Use MongoDB Connection Pool on AWS Lambda
In this post, we’ll show you how to use MongoDB connection pooling on AWS Lambda using both Node.js and Java drivers.
What is AWS Lambda?
AWS Lambda is an event-driven, serverless computing service provided by Amazon Web Services. It allows a user to run code without any of the administrative tasks, unlike that of EC2 instances where a user is responsible for provisioning servers, scaling, high availability, etc. Instead, you only have to upload the code and set up the event trigger, and AWS Lambda automatically takes care of everything else.
AWS Lambda supports various runtimes, including Node.js, Python, Java, and Go. It can be directly triggered by AWS services like S3, DynamoDB, Kinesis, SNS, etc. In our example, we use the AWS API gateway to trigger the Lambda functions.
What is a Connection Pool?
Opening and closing a database connection is an expensive operation since it involves both CPU time and memory. If an application needs to open a database connection for every operation, then that will have a severe performance impact.
What if we have a bunch of database connections that are kept alive in a cache? Whenever an application needs to perform a database operation, it can borrow a connection from the cache, perform the required operation, and give it back. By using this approach, we can save the time required for establishing a new connection every time and reuse the connections. This cache is known as the connection pool.
Node.js Driver MongoDB Connection Pool
For the Node.js driver, declaring the connection variable in global scope will also do the trick. However, there is a special setting without which connection pooling is not possible. That parameter is callbackWaitsForEmptyEventLoop which belongs to Lambda’s context object. Setting this property to false will make AWS Lambda freeze the process and any state data. This is done soon after the callback is called, even if there are events in the event loop.
Here’s the code to enable the MongoDB connection pool using the Node.js driver in the AWS Lambda handler function:
What is Cold Start Time?
Cold start time refers to the time taken by the AWS Lambda function for initialization. When the Lambda function receives its first request, it will initialize the container and the required process environment. In the above graphs, the response time of request 1 includes the cold start time, which significantly differs based on the programming language used for the AWS Lambda function.
What Happens to AWS Lambda Function During Inactivity?
In our testing, we also observed that AWS Lambda hosting containers were stopped when they were inactive for a while. This interval varied from 7 to 20 minutes. So, if your Lambda functions are not used frequently, then you need to consider keeping them alive by either firing heartbeat requests or adding retries on the client-side.
AWS Lambda Connection Pooling Conclusion
Lambda functions are stateless and asynchronous, and by using the database connection pool, you will be able to add a state to it. However, this will only help when the containers are reused, allowing you to save a lot of time. Connection pooling using AWS EC2 is easier to manage because a single instance can track the state of its connection pool without any issue. Thus, using AWS EC2 significantly reduces the risk of running out of database connections. AWS Lambda is designed to work better when it can just hit an API and doesn’t have to connect to a database engine.
