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CloudAEye Documentation


What is CloudAEye?

CloudAEye provides SaaS-based intelligent observability for cloud.

The AI-powered workflow automatically surfaces anomalous services, provides contextual awareness, frictionless management of an incident and root-cause-analysis to reduce MTTD (mean time to detect) and MTTR (mean time to repair).

The CloudAEye Free Tier provides customers the ability to try out our services free of charge up to the specified limits. Sign up!

Videos

CloudAEye Observability

We focus on the following:

  • Intelligent Monitoring - One shouldn’t have to constantly tune configuration
  • Intelligent Alerting - A team receives just a single notification; alert storms are a thing of the past
  • Why is My Service Unhealthy? – Automatic root-cause analysis highlights possible causes. It saves valuable time during an incident.
  • Automated Incident Report – Shows all aspects of a production incident with deep insights that helps team members to resolve an issue and avoid the manual analysis.

Differentiators

Semantic Observability: Experience an observability solution that is proactive and less noisy. We automatically analyze an anomaly and identify what is not working. We contextualize it from all available data (ex. logs, metrics, traces, tickets, code changes, deployments, chats, etc.) and generate a hypothesis about it. Our automated analysis quickly identifies why a customer’s service is broken, annotates the service in a dependency graph and enables the customer to test fixes rapidly.

Our mission is to deliver the ultimate AI solution for distributed cloud application management.

Log Management: Our log management suite provides an in-depth look into log discovery, log pattern analysis, exception insights, and state-of-the-art AI-driven log anomaly detection solutions. We provide enterprise-grade tiered log storage, alerting and notification mechanisms that is very easy to set up.

Serverless Management: Our lambda suite focuses on lambda performance analysis, trace and log management as well as AI-driven incident detection and recommendations for automatic remediation of lambda issues as well as solutions to lambda cold-start problems.

Root-cause Analysis: We correlate metrics, logs, traces, and deployments together to accurately pinpoint the root-cause of failures.

Generative AI: At CloudAEye, we believe in answering the what/why/how questions regarding customer’s cloud operations. We focus on saving countless SRE work hours by proving a conversational generative AI interface to make observability human-readable. Our assistant provides answers and detailed analysis, automates tasks, and generates contents in seconds that would have otherwise taken hours to complete.