Category: Amazon QuickSight

In this post we introduce a solution that addresses a common challenge faced by many customers: managing costs in multi-tenant applications, particularly for shared databases in Amazon Relational Database Service (Amazon RDS) and Amazon Aurora. This solution uses Amazon RDS Performance Insights and AWS Cost and Usage Reports (CUR) to addresses this challenge. This allows for efficient grouping of tenants within the same RDS or Aurora instances, while helping you implement accurate chargeback models, optimize resource-intensive workloads, and make data-driven decisions for capacity planning.

In this post, we walk you through a solution to aggregate RDS orphan snapshots across accounts and AWS Regions, enabling automation and organization-wide visibility to optimize cloud spend based on data-driven insights. Cross-region copied snapshots, Aurora cluster copied snapshots and shared snapshots are out of scope for this solution. The solution uses AWS Step Functions orchestration together with AWS Lambda functions to generate orphan snapshot metadata across your organization. Generated metadata information is stored in Amazon Simple Storage Service (Amazon S3) and transformed into an Amazon Athena table by AWS Glue. Amazon QuickSight uses the Athena table to generate orphan snapshot insights.

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.

This is a guest blog post by Oliver Jägle, Software Architect at DB Curbside Management, in partnership with AWS Senior Solutions Architect Ben Freiberg. Have you ever rented a scooter or a bicycle instead of walking or taking a bus? You’re not alone. More and more people around the globe have adopted this sort of […]

Businesses such as Paxos that issue stablecoin USD tokens want to find a way to identify common token metrics such as top holders, daily active users, daily volume, total number of holders, latest transfers, top Decentralized Finance (DeFi) protocols the tokens have been used on, and more. With Amazon Managed Blockchain (AMB) Query and Amazon […]

Customers have asked for a way to interact with graph datasets in Amazon Neptune using business intelligence (BI) tools such as Amazon QuickSight. Although some BI tools offer generic HTTP connectors that allow you to define a set of REST API calls to extract data from REST endpoints, you have to predefine either Gremlin or […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Many organizations have accelerated their adoption of stream data processing technologies in an effort to more quickly derive actionable insights from their data. Frequently, it is required […]

Amazon Aurora offers a high-performance advanced auditing feature that logs detailed database activity to the database audit logs in Amazon CloudWatch. If you are using Aurora 1.10.1 or greater, you can use advanced auditing to meet regulatory or compliance requirements by capturing eligible events like tables queried, queries issued, and connections and disconnections. You can […]