Amazon DynamoDB is a serverless, NoSQL database service that allows you to develop modern applications at any scale.
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tutorial2026-07-08
This article provides a comprehensive guide on building and connecting a production-ready ecommerce Model Context Protocol (MCP) server using Amazon Bedrock AgentCore and Mistral AI Studio. It outlines the process of implementing MCP tools, setting up authentication, and deploying the server with AWS Cloud Development Kit (CDK). The article emphasizes best practices for security, data management, and server deployment, enabling ecommerce teams to streamline AI-powered customer experiences. By the end of the tutorial, readers will have a functional server capable of handling various ecommerce operations.
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product2026-07-02
This article discusses the challenges of managing high-volume application logs and how to overcome them using AWS Glue and Apache Iceberg materialized views. It provides a detailed solution for building an application log pipeline that enhances query performance by utilizing pre-computed query results. The architecture leverages several AWS services, including Amazon CloudWatch Logs, AWS Lambda, and Amazon Data Firehose, to create a scalable and efficient data pipeline. The article also outlines deployment steps and best practices for maintaining fast analytics performance on large-scale log data.
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tech22026-03-30
This article explores the challenges of counting unique items in large datasets and introduces probabilistic data structures known as data sketches. It discusses how traditional methods for exact counting can be resource-intensive and slow, especially at scale. The author explains various types of sketches, their advantages, and how they can provide approximate answers quickly while maintaining acceptable error bounds. The article emphasizes the importance of understanding when approximation is appropriate and the architectural implications of using sketches in data engineering.
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product2026-03-26
The article discusses the implementation of AWS Glue Data Quality pipelines using Terraform, highlighting two methods: ETL-based and Catalog-based Data Quality validation. It explains how these methods can ensure comprehensive data quality across data lakes and pipelines, utilizing a real-world dataset of NYC yellow taxi trips. The article emphasizes the benefits of Infrastructure as Code (IaC) practices for consistent and repeatable deployments, and provides a step-by-step guide for setting up the necessary resources in AWS.
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product2026-03-04
The article discusses the capabilities of Amazon OpenSearch Service, focusing on its zero-ETL integrations with various AWS services. It highlights how these integrations simplify data access and analysis by eliminating the need for complex ETL pipelines. The article covers specific integrations with services such as Amazon S3, CloudWatch, DynamoDB, RDS, Aurora, and DocumentDB, detailing their features, benefits, and best practices. Overall, it emphasizes the operational efficiency and innovation acceleration that zero-ETL integrations can provide for real-time analytics and search applications.
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tutorial2026-01-15
This article presents a solution for automating business reporting using generative AI and Amazon Bedrock. It highlights the inefficiencies of traditional reporting processes and introduces a serverless architecture that leverages AWS services to streamline report writing and enhance internal communication. The solution includes a user-friendly interface for associates and managers, enabling efficient report generation and submission. Additionally, it addresses challenges such as data management and risk mitigation associated with AI implementation.
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product2025-11-18
The article discusses how organizations can leverage platform engineering principles to accelerate the development and deployment of generative AI applications. It highlights the challenges faced by organizations in experimenting with generative AI and emphasizes the importance of building reusable components to manage costs and improve efficiency. The article outlines the architecture of generative AI applications, including the integration of various data layers and the role of large language models. It also covers best practices for observability, orchestration, and governance in AI workflows.
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project2025-02-24
Interesting architecture to handle bursty and unpredictable traffic on AWS
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project2024-10-29
With AWS LakeFormation, creating filter packages and controlling access. A filter package provides a restricted view of a data asset by defining column and row filters on the tables.
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project2024-11-11
To search user profiles to remove, we use an AWS Lambda function that queries Aurora, DynamoDB, and Athena and places those locations in a DynamoDB table specifically for GDPR requests.
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project2024-11-11
To search user profiles to remove, we use an AWS Lambda function that queries Aurora, DynamoDB, and Athena and places those locations in a DynamoDB table specifically for GDPR requests.
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