Why DynamoDB with Serverless Framework?
DynamoDB plays really well with Serverless Framework and AWS Lambda. Why? Both DynamoDB and AWS Lambda are serverless services meaning that both of them are billed based on your usage. Moreover, AWS enables a set of integrations between them including DynamoDB Streams which are consumable by Lambda functions. Both services can be deployed in a multi-region fashion, and you don't have to worry about managing, patching or maintaining either of these two.
Step 1 - Prerequisites
Make sure you have:
You should be able to run the following commands without any issues:
Step 2 - Create new Serverless Framework project
Serverless Framework provides a set of templates for a variety of platforms and languages. For this tutorial, we're going to use
It should create the following file structure:
Step 3 - Provision necessary infrastructure
Go ahead and open
serverless.yml file. This is the file that defines our cloud-native application. We need to add a DynamoDB Table definition here. You can either use our DynamoDB Table Designer tool or use following example table definition. Paste that at the end of
But, that's not all. We have our DynamoDB table, but we don't have:
- Reference to that table
- IAM permission to let Lambda query and mutate this table
The first one is fairly easy. Simply add following lines to the
provider to supply table name as environment variable to all tables, or at
function level to pass it just to one table.
Second one is a bit more complex. Since we want to follow the principle of least privilege and don't want to give the Lambda permission to manipulate all the DynamoDB tables but only this particular one. We need to use a combination of
Fn::GetAtt intrinsic function and listing applicable IAM actions in
iamRoleStatements block nested inside
Step 4 - Application Code
Now, let's get to actual Lambda functions - our business logic. In this project, our API will have only three CRUD functionalities:
- Create Animal
- Get Animals
- Delete Animal
Go ahead, an open
handler.js file, delete everything inside and include following require statement at the top:
Don't worry that you don't have
aws-sdk installed locally. AWS-SDK is available in the AWS Lambda environment so you don't have to bundle it with your deployment artifact.
serverless.yml, add our
createAnimal function definition. It will be invoked on
POST animals request. You may also add other properties like
handler.js paste following lines of code.
It's pretty straightforward, we create
newAnimal object based on parameters from the body of the POST request, save that to the database, and return the newly created entity with status code 200.
Get Many Function
The function responsible for returning a collection of our animals is pretty similar to the create one:
When it comes to the logic, it's quite simple. We're running a Scan operation against DynamoDB to get the list of our records.
Lastly, the delete function is also similar. The only difference here is that the
path which includes
:name variable, uses
Once again, the logic is quite simple. We delete an entity with key
name which equals to our path parameter.
If you don't know how to create DynamoDB queries because its complicated syntax, use our DynamoDB Query Builder.
Step 5 - Deploy & Test
Deploying your project to the cloud is as easy as executing the following command:
It should output the URL of your endpoint. Copy it, and fire a request to check if it works correctly. If it does, then congrats! You've just deployed a production-ready, cloud-native API with Serverless Framework and DynamoDB!
Bonus - Our proven boilerplate
If you want to use something a bit more sophisitcated which follows many of the best practices, we've prepared a battle-tested Serverless Framework boilerplate for you.
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