Author: Abhishek Gupta

It's hard to operate stateful distributed systems at scale and Redis is no exception. Managed databases make life easier by taking on much of the heavy lifting. But you still need a sound architecture and apply best practices both on the server (Redis) as well as the client (application).

This blog covers a range of Redis-related best practices, tips and tricks including cluster scalability, client-side configuration, integration, metrics etc. Although I will be citing Amazon MemoryDB and ElastiCache for Redis from time to time, most (if not all) will be applicable to Redis clusters in general.

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One of the key components of microservices is how to manage and access data. The means to do that are different compared to traditional monolithic or three-tier applications. Some patterns are quite common, but others are specific and need to be evaluated before being incorporated into a solution. We will briefly go over some of these common database patterns for microservices before exploring CQRS (including how it differs from CRUD) and, finally, look at how it can be combined with event sourcing.

Earlier, I covered a Serverless URL shortener application on AWS using DynamoDB, AWS Lambda and API Gateway.

In this blog post, we will deploy that as a REST API on AWS App Runner and continue to use DynamoDB as the database. AWS App Runner is a compute service that makes it easy to deploy applications from a container image (or source code), manage their scalability, deployment pipelines, and more.

Constructs are the fundamental building block of cdk8s (Cloud Development Kit for Kubernetes) - an open-source framework (part of CNCF) with which you can define your Kubernetes applications using regular programming languages (instead of yaml). In Getting started with cdk8s, you saw how to use the core cdk8s library.

You can also use the cdk8s-plus library (also covered this in a previous blog) to reduce the amount of boilerplate code you need to write. With cdk8s-plus, creating a Kubernetes Deployment, specifying its container (and other properties) and exposing it via a Service is three function calls away?

This blog post covers how to build a Serverless URL shortener application using Go. It leverages AWS Lambda for business logic, DynamoDB for persistence, and API Gateway to provide the HTTP endpoints to access and use the application. The sample application presented in this blog is a trimmed-down version of bit.ly or other solutions you may have used or encountered.

It's structured as follows:

cdk8s (Cloud Development Kit for Kubernetes) is an open-source framework (part of CNCF) using which you can define your Kubernetes applications with regular programming languages (instead of yaml). Some of the previous blogs on this topic covered the getting started experience and using cdk8s-plus library to further improve upon the core cdk8s library features. We are going to continue and push cdk8s even further.
This blog post will demonstrate how you can use Kubernetes Custom Resource Definitions with cdk8s. We will start off with a simple Nginx example and then you will use the combination of Strimzi project CRDs along with Go  cdk8s to define and deploy a Kafka cluster on Kubernetes!

I am assuming that you've have some knowledge of Kubernetes Custom Resource Definitions and have probably even used a few in the form of Operators. If not, that's ok! The Kubernetes documentation covers it quite well. You can always refer to it, come back here and follow along!

This blog post will help you get quickly started with DynamoDB Streams and AWS Lambda using Go. It will cover how to deploy the entire solution using AWS CDK.

The use case presented here is pretty simple. There are a couple of DynamoDB tables and the goal is to capture the data in one of those tables (also referred to as the source table) and replicate them to another table (also referred to as the target table) so that it can serve different queries. To demonstrate an end-to-end flow, there is also an Amazon API Gateway that front ends a Lambda function which persists data in the source DynamoDB table. Changes in this table will trigger another Lambda function (thanks to DynamoDB Streams) which will finally replicate the data into the target table.

This is the second blog post of a two-part series that uses a practical application to demonstrate how to integrate Redis with AWS Lambda. The first post was about the solution overview and deployment. Hopefully, you were able to try it out end to end. As promised, part two will cover the infrastructure aspects (IaC to be specific) which are comprised of three (CDK) stacks (in the context of a single CDK App).

I will provide a walk-through of the CDK code which is written in Go, thanks to the CDK Go support. AWS Cloud Development Kit (CDK) is all about IaC (Infrastructure-as-code).

Lambda Function URL is a relatively new feature (at the time of writing this blog) that provides a dedicated HTTP(S) endpoint for your Lambda function. It is really useful when all you need is a single endpoint for your function (e.g. to serve as a webhook) and doesn't want to set up and configure an API Gateway. Looks like I can't seem to get enough of it! I have written a couple of blog posts on this topic that includes a practical example of using it to build a serverless backend and then deploying that solution using AWS CDK.

This is yet another blog post (it's a short one!) that demonstrates how you can use Lambda Function URL to write a simple application backed by DynamoDB. You will be able to invoke an API endpoint exposed by the Lambda Function URL, which in turn will execute operations (GetItem, PutItem, Scan) on DynamoDB. The function is written in Go using the DynamoDB package in AWS Go SDK and AWS Serverless Application Model (SAM) is used to quickly build and deploy the solution.