DEV Community

Cover image for Taming Cloud Costs with Infracost
Tomas Fernandez for Semaphore

Posted on • Originally published at semaphoreci.com

Taming Cloud Costs with Infracost

Photo by Mathieu Stern on Unsplash

When we combine the cloud with IaC tools like Terraform and continuous deployment we get the almost magical ability to create resources on demand. For all its benefits, however, the cloud has also introduced a set of difficulties, one of which is estimating cloud costs accurately.

Cloud providers have complex cost structures that are constantly changing. AWS, for example, offers 536 types of EC2 Linux machines. Many of them have similar names and features. Take for example "m6g.2xlarge" and "m6gd.2xlarge" — the only difference is that the second comes with an SSD drive, which will add $60 dollars to the bill. Often, making a mistake in defining your infrastructure can cause your bill to balloon at the end of the month.

Man in front of a blackboaard filled with equations. The text says: Calculating AWS Resources Cost
It’s so easy to go above budget.

We can set up billing alerts, but there are no guarantees that they will work. Alerts can happen during the weekend or be delayed, making us shoot past our budget in a few hours.

So, how can we avoid this problem and use the cloud with confidence?

Enter Infracost

Infracost is an open-source project that helps us understand how and where we’re spending our money. It gives a detailed breakdown of actual infrastructure costs and calculates how changes impact them. Basically, Infracost is a git diff for billing.

Infracost has two versions: a VSCode addon and a command line program. Both do the same thing: parse Terraform code, pull the current cost price points from a cloud pricing API, and output an estimate.

How Infracost works. It reads code from the repository and pulls the appropriate service costs from an API service. The IDE version prints the estimates on the screen while editing. The CLI version prints the result in the terminal, posts comments on GitHub, Bitbucket, or Gitlab, and can stop a CI/CD deployment if limits are exceeded.
You can use Infracost pricing API for free or host your own. The paid tier includes a cloud dashboard to track changes over time.

We can see the estimates right in the IDE:

A GIF showing how Infracost shows cost estimates in real-time as a developer changes a Terraform file.
Real-time cost estimation on VSCode.

Or as comments in pull requests or commits:

A GitHub Pull Request conversation showing an automated message from Infracost with the cost estimate.
Cost change information in the PR.

Infracost also has an optional Infracost Cloud, which comes with a paid tier and includes features like Jira integration, custom price books, and a dashboard to keep track of costs over time.

The Infracost paid dashboard showing how costs change over time.
The paid tier includes a dashboard to track spending over time.

Setting up Infracost

To try out Infracost, we’ll need the following:

  • An Infracost API key. You can get one by signing up for free at Infracost.io.
  • The Infracost CLI installed in your machine.
  • Some Terraform files.

Once the CLI tool is installed, run infracost auth login to retrieve the API key. Now we’re ready to go.

The first command we’ll try is infracost breakdown. It analyzes Terraform plans and prints out a cost estimate. The --path variable must point to the folder containing your Terraform files. For example, imagine we want to provision an "a1.medium" EC2 instance with the following:



provider "aws" {
 region = "us-east-1"
 skip_credentials_validation = true
 skip_requesting_account_id = true
}

resource "aws_instance" "myserver" {
 ami = "ami-674cbc1e"
 instance_type = "a1.medium"

 root_block_device {
 volume_size = 100
 }
}


Enter fullscreen mode Exit fullscreen mode

At current rates, this instance costs $28.62 per month to run:



$ infracost breakdown --path .

 Name Monthly Qty Unit Monthly Cost

 aws_instance.myserver
 ├─ Instance usage (Linux/UNIX, on-demand, a1.medium) 730 hours $18.62
 └─ root_block_device
 └─ Storage (general purpose SSD, gp2) 100 GB $10.00

 OVERALL TOTAL $28.62


Enter fullscreen mode Exit fullscreen mode

If we add some extra storage (600GB of EBS), the cost increases to $155.52, as shown below:



$ infracost breakdown --path .

 Name Monthly Qty Unit Monthly Cost

 aws_instance.myserver
 ├─ Instance usage (Linux/UNIX, on-demand, a1.medium) 730 hours $18.62
 ├─ root_block_device
 │ └─ Storage (general purpose SSD, gp2) 100 GB $10.00
 └─ ebs_block_device[0]
 ├─ Storage (provisioned IOPS SSD, io1) 600 GB $75.00
 └─ Provisioned IOPS 800 IOPS $52.00

 OVERALL TOTAL $155.62


Enter fullscreen mode Exit fullscreen mode

Infracost can also calculate usage-based resources like AWS Lambda. Let's see what happens when we swap the EC2 instance for serverless functions:



provider "aws" {
 region = "us-east-1"
 skip_credentials_validation = true
 skip_requesting_account_id = true
}

resource "aws_lambda_function" "my_lambda" {
 function_name = "my_lambda"
 role = "arn:aws:lambda:us-east-1:account-id:resource-id"
 handler = "exports.test"
 runtime = "nodejs12.x"
 memory_size = 1024
}


Enter fullscreen mode Exit fullscreen mode

Running infracost breakdown yields a total cost of 0 dollars:



$ infracost breakdown --path .

 Name Monthly Qty Unit Monthly Cost

 aws_lambda_function.my_lambda
 ├─ Requests Monthly cost depends on usage: $0.20 per 1M requests
 └─ Duration Monthly cost depends on usage: $0.0000166667 per GB-seconds

 OVERALL TOTAL $0.00


Enter fullscreen mode Exit fullscreen mode

That can’t be right unless no one uses our Lambda function, which is precisely what the tool assumes by default. We can fix this by providing an estimate via a usage file.

We can create a sample usage file with this command:

$ infracost breakdown --sync-usage-file --usage-file usage.yml --path .

We can now provide estimates by editing usage.yml. The following example consists of 5 million requests with an average runtime of 300 ms:




resource_usage:
 aws_lambda_function.my_lambda:
 monthly_requests: 5000000 
 request_duration_ms: 300 



Enter fullscreen mode Exit fullscreen mode

We’ll tell infracost to use the usage file with --usage-file to get a proper cost estimate:



$ infracost breakdown --path . --usage-file usage.yml

 Name Monthly Qty Unit Monthly Cost

 aws_lambda_function.my_lambda
 ├─ Requests 5 1M requests $1.00
 └─ Duration 1,500,000 GB-seconds $25.00

 OVERALL TOTAL $26.00


Enter fullscreen mode Exit fullscreen mode

That’s much better. Of course, this is accurate as long as our usage file is correct. If you’re unsure, you can integrate Infracost with the cloud provider and pull the utilization metrics from the source.

Git diff for cost changes

Infracost can save results in JSON by providing the --format json and --out-file options. This gives us a file we can check in source control and use as a baseline.

$ infracost breakdown --path . --format json --usage-file usage.yml --out-file baseline.json

We can now compare changes by running infracost diff. Let’s see what happens if the Lambda execution time goes from 300 to 350 ms:



$ infracost diff --path . --compare-to baseline.json --usage-file usage.yml

~ aws_lambda_function.my_lambda
 +$4.17 ($26.00 → $30.17)

 ~ Duration
 +$4.17 ($25.00 → $29.17)

Monthly cost change for TomFern/infracost-demo/dev
Amount: +$4.17 ($26.00 → $30.17)
Percent: +16%


Enter fullscreen mode Exit fullscreen mode

As you can see, the impact is a 16% increase.

Integrating Infracost with CI/CD

We’ve seen how this tool can help us estimate cloud costs. That’s valuable information, but what role does Infracost take in continuous integration? To answer that, we must understand what infracost comment does.

The comment command takes a JSON file generated by infracost diff and posts its contents directly into GitHub, Bitbucket, or Gitlab. Thus, by running Infracost inside CI, we make relevant cost information available to everyone on the team.

An automated comment on GitHub with cost differences caused by the commit.
Infracost comment on the cost difference in a GitHub commit.

If you want to learn how to setup CI/CD with Infracost, check out this tutorial: Running Infracost on CI/CD.

Working with monorepos

You will likely have separate Terraform files for each subproject if you work with a monorepo. In this case, you should add an infracost config file at the project's root. This allows you to specify the project names and where Terraform and usage files are located. You can also set environment variables and other options.



version: 0.1

projects:
 - path: dev
 usage_file: dev/infracost-usage.yml
 env:
 NODE_ENV: dev

 - path: prod
 usage_file: prod/infracost-usage.yml
 env:
 AWS_ACCESS_KEY_ID: ${PROD_AWS_ACCESS_KEY_ID}
 AWS_SECRET_ACCESS_KEY: ${PROD_AWS_SECRET_ACCESS_KEY}
 NODE_ENV: production


Enter fullscreen mode Exit fullscreen mode

When the config file is involved, you must replace the --path argument with --config-file in all your commands.

Establishing policies

One more trick Infracost has up its sleeve is enforcing policies. Policies are rules that evaluate the output of infracost diff and stop the CI pipeline if a resource goes over budget. This feature allows managers and team leads to enforce limits. When the policy fails, the CI/CD pipeline stops with an error, preventing the infrastructure from being provisioned.

A pull request on GitHub with a warning that a policy has been broken.
When a policy is in place, Infracost warns us if any limits are exceeded.

Infracost implements policies using Open Policy Agent (OPA), which uses the Rego language to encode policy rules.

Rego has a ton of features, and it’s worth digging in to learn it thoroughly, but for our purposes, we only need to learn a few keywords:

  • deny[out] defines a new policy rule that fails if the out object has failed: true
  • msg: defines the error message shown when the policy fails.
  • out: defines the logic that makes the policy pass or fails.
  • input: references the contents of the JSON object generated with infracost diff.

The following example shows a policy that fails when the total budget exceeds $1,000:



# policy.rego

package infracost

deny[out] {

 # define a variable
 maxMonthlyCost = 1000.0

 msg := sprintf(
 "Total monthly cost must be less than $%.2f (actual diff is $%.2f)",
 [maxMonthlyCost, to_number(input.totalMonthlyCost)],
 )

 out := {
 "msg": msg,
 "failed": to_number(input.totalMonthlyCost) >= maxMonthlyCost
 }
}


Enter fullscreen mode Exit fullscreen mode

This is another example that fails if the cost difference is equal to or greater than $500.



package infracost

deny[out] {

 # maxDiff defines the threshold that you require the cost estimate to be below
 maxDiff = 500.0

 msg := sprintf(
 "Total monthly cost diff must be less than $%.2f (actual diff is $%.2f)",
 [maxDiff, to_number(input.diffTotalMonthlyCost)],
 )

 out := {
 "msg": msg,
 "failed": to_number(input.diffTotalMonthlyCost) >= maxDiff
 }
}


Enter fullscreen mode Exit fullscreen mode

You can experiment and try several examples online on the OPA playground.
To enforce a policy, you must add the --policy-path option in any of the infracost comment commands like this:



curl -fsSL https://raw.githubusercontent.com/infracost/infracost/master/scripts/install.sh | sh
checkout
infracost diff --path . --usage-file usage.yml --compare-to baseline.json --format json --out-file /tmp/infracost-diff-commit.json
infracost comment github --path=/tmp/infracost-diff-commit.json --repo=$SEMAPHORE_GIT_REPO_SLUG --commit=$SEMAPHORE_GIT_SHA --github-token=$GITHUB_API_KEY --policy-path policy.rego --behavior=update

Enter fullscreen mode Exit fullscreen mode




Conclusion

The power to spin up resources instantly is a double-edged knife: a typo in a Terraform file can be a costly mistake. Staying proactive when managing our cloud infrastructure is essential to sticking to the budget and avoiding nasty surprises at the end of the month. If you’re already automating deployment with continuous deployment and managing services with Terraform, you may as well add Infracost to the mix to make more informed decisions and impose spending limits. Setting this up takes only a few minutes and can save thousands of dollars down the road.

Top comments (0)