Category: Analytics

Amazon OpenSearch intelligent ingestion is a fully managed, serverless capability that turns documents and structured data in Amazon S3 into RAG-ready, searchable indexes with no pipelines to manage. Learn how it works and when to use Ingestion Jobs or Ingestion Streams.

Trusted Identity Propagation with AWS IAM Identity Center now works across Regions. Learn how to share AWS Lake Formation-governed Amazon S3 and Amazon Redshift data in one Region and query it from another as the actual corporate user, with fine-grained access control and per-user auditability in AWS CloudTrail.

Learn how to trace two invisible threats in a multi-agent AI pipeline, prompt injection propagation and cross-tenant data exfiltration, using Amazon OpenSearch Service and Amazon Bedrock. Instrument every agent hop with embeddings, provenance, and PII detection, reconstruct the attack path, and add guardrails that stop these attacks before they reach production.

AWS Glue Data Quality is now available natively on Amazon EMR, bundled in AWS runtime for Apache Spark (emr-spark-8.1.0). Write the same DQDL rulesets you use in AWS Glue directly in your Amazon EMR Spark jobs. This post walks through two patterns: lightweight inline validation and an Apache Iceberg Write-Audit-Publish workflow with managed rulesets.

Learn how to build an enterprise-scale cross-account streaming pipeline with Amazon Kinesis Data Streams using the Kinesis Producer Library (KPL) and Kinesis Client Library (KCL) across three separate AWS accounts, with resource-based policies, cross-account IAM, and a shared customer managed AWS KMS key for maximum security isolation.

Troubleshooting a multi-service, MWAA-orchestrated ETL pipeline often means hunting across scattered Amazon CloudWatch log groups. This post shows how to centralize your ETL logs in Amazon OpenSearch Service and query them in plain language through an MCP server on Amazon Bedrock AgentCore, so you find root causes faster.

Learn how to pair DuckDB with AWS Glue 6.0 to run SQL-centric ETL on a single worker, reading Parquet from Amazon S3 and writing Apache Iceberg tables to Amazon S3 Tables. This post walks through a complete, runnable example and compares measured cost and runtime against an equivalent Apache Spark job on the same Glue runtime.

Amazon EMR 8.1.0 adds multi-catalog support through the RedirectingSessionCatalog, so you can query Iceberg, Delta Lake, Hudi, and Hive tables through a single catalog and join data across AWS accounts without copying it. This post shows how to put these capabilities into practice on Amazon EMR Serverless.

The KIP-848 consumer protocol in Apache Kafka 4.0 redesigns consumer group rebalancing to eliminate stop-the-world pauses. This post explains how the consumer protocol works on Amazon MSK, how to enable it on MSK Standard and Express brokers, and how to diagnose and resolve slow rebalancing issues.

Announcing Spark Connect on Amazon EMR on EKS: build, test, and debug Spark applications from VS Code, PyCharm, Jupyter notebooks, Amazon SageMaker Unified Studio, or dbt, while running full-scale Spark operations on your existing Amazon EKS clusters.