AWS Cloud Watch

What is AWS Cloud Watch?

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

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

Metrics about all AWS services being used are automatically displayed on the Amazon CloudWatch dashboard. The Amazon CloudWatch dashboard interface allows users to create custom graphical views across their AWS services.

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

Use cases for Amazon CloudWatch include:

• Infrastructure monitoring and troubleshooting to understand and resolve the root causes of performance issues with 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