We'll discuss limitations of the Lambda invoke function operator of Apache Airflow and create a custom Lambda operator. The custom operator extends the existing one and it reports the invocation result of a function correctly and records the exact error message from failure.

Recently AWS Glue 3.0 was released but a docker image for this version is not published. In this post, I’ll illustrate how to create a development environment for AWS Glue 3.0 (and later versions) by building a custom docker image.

In this post, I'll demonstrate how to build development environments for AWS Glue 1.0 and 2.0 using the Docker image and the Visual Studio Code Remote - Containers extension.

In this post, it is demonstrated how AWS Lambda can be integrated with Apache Airflow using a custom operator inspired by the ECS Operator.

Traefik is a modern HTTP reverse proxy and load balancer. In this post, it'll be demonstrated how path-based routing can be set up by Traefik with Docker. Also a centralized authentication will be illustrated with the Forward Authentication feature of Traefik.

In this post, I'll illustrate how a web service is created using FastAPI framework where tasks are sent to multiple workers. The workers are built with Celery and Rserve. Redis is used as a message broker/result backend for Celery and a key-value store for Rserve. Demos can be run in both Docker Compose and Kubernetes.

In this post, I'll demonstrate how to create a Linux development environment on Windows using WSL. Also an example app (Rserve web service with a sidecar container) on Minikube will be demonstrated.

LocalStack provides an easy-to-use test/mocking framework for developing AWS applications. In this post, I'll demonstrate how to utilize LocalStack for development using a web service.

In the previous posts, it is discussed how to package/deploy an R machine learning model with AWS Lambda and to expose the Lambda function via Amazon API Gateway. In this post, I'll demonstrate how to host a web application that services the backend API in a serverless environment.

In previous posts, we discussed how to package and deploy an R machine learning model via Lambda. In this post, I'll demonstrate how to expose the model via Amazon API Gateway.