Knowi provides its users with a built-in support to integrate CloudWatch datasources and Query against them to build multiple visualizations, each with a transformed view of the original data. This way, the users can have a unified view and actionable insights to analyze how their AWS resources, apps, and services are performing. Providing the end user with a capability to promptly respond to any operational problems or changes.
Query CloudWatch Datasource & Create Visualization
At Knowi, we provide users with the capability to add CloudWatch datasource by providing the datasource’s Default Region, Access Key ID & Access Key Secret, Access Key ID & Access Key Secret or IAM Role ARN, and External ID.
After adding CloudWatch as a datasource, users can start querying using any of the following three Query modes:
- Metric
- Expression
- Meta
The users can select Metric as the Query Type and use Knowi’s Visual Builder to configure the Query on top of CloudWatch. For example, you can use the Visual Builder for the Metric Query to return all metrics in the namespace AWS/EC2 for us-east-1 region, with a CPUUtilization metric and any value for the InstanceId dimension.
Apart from the above, the users can also use Search Expressions mode and simply define the Region and Time Range while writing the syntax for CloudWatch expressions in SQL to build the Query.
Last but not the least, Knowi also provides users with Meta mode to query the CloudWatch datasource by listing the Regions, Namespaces, Metrics, Statistics, Dimensions, and Dimension Values.
For more information, please refer to the documentation- Add & Query CloudWatch Datasource
Tip: In all the three modes discussed above, we provide users with the ability to write SQL-like syntax under Cloud9QL Query to perform additional transformations on the data returned from CloudWatch.
After creating your dataset, you can create multiple visualizations, each with various transformed views on top of your CloudWatch datasource. This allows for end-to-end monitoring of your amazon environment.
Monitor Your Amazon Environment & Receive Alerts
Knowi allows its users to create real-time and powerful visualizations with a unified view on top of the CloudWatch dataset. With this ability, the users can proactively monitor their Amazon environment and quickly identify any anomalies within any AWS resource, service, or application.
For example, you can examine hundreds of EC2 instances categorized via CPU utilization to identify underperforming applications. You can also group your metrics through InstanceID to further narrow down your analysis for faster identification of the failing instances. After isolating the instance, you can restore the application by booting up the instances with problems.
Moving forward, you can also set up the alerts which will help you receive notifications for any identified anomaly.
Conclusion
Integrating your CloudWatch datasource with Knowi provides you with a powerful capability to have a central and unified view of the operational health of your Amazon environment for faster detection of anomalies and proactive issue resolution. In this way, the customers can discover valuable insights and keep their vital AWS resources, applications, and services running smoothly.
