When it comes to operating Lambda, we often want to configure alarms to alert us when things aren’t running smoothly. Naturally our first choice for Lambda alarms is CloudWatch, the default monitoring service that comes with AWS.
CloudWatch gives us some custom metrics out-of-the-box, such as: errors and invocation rates. But there are some problems we run into when setting up alarms based directly on these metrics.
By the end of this article you’ll understand why alarms based on default AWS Lambda Metrics can cause difficulty, how AWS Metric Math helps us to apply “context” in our alarms and make them more effective, and how to setup an alarm using metric math to calculate an error rate percentage.
Recently, Terraform dropped an interesting new extension to their Terraform toolchain: the Terraform CDK. The new CDK allows you to write Terraform using TypeScript and Python — neat! But is the CDK as good as it seems?
I wanted to jump in to uncover the truth and understand whether writing Terraform in TypeScript really is the future, or whether it’s just another fad.
By the end of this article you’ll understand what the Terraform CDK is, how it works, and ultimately help answer the question: should you use it?
Recently I find myself in the position of applying monitoring to existing software applications quite often. Whilst I have been applying the monitoring tools, I noticed that I follow the same steps each time…
Which got me thinking: “Could you create a ‘recipe’ or ‘cookbook’ for how to apply monitoring to an existing software application?”. I set to work writing this article, and I can conclude, the answer is: yes!
By the end of this article you’ll know the 5 steps you should take when setting up monitoring on an existing service.
Are you creating a lambda function? Are you currently debugging wondering where you can access the output of your
Understanding how logs work is a common confusion area when working with AWS Lambda. Today, we’re going to clear up the confusion and get your hands on your AWS Lambda logs so that you can start to debug your Lambda function.
By the end of this article you’ll understand how and where console.log output goes from an AWS Lambda function, and also how to debug your AWS Lambda setup if you’re still not seeing log output.
Are you looking to create a basic AWS instance web server? Maybe you’re learning AWS, trying to get an understanding on Terraform or actually trying to get a pieceof your infrastructure setup. Whatever your reason for needing a simple AWS web server setup, that’s what we’ll be covering today.
Today we’ll walk through (in detail) how to create the simplest possible EC2 web server on AWS using Terraform. We’ll cover all of the fiddly AWS details like AMI’s and user data scripts.
By the end of this article you’ll know how to create a simple Apache based web server on AWS EC2 written in Terraform.
When it comes to working with Serverless and AWS Lambda there are many different tools and approaches to choose from. You may have heard about a few already and might be wondering about the differences. To be quite frank with you—there were some aspects I wasn’t event totally sure of myself.
Working with Serverless requires overcoming a few obstacles: How to run your functions locally? How to create your infrastructure? How to deploy your applications? Today we’ll take a look at five main serverless approaches that attempt to help with these obstacles: manually configuring, using Serverless Framework, Terraform, CloudFormation, and SAM.
By the end of this article you should understand what the main approaches to Serverless are and when to consider using them.
Are you looking to learn Serverless but need a little help in where to start? One of the best ways to get your head around a new technology is to dive in and build some example projects. But what are some nice and simple serverless beginner projects?
In today’s article we’ll go through three different simple examples of serverless functions you can build using AWS Lambda for your first trial with serverless.
By the end of this article you should have an overview of three serverless beginner projects, the steps you’d need to create them, and some ways that you can later extend them to learn more.
Ah Serverless… it’s the golden child of software engineering right now, and the internet is full of Serverless and AWS Lambda success stories. But actually the golden child of software engineer is harbouring a few secrets…
Yep, that’s right, Serverless isn’t as good as the marketing pages lead you to believe. That’s not to say Serverless is bad technology — I absolutely love Serverless. But on a few occasions whilst working with it, I felt kinda duped.
By the end of this article you’ll understand some of the limitations of AWS Lambda and how some features like, DDOS and memory leaks really work.
So you’re new to AWS Lambda and secrets management? Maybe you’ve just joined a team that’s using KMS and you want to know more about how KMS and Lambda work, or maybe you’re looking to use KMS as your preferred choice for Lambda secrets management.
Whatever your reasoning for investigating AWS KMS with Lambda, today we’re going to cover the in’s and out’s of how the two technologies work together, and show you how you can use them.
By the end of this article you’ll understand what KMS is, how KMS works with AWS Lambda and the alternatives to using KMS for AWS Lambda functions.
Running Terraform in a CI Server can be incredibly useful when you’re trying to automate or experiment with cloud resources. One of the easiest, cheapest and most accessible setups I’ve found is using Github Actions and S3 for state.
But learning a new technology can be frustrating especially when the anxiety of: “Am I doing this right?” strikes. In this article I’ll walk you through how to get a Terraform project running in Github Actions from start to finish — with all the details you need to understand what’s happening and why.
By the end of this article you will have a running Terraform project on Github Actions using remote state.