Investigating Deployment Patterns

In this post, we'll explore Continuous Delivery (CD) and Continuous Integration (CI), focusing on deployment patterns that are well-suited for microservice architectures.

As the name implies, microservices are small, focused services that are designed to perform a single task or function. These services are autonomous and independently deployable, meaning that changes made to one service should not affect the others within the application. This independence enables each service to be developed, tested, and deployed separately, streamlining the development process and improving flexibility.

In contrast, monolithic architectures feature tightly coupled services, where changes to one component often require redeploying the entire application. Microservices, on the other hand, communicate with each other using asynchronous methods such as message queues or event hubs, allowing for more scalable, decoupled interactions between services. This approach enhances fault tolerance and enables better management of complex systems.

While testing code ensures that functionality is correct, end-users often interact with applications in ways that differ from how they were designed and implemented. Additionally, as usage levels increase, replicating production loads in a test environment becomes increasingly difficult. This highlights the importance of testing in production, where real-world conditions can be simulated to identify issues that may not have been evident during development.

To minimize the risk of failure and catch issues before they impact the entire user base, various deployment patterns can be employed. These include feature flags to control the rollout of new features, canary releases to test new changes with a small subset of users before full deployment, ring-based deployments to gradually roll out updates in stages, and A/B testing to compare different versions of a feature and determine which performs best. These strategies help ensure a smoother and safer release process while providing the ability to quickly address any unforeseen problems.

Blue-Green deployments

Blue-green deployments reduce risk and minimize downtime during application updates by using two identical environments, known as blue and green. At any given time, one environment is active while the other remains idle. When deploying a new version of the application, it is first deployed to the idle environment, allowing for testing in a production-like setting before directing incoming requests to the new version.

Once the new version is tested and verified, traffic is switched to the updated environment, and the previously active environment becomes idle. This approach not only minimizes or eliminates downtime but also provides an easy way to roll back to the previous version by simply switching back to the old environment.

In Azure, services like Web Apps and Function Apps support this concept through deployment slots, making it easier to implement blue-green deployments. These slots allow you to deploy new versions without impacting the current live application, ensuring a smooth transition and reducing the risk of deployment-related issues.

Feature Flags

Feature flags enable you to push new code to the main codebase and deploy it into the application, but with the feature hidden behind a gate. This means that only users who have the flag enabled can access the new functionality. Release flags can be used to roll out new features gradually, targeting a smaller group of users, such as early adopters or canaries, before making them widely available.

Feature flags also facilitate A/B testing by giving a subset of users access to new functionality, allowing you to compare performance, operations, and user engagement metrics through your observability tools.

By using feature flags, you can expose new features or changes simply by “flipping a switch” at runtime. This approach separates feature deployment from feature exposure, allowing for more controlled and flexible delivery. It enhances delivery practices and helps maintain the stability of the product, as new functionality can be tested and monitored before being fully rolled out to all users.

Canary Builds

The use of canaries in coal mines, where canaries were sensitive to toxic gases and would collapse or die before humans were affected, provides the inspiration for canary releases. In this deployment strategy, a small subset of users is selected to validate new features and changes. By closely monitoring this group, developers can gather relevant data about the feature's behavior and determine whether to roll it out to a larger audience or disable it altogether.

With tools like traffic routing, deployment slots, and feature flags, you can direct a percentage of traffic to specific deployment slots or target particular user groups for testing. This allows for a controlled and gradual rollout of new features.

Another deployment method similar to canary releases is the dark launch. In a dark launch, the new feature is deployed but not fully exposed to all users. Instead, the feature is revealed to a specific group to gather feedback on the user experience. Alternatively, you can run two versions of a service side by side—one with the new version and one with the old—while collecting and comparing backend metrics. This allows you to observe any differences in operation and performance without affecting the entire user base.

A/B Testing

Split testing or A/B testing involves comparing two versions of a webpage or application to determine which one performs better. These experiments are typically shown randomly to different users, allowing analysts to assess which variation achieves specific goals, such as higher conversion rates, better user engagement, or improved performance.

For A/B testing to be effective, it's crucial to have a continuous delivery pipeline in place. This allows new versions of the application to be deployed with minimal disruption, enabling quick iterations and rapid testing of different features or design variations. By streamlining the deployment process, continuous delivery ensures that A/B tests can be conducted efficiently, providing valuable insights that drive product improvements.

Deployment Rings

Ring-based deployments are a gradual release strategy that allows you to increase the user base for a new version of an application in stages. Starting with a small group of canary users, the release is then extended to early adopters, and eventually to the general user base. With each "ring," the size of the user base grows, moving from the most risk-tolerant users to those who are more risk-averse.

During each stage, the new version is closely monitored for performance and issues. Only once the current ring is stable and healthy do you proceed to the next ring, ensuring that potential problems are addressed before the release reaches a larger audience. This approach minimizes risk by allowing for thorough testing and validation at each stage of the rollout.