Telegraf Output Plugin for Amazon Kinesis Data Firehose

Analyze real-time global market data using AWS Kinesis and Snowflake. We utilize CSV datasets extracted via API calls, stream them through Kinesis Firehose, and transform them with Snowflake. Our agile workflow ensures efficiency, providing a one stop comprehensive solution for real-time data insights.

This web analytics demo shows how to collect web logs with API Gateway and store them into S3 through Amazon Kinesis. Then this project shows how to analyze web logs with Amazon Athena.

Typical use cases of opensearch serverelss: search, time-series, kinesis firehose integration, securing with VPC

A collection of lambda functions to collect data from Cloudwatch, Kinesis, VPC Flow logs, S3, security-hub and AWS Inspector

This project shows how to implement a simple SaaS metering system on AWS

Dynamic Terraform module, which creates a Kinesis Firehose Stream and others resources like Cloudwatch, IAM Roles and Security Groups that integrate with Kinesis Firehose. Supports all destinations and all Kinesis Firehose Features.

Receives data from firehose and puts it to ElasticSearch

Real Time Data Ingestion, Change Data Capture, In Transit Data Manipulation using DynamoDB, DynamoDB Stream, Kinesis Stream, Kinesis Firehose, Lambda Resources

This repository for researching and building a pipeline where a client sends data to AWS-iotcore where Kinesis Firehose will buffer and feed the data to a Lambda function.

This is a CDK project that set up centralized logging to an S3 bucket via a Kinesis Firehose. The solution allows you to specify trusted accounts for different regions and then will configure the CloudWatch Log Delivery Endpoint with proper permission in those regions Solution is based heavily on Centralize Cloudwatch Log with CDK https://github…

High-Performance AWS Kinesis Client for Go

A streaming data pipeline leveraging managed services from AWS & the serverless architecture

Amazon Kinesis output plugin for Fluentd

An end-to-end AWS data engineering pipeline that orchestrates data ingestion, processing, and storage using Kinesis, S3, Redshift, Lambda, DynamoDB

Fluent Plugin for Amazon Kinesis

The Project aims to establish a robust data pipeline for tracking and analyzing sales performance using various AWS services. The process involves creating a DynamoDB database, implementing Change Data Capture (CDC), utilizing Kinesis streams, and finally, storing and querying the data in Amazon Athena.

Embracing Modern Data Solutions: Transitioning from Apache Flink to Redis and AWS Lambda with SQS and Kinesis

Using DynamoDb Stream to capture item-level changes in the DynamoDb table, then use kinesis data stream and kinesis firehose to save the changes into a s3 bucket.

This repository hosts custom Greengrass components