Implement Blue-Green Deployments on AWS using Terraform for zero downtime and easy rollbacks. Learn best practices from SquareOps for CI/CD and Auto Scaling.
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AWS Blue_Green Deployment Using Terraform Guide.pdf
1. AWS Blue/Green Deployment Using Terraform Guide
Introduction
With the rapid development on how applications are build & shipped,
adopting the right deployment strategy is pivotal for ensuring robust
Continuous Deployment (CD) and maintaining high software
quality standards. Deployment strategies play a crucial role in DevOps
practices, offering varied approaches to software release and
infrastructure management. In this blog, we’ll explore several key
deployment strategies, emphasising their relevance in Continuous
Integration and Continuous Deployment pipelines, before focusing on
the Blue-Green deployment method, particularly its
2. implementation on AWS using Terraform, a leading Infrastructure
as Code (IaC) tool.
1. Rolling Deployment: This technique, integral to
Continuous Deployment, involves incrementally updating
servers with the new version. It’s highly compatible with
Agile methodologies, ensuring minimal downtime and
facilitating a stable Continuous Delivery process.
2.Canary Deployment: A strategic fit for Continuous
Deployment, canary deployment targets a small segment of
the production environment first. Its gradual approach aligns
well with Agile and DevOps principles, allowing for real-time
monitoring and quick rollback if needed.
3.A/B Testing Deployment: This strategy is crucial for
user-centric Continuous Deployment, providing direct
feedback on user engagement and experience. It’s a
data-driven approach, often used in conjunction with
Continuous Testing practices.
3. 4.Recreate Deployment: Simple yet effective, this strategy
involves downtime but is sometimes used in Continuous
Deployment when zero-downtime isn’t a critical factor. It’s
straightforward and suitable for applications with flexible
availability requirements.
5. Shadow Deployment: Often used in Continuous
Deployment and Continuous Testing, this strategy involves
duplicating real traffic to a shadow version. It’s excellent for
performance testing under real conditions without impacting
the end-user experience.
Focusing on Blue-Green Deployment, this strategy is used for
Continuous Deployment with zero downtime. It involves maintaining
two identical environments: the Blue (current production) and Green
(new version). At any given time, only one of these environments is
live, serving all production traffic. When it’s time to release a new
version of the software, the update is first deployed to the inactive
environment (e.g., green). The switch from Blue to Green ensures
4. minimal downtime and provides a quick rollback mechanism in case
of issues, aligning seamlessly with Continuous Deployment and
Continuous Integration (CI) practices.
Integrating Terraform, a prominent Infrastructure as Code tool, into
Blue-Green deployment on AWS enhances the strategy. Terraform
automates the creation and management of both environments,
ensuring consistency and alignment with DevOps, Continuous
Integration, and Continuous Deployment principles. This integration
is particularly beneficial in AWS cloud environments, where managing
complex infrastructures requires both precision and flexibility.
When to use Blue-Green Deployment?
There are several benefits to using blue-green deployment:
● Zero downtime: By routing traffic to the new environment
before taking the old one out of service, you can ensure that
there is no disruption to the end users.
5. ● Easy rollback: If there are any issues with the new version
of the software, you can quickly roll back by routing traffic
back to the old environment.
● Improved reliability: By testing the new version of the
software in a separate environment before releasing it to
production, you can catch and fix any issues before they affect
the end users.
● Confidence in Release: Blue-green deployment allows you
to release software updates with confidence, knowing that
you have a fallback plan in case anything goes wrong.
6. Integrating Terraform with EC2 Autoscaling for
Blue-Green Deployments
While Blue-Green deployments offer significant advantages,
integrating this strategy with tools like Terraform and EC2
Autoscaling groups presents its own set of challenges. In this section,
we’ll delve into these challenges and outline the effective solutions
we’ve developed at SquareOps
The problem with Terraform and EC2 Autoscaling
groups
7. When implementing Blue-Green deployment using Terraform on AWS
a key challenge emerges with EC2 Auto Scaling groups & how
terraform operates. This challenge is crucial for DevOps engineers and
cloud architects who rely on Terraform for infrastructure as code (IaC)
practices and AWS CodeDeploy for seamless deployment processes.
Addressing this issue is essential for optimizing Continuous
Integration/Continuous Deployment (CI/CD) pipelines and ensuring
efficient cloud resource management.
The core of the problem lies in how Terraform interacts with AWS
Auto Scaling groups during a Blue-Green deployment orchestrated by
AWS CodeDeploy. AWS CodeDeploy, a critical service in AWS for
automating software deployments, plays a vital role in this setup.
According to the AWS CodeDeploy documentation, during a
Blue-Green deployment, a new Auto Scaling group is created to
transition to the new version of the application.
8. However, when Terraform is used to create and manage these Auto
Scaling groups, it does not automatically recognize or incorporate the
new Auto Scaling group created by CodeDeploy into its state
management. This discrepancy leads to Terraform attempting to
recreate the Auto Scaling group with its original configuration during
subsequent terraform apply operations. As a result, cloud engineers
face errors and inconsistencies, which can disrupt the deployment
process and lead to potential downtime or resource mismanagement.
To delve deeper into this topic, it’s essential to understand the
intricacies of Terraform’s state management and how it interacts with
AWS services. Terraform’s state file is crucial for tracking the
current state of the infrastructure it manages. When external changes
are made to the infrastructure that Terraform manages (in this case,
by AWS CodeDeploy), Terraform’s state file does not automatically
update to reflect these changes. This leads to a state mismatch,
causing Terraform to try to enforce the configuration as defined in its
code, which doesn’t account for the new Auto Scaling group.
9. Solution to Seamless Blue-Green Deployment for EC2
Autoscaling Groups with Terraform and AWS
CodeDeploy
To navigate this challenge, we’ve developed an approach that ensures
Terraform, AWS CodeDeploy, and EC2 Autoscaling groups work in
harmony. This section provides a detailed step-by-step
implementation of the solution.
1. Modify the official terraform module ( here
Terraform-aws-module) to accommodate the solution
requirements
Add support for an additional variable to ignore resource tag-related
changes.
11. To avoid the AWS Autoscaling group module from creating
auto-scaling groups with random names, we have set use_name_prefix
to false
Then using the terraform data source feature, we fetched the name of
12. the new auto-scaling group with the help of tags and referred to it
while calling the module again for any changes.
This code snippet assumes that the VPC network and AWS Application
Loadbalancers are already created. To get a complete example of
creating an autoscaling group using Terraform, that includes VPC and
ALB as well, send an email to [email protected] to get full
access to the Terraform library maintained by SquareOps
Configuring AWS CodeDeploy for Blue-Green Deployment
3. We have used Terraform to create the AWS code
deploy service resources also and its configurations
14. This terraform code snippet creates an IAM Role and Policy for
CodeDeploy that grants AWS CodeDeploy the necessary permissions
to perform deployments across EC2 instances and Autoscaling groups.
This role will be assumed by the CodeDeploy service. It also creates
the CodeDeploy Application and sets up deployment groups ( one for
each of the Blue and Green environments. )
4. Solution to the terraform state deviation problem
15. We also created a script that needs to be run before any terraform
operations. This will import new auto-scaling groups created by AWS
Codedeploy Service’s Blue-Green Deployment strategy and replace the
older auto-scaling group details. Now the terraform plan and terraform
apply will not create a new auto-scaling group after the CI/CD
deployments.
Let us go through all the commands in this script:
a.terraform refresh command refreshes the state of terraform to
identify any changes.
16. b. This command will match the name in outputs and state
Conclusion
In this blog, we’ve navigated through the challenges of setting up
Blue-Green deployments using AWS, Terraform, and AWS
CodeDeploy. Blue-Green deployment is more than just a deployment
strategy; it’s a pathway to ensuring zero downtime, enhancing the
reliability of your applications, and providing a safety net through easy
rollbacks.
By integrating this approach with Terraform’s powerful infrastructure
as code capabilities and AWS’s scalable cloud infrastructure, we offer a
solution that not only optimizes your deployment processes but also
aligns with the best practices in cloud computing and DevOps.
17. At SquareOps Technologies, our commitment to innovation and
excellence in cloud services is unwavering. We understand that every
organization’s needs are unique, and our team of experts is equipped
to provide tailored solutions that meet your specific requirements.
Whether you’re just starting your cloud journey or looking to optimize
existing systems, our comprehensive suite of services in Kubernetes,
CI/CD, Observability, Infrastructure as Code, Security, and Cost
Optimizations is designed to guide and support you at every step.
We invite you to reach out to us for any assistance in implementing
Blue-Green deployments or other cloud and DevOps solutions. Let’s
work together to transform your deployment strategy and propel your
business toward greater efficiency and success.
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