Deployment is the process of introducing software changes into production. It can be a risky proposition, as there is always a chance that something could go wrong with the new version and impact the end-users. This is why there are multiple deployment strategies that developers and site reliability engineers (SREs) can use to minimize the risks involved. In this article, we will explore the most common deployment strategies, their advantages and disadvantages, and when it makes sense to use them.
Canary Deployment Strategy
The canary deployment strategy is a technique to reduce the risk of introducing a software update in production by slowly rolling out the change to a small subset of users before making it available to everybody. This involves deploying a new version of the software to a small group of users, known as the “canary group.” The canary group is typically made up of a small percentage of users, such as 1% or 2%. Once the software is deployed to the canary group, the SREs can monitor its performance, stability, and user feedback. If everything looks good, the SREs can then roll out the new version to the rest of the users.
The rollout process for canary deployment is typically automated to minimize the risk of human error. The SREs will set up a pipeline that allows them to easily switch back to the previous version if something goes wrong. This ensures that there is always a working version of the software available to users. The canary deployment strategy is an excellent option for organizations that cannot afford deployment downtime during an update.
One significant advantage of canary deployment is that it allows SREs to catch issues early. By deploying the new version to a small group of users, they can identify issues before rolling out the update to the entire user base. This can save time and money as fixing issues later in the deployment process can be significantly more expensive and time-consuming.
However, there are also some disadvantages to canary deployment. For example, it can be difficult to select the users for the canary group. If the group is not representative of the entire user base, it may not provide the insights needed to make informed decisions. Additionally, the canary deployment strategy requires a certain level of infrastructure and tooling to be in place, which can be challenging for smaller organizations.
Blue-Green Deployment Strategy
The blue-green deployment strategy is a deployment technique in which both the old and new instances of the application or microservice run concurrently in production, with a load balancer instantly switching traffic from the older version to the newer version. In this deployment strategy, the new version of the software is deployed alongside the previous version on a server. The load balancer directs traffic to the new version, and if any issues arise, it can be quickly switched back to the old version.
The rollout process for blue-green deployment is also automated, which helps to minimize human error and reduce deployment downtime. One significant advantage of blue-green deployment is that all customers always access the same version, eliminating version issues. Additionally, if something goes wrong, rolling back the changes is quick and easy because the old version is still in place.
Despite these advantages, the blue-green deployment strategy also has some disadvantages. For example, running two versions of the software simultaneously can be resource-intensive, and organizations may need to invest in more infrastructure to support the deployment. Additionally, testing in production has its risks, and unexpected issues may arise when the new version is live.
The recreate deployment strategy is a less sophisticated deployment strategy, in which the older version of an application must be shut down before deploying the newer version. Typically, this involves taking the software offline for a brief window of time to deploy the new version. This deployment strategy is simpler than the others described so far, but it carries a higher risk of downtime if something goes wrong.
One potential advantage of the recreate deployment strategy is that it may be a good option for smaller organizations or applications with fewer users. Additionally, it allows SREs to perform a clean installation of the new version of the software.
However, there are also disadvantages to this deployment strategy. For example, the downtime required to deploy the new version can be a severe issue for larger organizations or those with significant user bases. Additionally, the recreate deployment strategy has a higher risk of failure and requires the SREs to thoroughly test the new version before deploying it.
Shadow Deployment Strategy
The shadow deployment strategy is one where the new version of the software is available alongside the old version in production, but a copy or a forked version of the traffic sent to the older version is redirected to the new version for production testing. In this deployment strategy, the new version of the software is deployed in production alongside the old version. Initially, the traffic is not directed to the new version but instead, a copy of the traffic is sent to the new version for testing purposes.
One significant advantage of shadow deployment is that it allows SREs to test new software in a real-world environment while simultaneously serving the production workload. This gives the SREs a good understanding of how the new version will perform under real-world conditions, without impacting the end-users.
However, the shadow deployment strategy also has some disadvantages. For example, it can be challenging to manage the routing of traffic between the old and new versions of the software. Additionally, the shadow deployment strategy requires a certain level of infrastructure and tooling to be in place, which can be challenging for smaller organizations.
A/B testing deployment strategy
The A/B testing deployment strategy relies on real-world statistical data to decide on a rollout or rollback. This deployment strategy involves deploying two versions of the software: the existing version (A) and the new version (B). The two versions are presented to users randomly, and the SREs collect data on how users interact with the software. This data is then used to determine which version performs better.
One significant advantage of A/B testing is that it provides SREs with real-world data to inform decision-making. This allows them to make informed decisions about which version to roll out based on user behavior. Additionally, A/B testing allows organizations to test significant changes to their software in a controlled environment.
However, there are also disadvantages to A/B testing. For example, it requires an expensive and intelligent load balancer to direct traffic between the two versions. Additionally, it can be challenging to identify and isolate specific variables that could impact user behavior.
Considerations for SREs
When it comes to choosing a deployment strategy, SREs need to make an informed decision based on the requirements of the application, organization, and users. Factors that SREs should consider include the size and complexity of the application, the number of users, the importance of minimizing downtime, the cost of infrastructure, and the level of risk tolerance.
SREs should also be aware of the importance of informed decision-making, particularly when it comes to balancing the needs of the business with the needs of the users. Informed decision-making requires careful consideration of the data and feedback available, along with the expertise of the SREs.
Route-based deployment strategy
The route-based deployment strategy involves the use of a router or load balancer by the SRE of an application team to target individual routes. This deployment strategy enables SREs to fine-tune the deployment process by directing traffic to specific routes for the new version of the software. For instance, SREs can direct traffic to the new version of the software for specific features or sets of users.
The rollout process for a route-based deployment strategy is typically automated, which helps to minimize human error and reduce deployment downtime. Additionally, the strategy allows SREs to monitor the performance of the new version of the software and roll back changes if necessary.
One significant advantage of the route-based deployment strategy is that it allows SREs to deploy new versions of software in a highly targeted manner. This enables them to test new features or functionality with specific users or clients without impacting the entire user base.
However, there are also disadvantages to the route-based deployment strategy. For example, it requires a higher level of infrastructure and tooling to be in place, which can be challenging for smaller organizations. Additionally, careful planning and testing are required to ensure that the targeted routing does not negatively impact the overall user experience.
When to use Canary Deployment
The canary deployment strategy is an excellent option for organizations that cannot afford downtime, need to minimize the risk of introducing a new version of the software, and want to catch issues early in the deployment process. Canary deployment is particularly useful for organizations with large user bases, where the impact of a flawed deployment could be significant.
Benefits and constraints of deployment strategies
Each deployment strategy has its advantages and disadvantages. Canary deployment allows SREs to catch issues early, blue-green deployment eliminates version issues, recreate deployment is simple and straightforward, shadow deployment allows SREs to test new software in a real-world environment, and A/B testing provides SREs with real-world data to inform decision-making.
However, each deployment strategy also has its own constraints. For example, canary deployment can make it difficult to select the right users for the canary group, blue-green deployment requires additional infrastructure to support parallel versions, recreate deployment has a higher risk of downtime, shadow deployment can be challenging to manage the routing, and A/B testing requires an expensive and intelligent load balancer.
Overall, the choice of deployment strategy should be based on a careful consideration of the specific needs and requirements of the organization, application, and users.
Deployment is an essential aspect of software development, but it can be a risky proposition without the right deployment strategy. In this article, we explore the most common deployment strategies, including the canary, blue-green, recreate, shadow, A/B testing, and route-based deployment strategies. We discuss the advantages and disadvantages of each strategy, as well as the considerations that should inform the choice of deployment strategy. Ultimately, the choice of a deployment strategy should be based on a careful examination of the specific needs and requirements of the organization, application, and users.