aws-sdk VS aws-lambda-java-libs

From this GitHub issue and this one from 2021 it seems like AWS just doesn't care about this - so, asking here if anyone knows of a workaround (other than "just keep using v2"... that's not a long-term solution), or if any AWS devs can shed some light on the situation.

AWS SDKs

Please note that ECS Exec is supported via AWS SDKs, AWS CLI, as well as AWS Copilot. In the future, we will enable this capability in the AWS Console. Also, this feature only supports Linux containers (Windows containers support for ECS Exec is not part of this announcement).

Set up the AWS CLI and AWS SDKs.

One common pattern to integrate with AWS from a workflow job is to call additional services using the AWS CLI. Overall, this works well, but there are a few considerations one should note when doing so. First and foremost, a workflow job needs to know where the AWS CLI installed and how to use it. You can do this by either installing the AWS CLI on the host compute and bind mounting it into the container job, or including the AWS CLI as part of the container image. That said, see my notes above on keeping container images small for associated caveats. Second, while the AWS CLI is great for scripting, for more complex operations direct integration via the AWS SDK is a better fit.

I like how you can imagine what the Python implementation that uses this looks like from this structure. If there are no waiters for what you need, you can create an Issue in the AWS SDK repository because the service teams provide those. I tried that for DynamoDB Streams, and I'm curious to see how long it will take them to add that.

Amazon Simple Email Service (SES) is a serverless service for sending emails from your applications. Like other AWS services, you can send emails with SES using the AWS REST API or the AWS SDKs. In this article, I want to look at how to send emails using SES with TypeScript specifically.

In 2002, Jeff Bezos's so-called API Mandate forced all Amazon teams to expose their data and functionality through service interfaces. Amazon has built AWS around the same principles: every service is programmatically controllable, from starting a virtual machine to accessing a satellite. While this is an essential property of an effective cloud platform, it is not necessarily developer-friendly. By now, AWS has incrementally and significantly improved in this space. Besides using their APIs, we can control services and infrastructure with a unified Command Line Interface (CLI), Software Development Kits (SDK), CloudFormation, and, since July 2019, the AWS Cloud Development Kit (CDK). The CDK had a massive impact on developer productivity and satisfaction. While teams could already access and control services and infrastructure using the AWS SDK and their favorite programming language, infrastructure was primarily defined using incredible amounts of mostly punctuation marks and whitespace, also known as YAML or JSON. CDK — initially only flavored TypeScript and Python — finally gave developers an AWS-native means to define Infrastructure as actual Code. Since its introduction, AWS has added support for more languages, like Java, C#, and Go.

Yes, no AWS api to create users/groups: https://github.com/aws/aws-sdk/issues/25

Amazon Web Services (AWS) Lambda is a serverless function-as-a-service (FaaS) platform that lets you deploy, run, and scale code in the cloud as self-contained functions without having to manually configure any infrastructure. Lambda runs your functions on demand in response to specific events, such as an HTTP request from the internet or activity in another AWS service.

FaaS is specifically focused on building and running applications as a set of independent functions or microservices. Major cloud providers like AWS (Lambda), Microsoft Azure (Functions), and Google Cloud (Cloud Functions) offer FaaS platforms that allow developers to write and deploy individual functions without managing the underlying infrastructure.

So AWS Lambda is basically a serverless computing service that is offered by AWS. It enables developers to run the code in response to various events. It protects the developers from the pain of managing the servers. Using a serverless execution model helps the developers to handle provision, manage and scale the servers automatically. Through this approach the developers can fully focus on writing the code instead of dealing with other aspects.

The first product that popularized the term “serverless” was AWS Lambda, which is both the prototypical and archetypical function as a service provider. It also has a great name, which pings back to its envisioned place in the cloud of the future. In computer programming, a lambda, often referred to as a lambda function or lambda expression, is a concise way to represent an anonymous function, which is a function without a name. The concept originates from lambda calculus in mathematical logic and has been adopted by many programming languages, each with its own syntax and characteristics.

You can build a custom config rules in 2 ways, using AWS Lambda and CloudFormation Guard. Lambda gives you a lot of flexibility, but it also brings complexity of maintaining. CloudFormation Guard is a bit more lightweight in that regard. Yes, you still need to maintain the logic to determine when your resource is compliant or not. But you need to do this in both cases, thus my go to preference is CloudFormation Guard.

AWS Lambda: https://aws.amazon.com/lambda/

This blog details how you can use some key serverless components from AWS like Amazon Eventbridge, AWS Lambda, and Simple Notification Service to setup a system that will monitor your site (which can be running anywhere) and send emails, text messages, slack messages, and more when the reachability status of your site changes.

I use the OpenWeather API to receive the current temperature data by providing the latitude and longitude coordinates as query strings in the request. A Lambda function invokes the weather API and sends the current temperature value as a custom metric to CloudWatch. I then graph the temperature values on a dashboard and activate an alarm when the temperature sinks below zero degrees Celsius.

After two years, I moved to a Web3 startup where I was given a lead software engineer role. This new role gave me more hands-on experience with AWS, where I've learned to implement serverless technologies like Lambda and DynamoDB.