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Data engineering teams running Apache Airflow across multiple AWS accounts have no built-in way to coordinate workflows between separate Amazon MWAA environments. With Airflow 3.0...
You can now use PythonOperator and BashOperator to run custom Python functions and shell scripts directly in the Amazon MWAA Serverless runtime, without provisioning additional inf...
Learn how the Everyday Essentials team built a scalable personalized recommendation platform on AWS using a batch-first architecture with Amazon MWAA for orchestration, Amazon Sage...
Every data team eventually asks the same question: what runs our pipelines, on what schedule, with what retry logic, and who gets paged when it fails. The answer used to default to...
The goal is not custom AMIs for every workload. It is to make dependency management, patching and recovery explicit platform responsibilities rather than repeated job-level tasks.
Creative teams produce more assets than ever, but fragmented tools and manual context transfer slow production. This post shows how to build a reusable agent harness with Amazon Qu...
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your...
In this post, we cover a high-level view of the Smartsheet remote MCP architecture, with a focus on the AWS infrastructure behind it. This includes security, governance, scaling an...
Agent Skills for Amazon MSK bring broker-type-aware expertise to operating and migrating Apache Kafka clusters. In this post, we walk through installing the managing-amazon-msk and...
In this post, we show you how to set up the agent for Amazon EMR on EKS and walk through troubleshooting a failed job run. We demonstrate the workflow from both the Amazon EMR cons...
Learn how to query Amazon S3 Tables from Trino on Amazon EMR using the Apache Iceberg REST catalog endpoint. This post shows how to deploy the integration with AWS CloudFormation,...
AWS Glue 6.0 is now available, lowering AWS Glue pricing by 30%, adding an AWS optimized build of Apache Spark 4.1, and introducing Apache Iceberg V3 capabilities suitable for ente...
Announcing delivery to streaming tables on Apache Iceberg for Amazon MSK Express brokers, a fully managed capability that continuously materializes your Kafka streaming data as que...
Learn how to combine OpenAI-compatible endpoints on Amazon SageMaker AI with Amazon Bedrock AgentCore runtime to build a multi-agent workflow where each specialized agent uses the...
Learn how AppFolio transformed its data streaming architecture by adopting Amazon MSK Express brokers, replacing hours-long rebalances and manual storage planning with a platform t...
Learn how to build a no-code customer retention pipeline in Amazon Quick that detects at-risk customers from call transcripts and CSAT data, scores them by retention priority with...
In this post, we show how Apache Celeborn resolves this trade-off for Amazon EMR on EKS and Amazon EMR on EC2, improving job reliability while unlocking additional cost savings.
Extend AWS DevOps Agent to investigate Apache Spark failures on Amazon EMR. This post shows how to register the Apache Spark Troubleshooting Agent for Amazon EMR as a custom MCP ca...
In this post, we discuss the benefits of Advanced Scaling for Amazon EMR on Amazon EC2 and demonstrate how it works through some example scenarios. You'll learn when to prioritize ...
When people begin learning AWS, they usually focus on services like EC2, S3, IAM, VPC, RDS, Lambda, CloudFormation, and ECS. These are the…Continue reading on AWS Tip »
With AWS Glue 6.0, you can build real-time, near-real-time, and batch data pipelines on a single platform. Using a financial market-risk example, learn how to flag high-risk trades...
Walk through upgrading a PySpark ETL job from AWS Glue 5.1 to AWS Glue 6.0 using the generative AI upgrades for Apache Spark. The upgrade analysis automatically detects incompatibi...
In this post, we show you how to use Amazon SageMaker Unified Studio to implement cross-account data sharing in Amazon Redshift using data mesh principles. We demonstrate how to bu...
The data lakehouse has become the default architecture for analytics on AWS in 2026. It combines the best of both worlds: the low-cost, schema-flexible storage of a data lake (S3)...
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