aws-samples Goto Github PK

amazon-rds-proxy-video-demo

amazon-rds-proxy-with-reader-support-benchmarking-script

amazon-rds-purpose-built-workshop

A tutorial for developers, DBAs and data engineers to get hands-on experience on how to migrate relational data to AWS purpose-built databases such as Amazon DynamoDB, Amazon Aurora using AWS DMS and build data processing applications on top of it.

amazon-rds-push-db-load-using-cloudwatch-to-dynatrace

Deliver RDS Performance Insights to Dynatrace (APM tool)

amazon-rds-sizing-sample

Python and AWS CloudFormation code for Right Sizing Amazon RDS Instance at Scale based on Oracle Performance Metrics.

amazon-rds-upgrade-blog

Sample scripts for using Amazon RDS for Oracle with AWS Database Migration Service to upgrade the database engine with minimal downtime.

amazon-redshift-assume-role-sample

amazon-redshift-auto-pause

amazon-redshift-commands-using-aws-glue

Use a AWS Glue Python Shell Job to connect to your Amazon Redshift cluster and execute a SQL script stored in Amazon S3.

amazon-redshift-commands-using-sagemaker

amazon-redshift-config-compare

amazon-redshift-cost-attribution

amazon-redshift-data-lifecycle-manager

This code sample focuses on automating movement (unload) and management (delete/vacuum/analyze) of data in Amazon Redshift tables with temporal attributes through a simple configuration while maintaining movement and management choice, priority, logging, auditing and checkpointing.

amazon-redshift-data-warehouse-migration

In few hours, quickly learn how to effectively migrate oracle data warehouse workload to Amazon Redshift using AWS Schema Conversion Tool (SCT) and SCT data extractors. The lab will help them to use advance features of SCT like Virtual Partition while migrating the data warehouse to Amazon Redshift.

amazon-redshift-devops-blog

amazon-redshift-disaster-recovery

Guidance on how to restore an Amazon Redshift cluster to a secondary region if the cluster becomes unavailable/unreachable in the primary region.

amazon-redshift-dynamic-data-masking

amazon-redshift-infrastructure-automation

amazon-redshift-location-user-defined-functions

Amazon Redshift User Defined Functions to call Amazon Location Service APIs

amazon-redshift-ml-getting-started

Examples to get you started with Amazon Redshift ML

amazon-redshift-modernize-dw

Can you set up a data warehouse and create a dashboard in under 60 minutes? In this workshop, we show you how with Amazon Redshift, a fully managed cloud data warehouse that provides first-rate performance at the lowest cost for queries across your data warehouse and data lake. Learn the steps and best practices for deploying your data warehouse in your organization. Also, learn how to query petabytes of data in your data warehouse and exabytes of data, without loading or moving, in your Amazon S3 data lake. Finally, learn how to easily migrate from traditional or on-premises data warehouses.

amazon-redshift-query-patterns-and-optimizations

In this workshop you will launch an Amazon Redshift cluster in your AWS account and load sample data ~ 100GB using TPCH dataset. You will learn query patterns that affects Redshift performance and how to optimize them. In this lab we will also provide a framework to simulate workload management (WLM) queue and run concurrent queries in regular interval and measure performance metrics- query throughput, query duration etc. We will also provide some use cases for Redshift spectrum to query data from s3 in columnar format such as Parquet.

amazon-redshift-serverless-rsql-etl-framework

Amazon Redshift Serverless RSQL ETL Framework

amazon-redshift-streaming-workshop

This repository provides the resources required for the Amazon Redshift Streaming workshop

amazon-redshift-tiered-storage

Amazon Redshift offers a common query interface against data stored in fast, local storage as well as data from high-capacity, inexpensive storage (S3). This workshop will cover the basics of this tiered storage model and outline the design patterns you can leverage to get the most from large volumes of data. You will build out your own Redshift cluster with multiple data sets to illustrate the trade-offs between the storage systems. By the time you leave, you’ll know how to distribute your data and design your DDL to deliver the best data warehouse for your business.

amazon-redshift-udfs

A collection of example UDFs for Amazon Redshift.

amazon-redshift-with-cloudformation

Automate Redshift cluster creation with best practices using AWS CloudFormation

amazon-rekognition-and-amazon-appflow-image-moderation-using-aws-cdk-for-slack

This project deploys a fully serverless pipeline to moderate images posted to a Slack channel using the AWS CDK along with AWS Solutions Constructs. Services used are: Amazon Rekognition, Amazon AppFlow, AWS Lambda,Amazon S3 and Amazon SQS

amazon-rekognition-automate-video-editing-example

amazon-rekognition-batch-processing-label-and-face-detection