Glossary // AWS Cloud Watch

What is AWS Cloud Watch?

Amazon CloudWatch provides real-time monitoring of Amazon Web Services (AWS) resources and its running applications. Specifically designed for system architects and administrators, Amazon CloudWatch facilitates performance reporting requirements across AWS instances, providing system-wide visibility into resource utilization and application performance. Amazon CloudWatch also provides visibility into operational health for AWS resources, such as Amazon EC2 instances, Amazon EBS (Elastic Block Store) volumes, Elastic Load Balancers, and Amazon RDS database instances as well as on-premise servers.

CPU utilization, latency and request count, are among the metrics automatically provided by Amazon CloudWatch. Additional metrics can be monitored, including memory usage, transaction volumes or error rates.

The Amazon CloudWatch dashboard interface allows users to create custom graphical views across their AWS services by automatically displaying metrics about each service. 

Through API requests, users can enable the same core functionality of Amazon CloudWatch for custom data. Custom dashboards can be created to display metrics related to custom and external applications.

Amazon CloudWatch also functions for basic monitoring of system logs, allowing users to track and analyze specific metrics. Data displayed can be both real-time data and historical (up to a two-week maximum).

Users can access Amazon CloudWatch functions through an API, command-line tools, an AWS SDK (Software Development Kit) or the AWS Management Console. From these interfaces, users can create custom reports, notifications, or alarms. Alarms can be set to send alerts, or automatically make changes to resources when a metric crosses a limit, or when resources are underutilized.

Use cases for Amazon CloudWatch include:

• Infrastructure monitoring and troubleshooting to understand and resolve the root causes of performance issues in resources and applications.
• Resource optimization to automate capacity and resource planning.
• Application monitoring, with the automated triggering of alarms and workflows to optimize customers’ experiences.
• Log analytics to identify operational issues and optimize performance.