Learn how to build your project with internal AWS monitoring is hard to Grasp. Learm how a serverless monitoring solution can catch problems for you without the painful learning curve connected to serverless failure detection.
When building cloud-based systems and serverless systems, in particular, it’s crucial to stay on top of things. Your infrastructure will be miles away from you and not a device you hold in your hands like when you build a frontend. That’s why adding a monitoring solution to your stack, which offers a pre-configured serverless failure detection, should be one of the first decisions.
When deciding on a monitoring solution, it’s a good idea to check out if it brings adequate alerting features. When it comes to serverless, most of the time from a new incident to a fix is lost to finding the problem, not the actual troubleshooting. This means a monitoring solution can shrink the biggest chunk of that equation.
Serverless is all about outsourcing non-differentiating work to managed services. If you aren’t in the business of selling authentication software, don’t build authentication software; buy it from someone who makes their money from it; the chances are they have one or more teams working on the solution and it will outperform yours in a heartbeat.
As mentioned before, the challenge here is that you can’t look into these services. You use SQS, DynamoDB, or API Gateway, but you can’t directly monitor the servers these services are running on, let alone SSH into them to debug them. AWS has its own logging and tracing services in place. So you need to extract the data and set alarms there.
The problem with the AWS provided monitoring services is, they aren’t easy to use because they’re general solutions. CloudWatch doesn’t just log Lambda or SQS data; it logs all AWS services data. This can make it a bit fiddly to set the right alerts for all your services. A serverless system in constant flux to add new features, updates, and refactors requires you to meddle with these settings constantly.
Also, AWS monitoring solutions aren’t particularly frugal when it comes to what data they log. In a serverless system, your transactions usually span multiple services, all emitting large numbers of log lines. Combing through that amount of data costs time and, in turn, money. And more often than not, AWS Console just isn’t enough for serverless teams, especially when scaling.
Serverless Express enables you to easily host Express.js APIs on AWS Lambda and AWS HTTP API. Here is how to get started and deliver a Serverless Express.js based API with a custom domain, free SSL certificate and much more!
Adding Code to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker. With Docker, we have three ways to add code to Lambda that isn’t directly part of our Lambda function. Try to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker.
Serverless Proxy with AWS API Gateway and AWS Lambda. We can communicate between Public and Private instance via a Serverless Proxy thanks to AWS Api Gateway and AWS Lambda. Github Webhook calls a Public API Gateway, API Gateway triggers a Lambda attached to VPC.
Serverless Framework: Use AWS S3 Object Lambda to resize images on the fly. I will show you how to use AWS S3 Object Lambda to resize images on the fly. The Serverless Framework will be used to define the Infrastructure as Code and to simplify the deployment.
A Deep Dive into Serverless Tracing with AWS X Ray & Lambda. Over the past few weeks I’ve been experimenting with building a Serverless API on AWS with the goal of having everything needed to run a production system. One necessary piece was distributed tracing. While I’d seen a bit of what some non-AWS options had to offer, the extra cost of the services themselves, along with actually getting the data to them, was a bit prohibitive for what I imagined should be possible (and cheaper) with only AWS, which brought me to X Ray.