Many DevOps folks are inclined to use Hashicorp’s Terraform on AWS to manage infrastructure as code. This can have some Schroedinger-esque qualities to it, in that it can simplify your cloud management while also adding a layer of complexity to your toolset. If you’re already using Terraform, or are planning to start implementing infrastructure as code, then use these tips for better management of AWS deployments.

1. Use Terraform AND CloudFormation

This might come as a surprise, but not everyone wants to be involved in the holy war between Terraform and CloudFormation – and many have team members who use both tools. If this rings true for you, there’s no need to give up on CloudFormation. You can make use of the aws_cloudformation_stack resource type in Terraform. By using this, you can incorporate existing CloudFormation templates in your Terraform configurations, or you can make use of any potential features that aren’t available in Terraform. The “parameters” and “outputs” of the resource let you have a bidirectional communication between the two tools as well. 

2. Run “terraform plan” early and often

One of the best things about infrastructure as code is that you can know what’s going to happen before it happens. Using the “terraform plan” command to get an output of any AWS infrastructure changes that would happen from the existing terraform configuration can help you plan, communicate, and document everything that happens during your change windows. Making a habit of getting the plan after even minor code changes can save you a bunch of headache from errors or misunderstood edits.

3. Be careful using Autoscaling Groups with Terraform

AWS Autoscaling Groups are a great idea on paper, but can cause headaches (and often at the worst possible times) in practice due to either scaling too much or not enough. The biggest key for this is that you need to not only build out your ASG in Terraform, but also define the scaling policies, scaling boundaries, and know how to handle graceful termination and data storage. You also need to know what it looks like if Terraform expects one setup, but you’ve parked your resources for cost savings or suspended any ASG processes. This can be a challenge when you try to test your scaling policies, or if you don’t use ASGs the same way in development environments.

4. Adopt a “microservices” architecture with your configurations

Splitting your Terraform configuration into multiple files might seem like you’re just adding complexity, but this “microservices” approach can really help with management in large organizations. By making heavy use of output variables, you can coordinate configurations as needed, or you can keep things isolated for risk mitigation in case a configuration doesn’t do what you intended. Separate files also helps you keep track of what’s changing and where for audit logging purposes.

5. Create reusable modules specific to your organization

Along a similar line to number 4 above, creating smaller configurations can help you reuse code for different projects or teams. Reusable modules that are specific to what you do as a company can help accelerate deployment in the future, and can help with non-production workloads when developers want an AWS environment that is as close to production as possible.

Conclusion

Using Terraform on AWS can be a fantastic tool for defining your cloud infrastructure in an easily-deployable way, but can be daunting if you are trying to just get started or scale out to fit a larger enterprise. Use these tips to help save some frustration while making full use of the power of AWS!

About Chris Parlette

Chris Parlette is the Director of Cloud Solutions at ParkMyCloud. Chris helps customers reduce their cloud waste and manage their hybrid infrastructures by drawing on his years of experience working at various software startups. From SaaS to on-prem, virtualization to cloud, monitoring tools to cloud management platforms, and small businesses to large enterprises, Chris has seen it all and loves helping drive improvements to IT management. Chris earned a BS in Computer Science from the University of Maryland. He and his wife, Megan, reside in Silver Spring, MD.

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