Source URL: https://aws.amazon.com/blogs/opensource/introducing-qontos-prometheus-rds-exporter-an-open-source-solution-to-enhance-monitoring-amazon-rds/
Source: AWS Open Source Blog
Title: Introducing Qonto’s Prometheus RDS Exporter – An Open Source Solution to Enhance Monitoring Amazon RDS
Feedly Summary: Databases are a critical part of most applications and essential to business continuity. To ensure performance, availability, and scalability, Amazon Relational Database Service (Amazon RDS) administrators typically monitor various metrics, such as the usage of CPU, RAM, IOPS, storage, or service quotas. Today, these metrics are found in several AWS services such as Amazon CloudWatch […]
AI Summary and Description: Yes
Summary: The text discusses a unified monitoring framework developed by Qonto for Amazon RDS that enables effective management of databases at scale using Prometheus and Grafana. It emphasizes the importance of standardizing database monitoring to enhance performance, availability, and scalability while sharing the implementation details and the significance of their open-source contribution.
Detailed Description:
– The critical role of databases in application performance and business continuity is highlighted, stressing the need for monitoring various metrics like CPU, RAM, and IOPS usage.
– Qonto’s solution, the Prometheus RDS Exporter, allows users to monitor multiple Amazon RDS databases through a unified framework, catering to medium and large-scale enterprises that typically manage many databases.
– Key components of the framework include established best practices and an automated tracking system that both reduces administrative work and minimizes risks associated with database operations.
– The monitoring system takes advantage of various AWS services to collect and visualize metrics efficiently:
– **APIs Used in the Prometheus RDS Exporter**:
– Amazon RDS for inventory and settings
– Amazon CloudWatch for consumption metrics
– Amazon EC2 for instance capacity
– Service Quotas to anticipate limit exceeded errors
– The text outlines the specifics on how to set up the Prometheus RDS Exporter, including:
– Creating necessary IAM policies and roles to fetch AWS API data securely
– Deploying in a Kubernetes environment with Helm
– Setting up Grafana for visualizing metrics and installed alerts
– **Deployment Steps**:
– Create an IAM policy and role for the Prometheus RDS Exporter.
– Deploy the RDS Exporter using Helm, configuring service accounts and necessary annotations.
– Install Grafana dashboards for effective monitoring.
– Enable predefined alerts to inform administrators of significant events or thresholds being exceeded.
– **Conclusion**: Emphasizes that Qonto’s approach leads to improved observability and scalability of database management in organizations, significantly benefiting teams handling large databases.
This text holds significant implications for security and compliance professionals as it highlights the importance of standardized monitoring practices, detailed access controls via IAM, and the integration of open-source tools to enhance database security and compliance with operational standards.