Category: Learning Levels

Amazon OpenSearch Service has taken a significant leap forward in scalability and performance with the introduction of support for 1,000-node OpenSearch Service domains capable of handling 500,000 shards with OpenSearch Service version 2.17. This post explains cluster state publication, Remote Publication, and their benefits in improving durability, scalability, and availability.

In this post, we explore a streamlined, configuration-driven approach to orchestrate dbt Core jobs using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) and Cosmos, an open source package. These jobs run transformations on Amazon Redshift. With this setup, teams can collaborate effectively while maintaining data quality, operational efficiency, and observability.

In this post, we show how automatic semantic enrichment removes friction and makes the implementation of semantic search for text data seamless, with step-by-step instructions to enhance your search functionality.

This post demonstrates how to harness OpenSearch Dashboards to analyze logs visually and interactively. With this solution, IT administrators, developers, and DevOps engineers can create custom dashboards to monitor system behavior, detect anomalies early, and troubleshoot issues faster through interactive charts and graphs.

In this post, we address common multi-tenancy challenges and provide actionable solutions for security, tenant isolation, workload management, and cost optimization across diverse healthcare tenants.

In this post, we demonstrate how to use Amazon Bedrock Flows in SageMaker Unified Studio to build a sophisticated generative AI application for financial analysis and investment decision-making.

In this post, we first briefly review how planner statistics are collected and what impact they have on queries. Then, we discuss Amazon Redshift features that deliver optimal plans on Iceberg tables and Parquet data even with the lack of statistics. Finally, we review some example queries that now execute faster because of these latest Amazon Redshift innovations.

In this post, we walk you through a solution for implementing rack awareness in consumer applications that are dynamically deployed across multiple Availability Zones using Amazon EKS.

This post demonstrates how to build a solution by combining Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue Data Catalog for schema management, and Amazon Athena for one-time querying. We’ll focus specifically on handling Avro-formatted data in partitioned S3 buckets, where schemas can change frequently while providing consistent query capabilities across all data regardless of schema versions.

Customers new to Amazon OpenSearch Service often ask how many shards their indexes need. An index is a collection of shards, and an index’s shard count can affect both indexing and search request efficiency. OpenSearch Service can take in large amounts of data, split it into smaller units called shards, and distribute those shards across a dynamically changing set of instances. In this post, we provide some practical guidance for determining the ideal shard count for your use case.