Category: Amazon CloudWatch

Today, we’re announcing the Remote Query Cache Plugin for the AWS Advanced JDBC Wrapper. The plugin handles query caching automatically. It intercepts JDBC queries, caches results in Amazon ElastiCache for Valkey, and serves subsequent identical queries from cache. Your only application change is prefixing queries with SQL hints. In this post, we show you how to use Amazon CloudWatch Database Insights to identify queries to cache, configure the Remote Query Cache Plugin in your Java applications, and monitor cache effectiveness using Amazon CloudWatch.

In this post, we demonstrate how to create custom Amazon RDS for SQL Server CloudWatch metrics. You accomplish this by using SQL Server Agent jobs and CloudWatch Logs integration. We walk through an example of monitoring table size within a SQL Server database however, this approach works for various other metrics. You can adapt this approach to track row counts, database size, job counts, user sessions, or other metrics.

In this post, you learn how to implement conversational operations for Oracle E-Business Suite (Oracle EBS) on AWS by connecting Kiro CLI with your monitoring infrastructure through the MCP. We walk through the technical architecture that enables natural language queries to retrieve CloudWatch metrics, analyze logs, and execute operational commands.

In this post, we explore an artificial intelligence and machine learning (AI/ML)-powered database monitoring tool for PostgreSQL, using a self-managed or managed database service such as Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL.

In this post, we demonstrate how you can use Amazon CloudWatch Database Insights to analyze your SQL execution plan to troubleshoot and optimize your SQL query performance in an Aurora PostgreSQL cluster.

In this post, we show how you can use Amazon CloudWatch Database Insights for troubleshooting your Amazon RDS and Amazon Aurora resources. CloudWatch Database Insights serves as a database observability solution offering a tailored experience for DevOps engineers, application developers, and database administrators. This tool is designed to accelerate database troubleshooting processes and address issues across entire database fleets, enhancing overall operational efficiency.

Amazon DynamoDB continuously sends metrics about its behavior to Amazon CloudWatch. Something I’ve heard customers ask for is how to get a count of successful requests of each operation type (for example, how many GetItem or DeleteItem calls were made) in order to better understand usage and costs. In this post, I show you how to retrieve this metric.

In this post, we show you how to import multiple Enhanced Monitoring metrics to CloudWatch and use the full capabilities of CloudWatch on those metrics.

Amazon DocumentDB (with MongoDB compatibility) is a highly efficient, scalable, and fully managed enterprise document database service designed to handle native JSON workloads. Amazon DocumentDB simplifies storing, querying, and indexing JSON data as a document database. The Amazon DocumentDB profiler feature is a valuable tool for monitoring the slowest operations on your cluster to help […]

Customers are actively exploring opportunities to optimize their expenses, aligning with the Cost Optimization pillar of the AWS Well-Architected Framework. In this post, we discuss the following tools that you can use to analyze your spend and optimize your Amazon Relational Database Service (Amazon RDS) costs.