I was recently working on a serverless api that uses serverless offline, express.js and mongodb.
We started getting emails from MongoDB Atlas telling us that we ran out of connections.
Logging is very important to developers as it helps us more efficiently debug a system in production and the steps that led to the occurrence of the bug.
In this post, we look at ways to make logging better.
Having your application / system produce the right amount and quality of logs is just as important as having the system process the needed data because it helps make debugging easier and allows us to better optimize data.
Logging on AWS lambda can be really costly if it’s not done correctly.
Developing locally makes a lot more sense than deploying to a dev environment consistently because it helps save time, save some cloud costs, and avoids obvious embarrassment. 🙂
AWS CloudWatch is a monitoring solution that’s provided by Amazon Web Services. It’s really a big service that contains a large collection of monitoring tools.
To write to Amazon S3 from an AWS Lambda function in Node.js, you can use the AWS SDK for JavaScript in Node.js.
The pay per use pricing model of function as a service makes it appear to be really cheap. For a lot of workloads, it is really a lot cheaper and maybe even free. There’s a lot of costs that can quickly add up and surprise businesses.
The serverless default for CloudWatch Logs is to keep the logs forever. CloudWatch Logs are pretty expensive to keep around indefinitely. In the serverless.yml file, we’re able to set how long the cloudwatch logs are kept for. I recommend keeping them for at least 7 days but 30 days is probably more ideal.
In late 2014, AWS Lambda launched and has grown in widespread use since then. AWS lambda is a serverless computing technology which has been a game change for software development.
AWS Lambda is a service that makes it easy to build small scalable applications. Lambdas are small functions that are packaged up and sent to AWS. Using a framework like the serverless framework makes it fairly easy to work with and pretty efficient.
Lambda is event driven. It works by responding to events whether they be timed, API driven or responding to events within AWS. One of the most common examples of using lambda is to resize images that have been uploaded to an S3 bucket.
Lambda is stateless meaning that every time a function is triggered, it is a completely new environment.
There’s so many reasons to use AWS Lambda. It’s easy to get started with it, it’s massively flexible, it is very scalable and more. …
In the ten years or so that I have been programming professionally, there’s been significant changes to the way we did things whether it be the way we developed software, the way we managed software, or the environments we used to execute our code. Over time, these changes have become increasingly more and more dramatic to the point where it’s now possible to run a company and maintain almost no actual servers.
For the last 18 months or so, I have been working with “serverless computing” which is an incredibly encompassing buzzword for a lot of different technologies and techniques.
Serverless computing is a very large break from the traditional way we developed software and deployed software to servers. Serverless computing is basically an architecture where code is stored and executed by a fully managed provider.…
