Kaleido seamlessly integrates with AWS CloudWatch, to diagnose problems quickly, through your application stack, right down onto the chain. The monitoring and management service provides data and actionable insights to monitor your applications running on Kaleido, understand and respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health. Visualize key metrics like CPU utilization and memory. You can also correlate a log pattern, e.g. error to a specific metric to quickly get the context and go from diagnosing the problem to understanding the root cause.
Enables you to collect metrics and logs from all your AWS resources, applications, and services that run on AWS and on-premises servers, helping you break down data silos so you can easily gain system-wide visibility.
Natively integrated with more than 70 AWS services such as Amazon EC2, Amazon DynamoDB, Amazon S3, Amazon ECS, AWS Lambda, Amazon API Gateway, etc. that automatically publish detailed 1-minute metrics and custom metrics with up to 1-second granularity.
Visualize key metrics like CPU utilization and memory. You can also correlate a log pattern, e.g. error to a specific metric to quickly get the context and go from diagnosing the problem to understanding the root cause.
The Ethereum logs for each node serve as a rich datasource for devops-centric tasks such as application troubleshooting and operational health monitoring. While the Kaleido /logs API provides a convenient endpoint to retrieve these logs, it requires a manual configuration against the consortia/environment/node resource IDs and must be constantly polled to ensure up-to-date streams.
As an alternative to this configuration-intensive approach, Kaleido offers the option to integrate nodes with AWS’ monitoring and management service, Cloudwatch, and directly stream real time logs.
A fully-encompassed monitoring service provides the ability to visualize Kaleido logs alongside existing resources and processes, and surfaces an aggregated trove of data that can lead to greater insights and application optimization.
For example, your Cloudwatch service could be customized to trigger metric-based alarms and issue automated actions based on certain inflections. This centralized view of the core application and business processes helps lead to more informed decisions and increased efficiency.
