AWS Big Data Blog
Build a dynamic rules engine with Amazon Managed Service for Apache Flink
This post demonstrates how to implement a dynamic rules engine using Amazon Managed Service for Apache Flink. Our implementation provides the ability to create dynamic rules that can be created and updated without the need to change or redeploy the underlying code or implementation of the rules engine itself. We discuss the architecture, the key services of the implementation, some implementation details that you can use to build your own rules engine, and an AWS Cloud Development Kit (AWS CDK) project to deploy this in your own account.
Deprecation of Lake Formation’s Governed Tables Feature
After careful consideration, we have made the decision to end support for Governed Tables, effective December 31, 2024, to focus on open source transactional table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. This decision stems from customer preference for these open source solutions, which offer ACID-compliant transactions, compaction, time travel, and other features previously provided by Governed Tables.
Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics
Over the last year, Amazon Redshift added several performance optimizations for data lake queries across multiple areas of query engine such as rewrite, planning, scan execution and consuming AWS Glue Data Catalog column statistics. In this post, we highlight the performance improvements we observed using industry standard TPC-DS benchmarks. Overall execution time of TPC-DS 3 TB benchmark improved by 3x. Some of the queries in our benchmark experienced up to 12x speed up.
Amazon EMR Serverless observability, Part 1: Monitor Amazon EMR Serverless workers in near real time using Amazon CloudWatch
We have launched job worker metrics in Amazon CloudWatch for EMR Serverless. This feature allows you to monitor vCPUs, memory, ephemeral storage, and disk I/O allocation and usage metrics at an aggregate worker level for your Spark and Hive jobs. This post is part of a series about EMR Serverless observability. In this post, we discuss how to use these CloudWatch metrics to monitor EMR Serverless workers in near real time.
Apply enterprise data governance and management using AWS Lake Formation and AWS IAM Identity Center
In this post, we explore a solution using AWS Lake Formation and AWS IAM Identity Center to address the complex challenges of managing and governing legacy data during digital transformation. We demonstrate how enterprises can effectively preserve historical data while enforcing compliance and maintaining user entitlements. This solution enables your organization to maintain robust audit trails, enforce governance controls, and provide secure, role-based access to data.
Enrich your serverless data lake with Amazon Bedrock
Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. By consolidating this information, analysts can discover and integrate data from across the organization, creating valuable data products based on a unified dataset. This post shows how to integrate Amazon Bedrock with the AWS Serverless Data Analytics Pipeline architecture using Amazon EventBridge, AWS Step Functions, and AWS Lambda to automate a wide range of data enrichment tasks in a cost-effective and scalable manner.
Achieve cross-Region resilience with Amazon OpenSearch Ingestion
In this post, we outline two solutions that provide cross-Region resiliency without needing to reestablish relationships during a failback, using an active-active replication model with Amazon OpenSearch Ingestion (OSI) and Amazon Simple Storage Service (Amazon S3). These solutions apply to both OpenSearch Service managed clusters and OpenSearch Serverless collections. We use OpenSearch Serverless as an example for the configurations in this post.
How to track Amazon OpenSearch Service domain-level cost
Amazon OpenSearch Service Pricing is based on three dimensions: instances, storage, and data transfer. Storage pricing depends on the chosen storage type and also the storage tier. Visibility into domain-level charges enables accurate budgeting, efficient resource allocation, fair cost attribution across projects, and overall cost transparency. In this post, we show you how to view the OpenSearch Service domain-level cost using AWS Cost Explorer.
Amazon OpenSearch Service: Managed and community driven
Today the Linux Foundation announced the OpenSearch Software Foundation. As part of the creation of the OpenSearch Foundation, AWS has transferred ownership of OpenSearch to the Linux Foundation. At the launch of the project in April of 2021, in introducing OpenSearch, we spoke of our desire to “ensure users continue to have a secure, high-quality, fully open source search and analytics suite with a rich roadmap of new and innovative functionality.” We’ve maintained that desire and commitment, and with this transfer, are deepening that commitment, and bringing in the broader community with open governance to help with that goal.
Use Batch Processing Gateway to automate job management in multi-cluster Amazon EMR on EKS environments
AWS customers often process petabytes of data using Amazon EMR on EKS. In enterprise environments with diverse workloads or varying operational requirements, customers frequently choose a multi-cluster setup due to the following advantages: Better resiliency and no single point of failure – If one cluster fails, other clusters can continue processing critical workloads, maintaining business […]