A serverless architecture for orchestrating ETL jobs in arbitrarily-complex workflows using AWS Step Functions and AWS Lambda.
Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS
Configuration with AWS step functions and lambdas which initiates processing from activity state
Build and deploy a serverless data pipeline on AWS with no effort.
Generative AI video short-form generator using Amazon Bedrock and AWS serverless services.
A single pipeline to deploy multiple services on amazon ecs using gitops
All your AWS Stepfunctions at a glance in the terminal! 🧐
Serverless Telegram bot made on 4 AWS Lambda chained by AWS Step Functions. All of this written on Serverless Framework using plugins.
This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.
Introducing an application that uses ChatGPT to generate daily summaries of your WhatsApp group discussions, saved to a Google Sheet, and providing easy access to previous conversations and shared media.
A Step Functions microservice for remediating GuardDuty findings.
A pytest fixture that makes you able to mock Lambda code during AWS StepFunctions local testing
Activity worker for performing activity tasks from AWS StepFunctions
SAM template for Amazon DynamoDB table to CSV using DynamoDB Export feature.
A fast, scalable, multithreaded download statemachine based on AWS, supporting .mkv, .mov, .mp4, .jpg, and others.
A serverless AWS pipeline that fetches random dog images from a public API, stores them in S3, triggers alerts for unexpected non-image files via SNS, and logs metadata to DynamoDB. Built as a challenge deliverable for Intermediate and Advanced AWS Services.
Jupyter notebooks are widely used by Datascientists for their data transformation workloads. There are scenarios where the notebook needs to be scheduled and run in regular interval and they need to be productionize. This repo provides a framework for the Datascientists to productionize their workloads dynamically (based on the notebooks) using …
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