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.
I remember staring at the AWS Lambda console for the first time and feeling overwhelmed. There were so many things happening: qualifiers, actions, triggers, permissions. It’s like the cockpit of a fighter jet in there. And with new features the Lambda interface has only become more complicated.
But when you understand the different parts of the AWS Lambda console and everything you can achieve with Lambda it opens up your perspective and builds your confidence. When you know what all the parts do you can then focus your attention only on the features that matter for you.
By the end of this article you will be more confident using AWS Lambda after we explore and understand the AWS Lambda console.
Have you ever wondered what a queue is or how you could implement a queue in AWS? Perhaps you’re considering using a queue for a solution that you’re working on but you’re not fully sure how the pieces fit together?
If that’s you — you’re in the right place! Today we’ll remove the mysticism of queues in AWS. But how will we remove the mysticism? By walking step-by-step for how to configure an SQS queue and use Lambda to process it.
By the end of this article you’ll understand what a queues is, why you might need one and how to setup one up SQS and Lambda.
We’ve talked a lot recently about infrastructure as code and setting up cloud environments. But nothing beats getting hands on with a technology to help learning. A workflow I’ve used a lot recently is Terraform (and remote state) using a Github Actions pipeline. It’s cheap, straight-forward and a great little workflow for creating cloud resources. Today, let me show you why.
So I thought setting up a basic workflow for creating a website would be a great hands-on way to get your head around some different topics: AWS, Terraform and Github Actions. Today we’ll go through how to setup an S3 bucket (which could function as a website) in AWS and use a Github Actions pipeline to create the infrastructure and upload our files.
By the end of this article you’ll know how to configure an AWS S3 bucket using Terraform and deploy it using Github Actions.
AWS (Amazon Web Services) is overwhelming. If you’re new to AWS you’ll know all too well the feeling of being lost and not knowing where to start. Today, we’re going to change that. We’re going to clear the mist of uncertainty and discuss everything you need to know to begin your learning journey on AWS.
Today we’ll talk about three things that will help you start learning AWS. And they are: focusing on the core services, getting hands-on and structuring your learning. We’ll go through each area in a decent amount of detail, so that you have a great starting point for your learning.
By the end of this article you’ll have an understanding of the core services of AWS, how to structure your learning around them and how to get up and running with some hands on experimentation.
Your AWS Lambda code is throwing errors in production. To defuse the situation, you need to pinpoint what’s going wrong and find the fix. It’s a good thing you already instrumented your Lambda with high quality, well structured logs, right?
There are many aspects to monitoring a distributed system. And a big part is understanding how, and what to log. But, fear not, you’re in the right place!
Today we’re going to talk about the first step: how you can get Lambda logs into CloudWatch for analysis. Once we’ve discussed that, in the next article, we’ll discuss how to analyse those logs to properly extract the data.
By the end of this article you’ll understand the three steps you’ll need to take to enable CloudWatch logging for a Lambda function.