Continuous Deployment

As technology continues to evolve, the demand for faster software delivery and more frequent releases has significantly increased. In response to this demand, software development teams have adopted various methodologies and approaches to speed up the software development process. Two popular approaches are Continuous Delivery and Continuous Deployment.

Continuous Delivery and Continuous Deployment are related software delivery methodologies emphasizing agility and automation in software development. Continuous Delivery is a process of automating the software delivery process to enable frequent and efficient releases. Continuous Deployment, on the other hand, is an extension of Continuous Delivery where every successful build of the software is automatically deployed to production.

The main difference between Continuous Delivery and Continuous Deployment is the level of automation and control over the release process. With Continuous Delivery, the software is built, tested, and prepared for deployment, but the deployment is a manual process. This means the development team has more control over when and how the software is released. With Continuous Deployment, the software is automatically deployed to production after every successful build, enabling much faster releases and reducing human error.

Another significant difference between these two approaches is the level of risk involved. With Continuous Delivery, there is still a chance that a deployment could fail at the production stage, even though thorough testing was done in the development and testing environments. With Continuous Deployment, since every build is deployed to production automatically, the risk of a failed deployment is significantly higher, and the impact could be much greater.

One way to mitigate the risks associated with Continuous Deployment is to implement canary releases, where new features are gradually released to a subset of users to identify and fix any issues before fully rolling out the latest release. This approach is not possible with Continuous Delivery, where the development team has full control over when and how the software is released.

Continuous Deployment demands a greater degree of automation compared to Continuous Delivery. To achieve Continuous Deployment, an automated pipeline is necessary to seamlessly guide the code through various stages of development, testing, and deployment. This requires an elevated standard of code maturity, rigorous quality testing, and adherence to DevOps practices. On the other hand, Continuous Delivery allows for some manual processes, rendering it more accessible for organizations that are not fully prepared for complete automation.

Choosing between Continuous Delivery and Continuous Deployment depends on various factors, such as the development team's maturity level, risk tolerance, and the need for speed and agility. Continuous Delivery is a good starting point for organizations that are looking to automate their software delivery process and achieve more frequent releases.

On the other hand, Continuous Deployment is suitable for organizations that require maximum speed and agility in their software development process but are willing to take on more risk. Regardless of the approach, it is essential to have a solid Continuous Integration and Continuous Testing process to ensure the code quality and stability of the software. By implementing the right approach for your team, you can enjoy faster releases, improved quality, and reduced risk in your software development process.

Continuous Deployment Best Practices

Here are five crucial Continuous Deployment (CD) best practices:

1. Automated Testing:

• Implement a comprehensive suite of automated tests, including unit, integration, and end-to-end tests.
• Use tools like unit testing frameworks, integration testing frameworks, and automated testing services to ensure code changes are thoroughly tested before deployment.

2. Continuous Integration (CI):

• Practice continuous integration by frequently merging code changes into a shared repository.
• Use CI tools to automatically build and test code with every integration, ensuring it remains in a deployable state.

3. Incremental Deployment:

• Deploy small, incremental changes rather than large, monolithic updates. This reduces the risk of introducing major issues and allows for quicker rollbacks if needed.

4. Rollback Plans and Canary Releases:

• Have well-defined rollback procedures in case a deployment introduces critical issues.
• Implement canary releases to gradually roll out changes to a small subset of users, allowing for early detection of any problems before a full release.

5. Monitoring and Observability:

• Implement robust monitoring and observability solutions to track the health and performance of your application in real-time.
• Set up alerts to notify the team of any anomalies, ensuring rapid response to potential issues.

By adhering to these best practices, development teams can establish a reliable and efficient Continuous Deployment process, enabling them to deliver high-quality software to users quickly and with confidence.

Five Benefits Of Continuous Deployment

1.Faster Time to Market

Time is of the essence in software development. With Continuous Deployment, bugs can be detected and fixed quickly, and new features can be pushed out seamlessly. This means that your organization can deliver high-quality software releases faster than ever before. With Kubernetes, you can take advantage of the built-in scaling capabilities to handle increased load during peak periods. The automated scaling ensures that your applications are always available, providing an uninterrupted flow of business value.

2. Improved Quality

Continuous Deployment's automated testing ensures quality control that can catch problems before they reach production. Thorough testing at every stage of the deployment pipeline leads to a reduction in bugs and an improved user experience. By catching any issues early and addressing them immediately, your DevOps team can become more agile and responsive to customer needs.

3. Better Collaboration

Continuous Deployment encourages better collaboration between developers, testers, and operators. With a shared automated pipeline, teams learn to work together and communicate better. Collaboration ensures that the pipeline runs efficiently, from code testing to deployment. Kubernetes provides developers and operators with abstraction that makes it easier to handle versioning and deployment, thereby streamlining collaboration efforts.

4. Increased Visibility and Control

While deploying software through traditional means may be challenging, using Continuous Deployment provides increased visibility and control. With Kubernetes, you can easily monitor and track your application state and your deployment pipeline. Kubernetes provides an intuitive dashboard that allows you to troubleshoot and take corrective action proactively. You can use Kubernetes to label and organize your software, making it easier to keep track of the version of each component.

5. Cost Savings

Implementing Continuous Deployment eliminates the traditional deployment roadblocks that are faced with manual deployments. This leads to a reduction in the operational and maintenance costs associated with deployment, not only providing cost savings but also freeing up time and resources that can be used for further innovation and development

Continuous Deployment done right with Plural CD

Plural is an end-to-end solution for managing Kubernetes clusters and application deployment. Plural offers users a managed Cluster API provisioner to consistently set up managed and custom Kubernetes control planes across top infrastructure providers.

Additionally, Plural provides a robust deployment pipeline system, empowering users to effortlessly deploy their services to these clusters. Plural acts as a Single Pane of Glass for managing application deployment across environments.

With Plural you can effortlessly detect deprecated Kubernetes APIs used in your code repositories and helm releases minimizing the effect deprecated APIs can have on your ecosystem.

Features:

• Rapidly create new Kubernetes environments across any cloud without ever having to write code
• Managed, zero downtime upgrades with cluster API reconciliation loops, don’t worry about sloppy and fragile terraform rollouts
• Dynamically add and remove nodes to your cluster node topology as you like
• Use scaffolds to create functional gitops deployments in a flash
• First-class support for cdk8s.io to provide a robust Kubernetes authoring experience with unit testability and package management
• Integrated secret management
• A single, scalable user interface where your org can deploy and monitor everything fast.