Effective deployment of software to end users is one of the most vital aspects of the software development lifecycle. Thorough testing and validation allow DevOps Engineers to reduce errors or conflicts thus increasing collaboration and management during the deployment process.

The most famous deployment strategies used in the industry are Blue-Green deployment and Canary deployment. Companies like Facebook and Google leverage the use of canary deployment while Netflix and Amazon opt to use blue-green deployment to update their services consistently without delay.

Deployment strategies

Deployment strategies are ways to implement changes and upgrade existing applications. The need to upgrade to a new version or make changes to existing applications is very important since thorough research has been carried out to ensure the end user enjoys every feature of the application for ease of use.

Importance of Safe Deployment

When the deployment is carried out, several factors must be taken into account including but not limited to;

• Security of the user data to the third party.
• Minimizing downtime to ensure high availability of services.
• Decrease in errors that may result in loss of data.

Blue-Green Deployment

Blue-Green deployment is a software release strategy that involves the creation of two identical environments (blue and green) where traffic is often directed to the blue environment and the new version is deployed to the green environment. After thorough testing and changes are confirmed, the traffic is switched to the green environment.

The main advantages of this deployment are that there is minimal downtime whereby updates can be rolled out perfectly without disrupting the user experience and simplified testing in a production-like environment.

The drawbacks of this deployment strategy are that it is expensive since it requires two complete environments to run and managing the two environments can be complex leading to delayed updates and high labor cost.

Canary Deployment

Canary deployment is a software release practice where an application is deployed in stages to a limited subset of users first. These users monitor and test the application’s performance and provide user feedback accordingly. Once updates and changes are approved, the updates are released to all the users.

The advantages of this deployment are that there is minimal risk where the impact of damage is limited to a small group, it is flexible and adaptive, and also engineers can monitor usage and catch concerns early.

Its disadvantages are that it requires robust monitoring tools, has potential user segmentation issues, and has a slower release compared to blue-green deployment.

Comparisons

Resource Requirements

Load balancer

In canary deployment, the load balancer routes limited traffic to the new version until testing is complete while most traffic is directed to the stable version (old).

In blue-green deployment, the load balancer switches between two environments which are the current version (blue) and the new version (green). Upon successful testing, the load balancer shifts all the traffic to the green environment (new version).

The main tools used as load balancers include AWS Elastic Load Balancing (ELB), Google Cloud Load Balancing, and NGINX.

Application environments

Canary deployment involves the use of a single environment to host the new version and the stable version simultaneously while blue-green deployment, two identical environments are created separately for one environment to host the new version and the other to host the live production.

The common tools used in creating application environments for these deployments are Kubernetes, Docker Swarm, Virtual Machines, and Cloud environments such as Google Cloud, AWS, and Azure.

Traffic Management

Traffic in canary deployment is shifted from the stable version to the canary version based on set-out rules and tools to control the traffic.

In blue-green deployment, traffic is more straightforward whereby traffic is either fully in the Blue environment or fully in the Green environment. It requires precise timing to manage the traffic.
Common tools used in traffic management are Istio, Envoy, AWS App Mesh, and Consul.

Monitoring and Observability

Monitoring is critical in software deployment because the main goal is to collect metrics, logs, and user feedback to detect any issues early and prevent disasters.

In canary deployment, monitoring will ensure traffic conditions for both versions are collected and analyzed simultaneously to detect any malfunctions while in blue-green deployment, monitoring focuses on ensuring the green environment is functioning before and after the switch from the blue environment.

The main tools used to achieve this aspect are Prometheus, Grafana, Datadog, ELK (Elasticsearch, Logstash, Kibana), and New Relic.

CI/CD Pipelines

CI/CD pipelines streamline every stage of software delivery by automating building, testing, and deployment. Continuous Integration ensures the code changes are integrated and tested and Continuous Deployment ensures the software changes are deployed automatically into production.

In canary deployment, the CI/CD (Continuous Integration/ Continuous Deployment) pipeline needs to support regular deployment processes by automating traffic, rolling back, or scaling up the canary.

In this scenario, a Docker image is deployed on the staging environment in Kubernetes where tests are run frequently to validate the image. The Canary version receives 10% of the traffic for testing. Jenkins is used to control traffic distribution between the two versions.
After all the tests are done and the canary version is stable, all the traffic is directed to the canary version entirely.

In blue-green deployment, the CI/CD pipeline supports deploying to a separate environment and also manages the clean-up process where the old environment can be used for updates for the next version release.

Here, a Docker image is deployed to a staging environment similar to Canary Pipeline but a green environment is set up as a copy of the Blue environment. The new Docker image is deployed to the Green environment in Kubernetes where tests are run endlessly to ensure the image functions correctly. If the application passes the tests, a load balancer is used to switch all traffic from the Old Version (Blue) to the new version (Green).

The main tools used for CI/CD processes are Jenkins, GitLab CI/CD, CircleCi, Spinnaker, and ArgoCD.

Risk management

Risk management in software deployment involves identifying and mitigating the risks associated with the release of new versions with new features into a production environment.

Potential risks can be identified from code bugs, compatibility issues, performance impact, user experience, and security vulnerabilities where the main sources of risk are new features and functionality, infrastructure changes such as servers, databases or networks, and third-party dependencies i.e. third-party libraries or services.

In canary deployment, the risk is mitigated by deploying the new version to a small subset of users for feedback. If issues arise, then a small number of the user base is affected and rollback is easier. Monitoring tools are set up to detect issues early and notify the team of any vulnerabilities allowing for quick intervention. Feature flags are also used to enable and disable specific features that may be causing malfunctioning.

In blue-green deployment, a dual environment is created where the new version of the software is deployed on the Green environment, and the live environment is deployed on the Blue environment. Functional testing, performance testing, and security testing are thoroughly performed before switching live traffic to the Green environment. In case issues are detected, a quick rollback is quickly redirected to the original environment (blue).

Implementation complexity

When deploying software, complexities involved in the process are a key factor that influences the choice put into place.

Canary deployment offers significant benefits in traffic distribution where traffic is directed to a small subset of users, provides continuous feedback in real-time, and issues can be detected earlier to minimize damage impact.

Canary deployment complexity is very high since it requires sophisticated tools to manage and route traffic between the canary and stable versions, monitoring and alert tools used to output real-time analytics on when to move to the new version can be complex, automation and CI/CD integration involves writing complex scripts using specialized tools thus adding another layer of complexity and finally, rollback mechanisms need to scale back traffic gradually if issues are detected adding further complexity.

Blue-Green deployment offers outstanding benefits in software deployment as it has simplified traffic switching from one environment (Blue) to another environment (Green) once testing is complete, isolation of environments ensures risks of conflicts between the new version and old version are reduced and rollback is simplified reducing the complexity of the recovery process.

Blue-Green deployment complexity is moderate whereby coordinating and testing across two environments require more careful planning and resources, synchronization of databases and configurations between the two environments can be complex, and higher costs can be incurred when managing the infrastructure of two separate environments.

Uses cases

The choice between Canary and Blue-Green deployment strategies depends on the requirements of the software deployed, the type of infrastructure to be used, and the ability to mitigate risk effectively in case a threat arises.

Canary deployment

This type of deployment strategy is suitable in the following scenarios;

• High Traffic: When you have applications with high traffic, some issues may cause system failure, and its impact could be massive hence a new feature is introduced to a small segment of users and feedback can be gathered fast. An example is a social media platform.

• Gradual Rollout: Applications that need gradual rollout are achieved by deploying a new feature to a small subset of users to monitor its performance and slowly increasing the user base if no threats or issues have been detected. An example is an E-commerce platform.

  Blue-Green deployment

  This type of deployment strategy is suitable in the following scenarios;

• High Availability: This deployment allows switching between environments without downtime and this ensures that a 100% uptime is constant ensuring high availability. An example of a high availability software is a financial service application.

• Infrastructure Migration: Suitable for organizations that need to migrate their services to new infrastructure allowing for thorough testing before the switch is done.

• Regulations and Compliance: Suitable when a clear variance is needed between new features and old versions which can be audited and documented to meet regulatory requirements.

• Long Deployment Applications: Some applications have a long deployment process that requires more time to be deployed and hence cannot withstand interruptions. Blue-Green deployment ensures the long process is complete whereby the new version deployment happens in a separate environment.

  Conclusion

  The main difference between Canary deployment and Blue-Green deployment is that in Canary Deployment, the application is deployed in stages to a small subset of users before actual release to the users while Blue-Green deployment involves deploying software in two separate environments one for the live version (Blue) and the other on the new version (Green).

The type of deployment to choose depends on the infrastructure used, the type of application used such as applications with a higher user base, the type of traffic to experience, risk mitigation strategies that may affect application deployment, and the complexity of software deployed.

Before deciding on what type of deployment strategy to put into place for your software application, it is vital to do thorough research on the type of deployments used and consider its advantages and disadvantages.