Category: Expert (400)

In this post, we walk through the steps of integrating Oracle Database@AWS (ODB@AWS) with Amazon Bedrock for by creating a RAG assistant application using an Amazon Titan embedding model in Amazon Bedrock and vectors stored in Oracle AI Database 26ai.

In this post, we show an algorithm to efficiently compare two Amazon DynamoDB tables and find the differences between their items. We provide an example where two tables, each containing approximately half a billion items, are compared in less than 7 minutes, for less than $10.

Part 1 of this series showed how to rate-limit calls to Amazon DynamoDB by using Python Boto3 event hooks. In this post, I expand on the concept and show how to rate-limit calls in a distributed environment, where you want a maximum allowed rate across the full set of clients but can’t use direct client-to-client communication.

In this post, I present a technique where a Python script making calls to Amazon DynamoDB can rate limit its consumption of read and write capacity units. The technique uses Boto3 event hooks to apply the rate limiting without having to modify the client code performing the read and write calls.

This post demonstrates how to implement SSL encryption for in-transit data protection when connecting Oracle Real Application Clusters (Oracle RAC) as a source to AWS Database Migration Service (AWS DMS). Additionally, it covers the unique steps required to configure SSL for Oracle Automatic Storage Management (Oracle ASM) instances.

Oracle Database@AWS (ODB@AWS) is an offering you can use to access Oracle Exadata infrastructure managed by Oracle Cloud Infrastructure (OCI) within Amazon Web Services (AWS) data centers. You can use ODB@AWS to migrate your Oracle Exadata workloads to AWS while maintaining the same performance and features as your on-premises Oracle Exadata deployments. You benefit from […]

AWS DMS accommodates a broad range of source and target data repositories, such as relational databases, data warehouses, and NoSQL databases. Proper preparation and design are vital for a successful migration process, especially when it comes to optimizing performance and addressing potential delay issues. In this blog post, we offer guidance about recognizing potential root causes of complete load and CDC delays early in the process and provide suggestions for optimally clustering tables to achieve the best performance for an AWS DMS task.

When your network fails, finding the root cause usually takes hours of investigations, going through correlated alarms that often lead to symptoms rather than the actual problem. Root-cause analysis (RCA) systems are often built on hardcoded rules, static thresholds, and pre-defined patterns that work great until they don’t. Whether you’re troubleshooting network-level outages or service-level degradations, those rigid rule sets can’t adapt to cascading failures and complex interdependencies. In this post, we show you our AWS solution architecture that features a network digital twin using graphs and Agentic AI. We also share four runbook design patterns for Agentic AI-powered graph-based RCA on AWS. Finally, we show how DOCOMO provides real-world validation from their commercial networks of our first runbook design pattern, showing drastic MTTD improvement with 15s for failure isolation in transport and Radio Access Networks.

Organizations operating hybrid environments can now extend their self-managed Active Directory authentication to Amazon RDS for Db2 instances via a forest trust with AWS Managed Microsoft AD. While basic Kerberos authentication functions transparently in this configuration, implementing group-based access control necessitates specific configuration, particularly when collaborating with users from trusted AD domains. In this post, we show how to enable Amazon RDS for Db2 to allow authorizations of groups in a customer managed Microsoft AD through a Directory Service domain.

In this post, we discuss different ways you can use volatility classification with functions in PostgreSQL and provide best practices to help you keep your database optimized and develop efficient and reliable database applications.