10 AWS Naming Convention Best Practices
AWS naming conventions are important for keeping your resources organized and easy to find. Here are 10 best practices to follow.
Naming conventions are important in any cloud environment, but they are especially important in AWS. This is because AWS resources can be spread across multiple regions and accounts, making it difficult to keep track of everything without a consistent naming scheme.
There are many different ways to name your AWS resources, but there are a few best practices that you should keep in mind. In this article, we will discuss 10 AWS naming convention best practices that you should follow in order to keep your AWS environment organized and easy to manage.
1. Use a naming convention that is easy to understand
When you have a consistent naming convention, it is much easier to understand what each resource is used for. This is especially important when you have a large number of resources, or when you are working with other people who are not familiar with your AWS environment.
A good naming convention should be intuitive and easy to remember. It should also be flexible enough to accommodate future changes. For example, you might want to include the environment (e.g. development, staging, production) in the name of each resource.
Finally, make sure to document your naming convention so that everyone on your team is aware of it.
2. Avoid using names that are too long or complicated
When you use long or complicated names for your AWS resources, it can make it difficult for other people to understand what they are and what they do. This can lead to confusion and frustration, and can even cause people to make mistakes when working with them.
It’s much better to use short, descriptive names that are easy to remember and understand. This will make it easier for everyone to work with your AWS resources, and will help avoid any potential problems.
3. Keep the name short and simple
When you’re working in the AWS console, you’re constantly typing in names of resources. If the name is too long or complex, it’s going to be a pain to constantly type it out. Not only that, but if you have to share the name with someone else, it’s going to be even more difficult for them to remember and type it out correctly.
It’s also important to keep the name simple because it will be easier to read when looking at a list of resources. If the name is too long or complex, it will be more difficult to scan through and find the resource you’re looking for.
Finally, keeping the name short and simple will make it less likely that you’ll make a mistake when creating or deleting a resource. If you accidentally delete a resource with a long and complex name, it might be difficult to remember what it was so you can recreate it.
4. Make sure you can easily remember what it means
If you can’t remember what it means, then chances are good that someone else on your team won’t be able to either. This can lead to confusion and frustration, and ultimately cause people to start ignoring the convention altogether.
A good naming convention should be intuitive and easy to remember. A good way to achieve this is by using abbreviations that are easily recognizable. For example, using “AWS” for Amazon Web Services is a good abbreviation that everyone on your team will be able to understand.
Another important AWS naming convention best practice is to be consistent. Once you’ve decided on a convention, make sure you stick to it. This will help to avoid confusion and ensure that everyone on your team is on the same page.
5. Don’t use special characters in your AWS resource names
When you use special characters in your AWS resource names, it can cause problems when you try to automate tasks using the AWS CLI or SDKs. That’s because the AWS CLI and SDKs treat special characters as delimiters, so they can’t properly parse resource names that contain them.
This can lead to unexpected results, or even errors, when you try to run commands on those resources. For example, if you have an S3 bucket named “my-bucket-1”, and you try to run the “aws s3 ls” command on it, you’ll get an error because the AWS CLI interprets the hyphen as a delimiter.
To avoid these problems, simply don’t use special characters in your AWS resource names. Use letters, numbers, and underscores instead.
6. Don’t use spaces in your AWS resource names
When you use spaces in your resource names, AWS automatically replaces them with plus signs (+). This can cause problems down the road because some software and programming languages don’t recognize plus signs as spaces. As a result, your resources might not be able to communicate with each other properly, which can lead to all sorts of issues.
To avoid this problem, simply don’t use spaces in your resource names. If you need to separate words, use underscores (_) or dashes (-) instead.
7. Use lowercase letters for all of your AWS resources
When you use lowercase letters for your AWS resources, it’s much easier to manage and organize them. For example, if you have two Amazon S3 buckets with the same name but one is all lowercase and the other is mixed case, they will show up as two different buckets in the AWS console.
It can also be helpful to use dashes (-) or underscores (_) to separate words in your resource names. This makes it even easier to read and understand what your resources are at a glance.
Overall, using lowercase letters for your AWS resources is a best practice that will save you time and frustration in the long run.
8. Use hyphens instead of underscores in your AWS resource names
While both hyphens and underscores are valid characters in AWS resource names, hyphens are the recommended character. The main reason for this is that some software applications (such as Hadoop) treat hyphens and underscores differently.
Specifically, when using Hadoop with Amazon S3, if you use an underscore in your S3 bucket name, Hadoop will not be able to read files from that bucket. On the other hand, if you use a hyphen in your bucket name, Hadoop will have no problem reading files from the bucket.
So, to avoid any potential compatibility issues, it’s best to use hyphens instead of underscores in your AWS resource names.
9. Be consistent with your naming conventions
If you’re not consistent with your naming conventions, it will be difficult for others (and yourself) to understand what resources are related to each other. For example, if you have an Amazon S3 bucket named “my-bucket” and an Amazon DynamoDB table named “MyTable”, it’s not immediately clear that the two resources are related.
On the other hand, if you’re consistent with your naming conventions, it’s easy to see that the two resources are related. For example, if you have an Amazon S3 bucket named “my-bucket” and an Amazon DynamoDB table named “my-table”, it’s immediately clear that the two resources are related.
Being consistent with your AWS naming conventions will also make it easier to automate tasks using scripts or tools. For example, if you want to delete all resources associated with a particular project, you can easily do so if all of the resources have the same prefix (e.g. “project-name”).
Finally, being consistent with your AWS naming conventions will make it easier to comply with corporate governance policies. For example, if your company has a policy that requires all resources to be tagged with the name of the owner, it will be much easier to compliance with this policy if all resources have the same naming convention.
10. Use tags to add more information about your AWS resources
Tags are metadata that you can add to your AWS resources. They are key-value pairs that help you categorize and organize your resources. You can use tags to control access, track costs, and identify resources for different purposes.
One of the benefits of using tags is that they are easy to add and manage. You can add tags when you create a resource or you can add them later. You can also edit and delete tags as needed.
Another benefit of tags is that they are flexible. You can use them to add any information that you think will be helpful in identifying and managing your resources.
Finally, tags are cost-effective. They don’t cost anything to create or maintain, and they can help you save money by helping you optimize your use of AWS resources.