Best for Serverless Apps
Handle any size and complexity with automatic anomaly detection and root-cause analysis
CloudAEye root-cause analysis with context
Benefits
AI-Powered
Provides end-to-end visibility into your serverless applications. Never miss an anomaly with AI-powered models that will ingest and analyze all the data and identify anomalies and root-cause of the incident.- Intelligent Monitoring – Use a monitoring solution that does not require you to tune configuration and rules constantly. Be productive in under 10 minutes.
- Intelligent Alerting - Alert storms are a thing of the past! Your team receives a single notification from CloudAEye when there is an anomaly.
- Get the answer to critical questions such as "Why Is My Service Unhealthy?" – CloudAEye delivers sophisticated root-cause analysis with detailed context that saves valuable time during an incident.
Features
Serverless Monitoring
- Real-time insights about critical application issues. The AI-powered models analyze data streams and monitor thousands of metrics to establish normal bounds for application behavior and can automatically identify deviations from normal activity
- Monitor all your functions & AWS services in one place with out-of-the-box integrations
- Get actionable insights without the digging
Logs Analysis
- Search and analyze logs faster for rapid troubleshooting
- See AI-powered root-cause indicators from the logs automatically during an incident and avoid digging through logs
- Centralize all logs from lambda and AWS services with out-of-the-box integrations
Operational Insights
- Automatic detection of lambda operational issues such as Cold Start, Throttled, Errors, Out of Memory, Over Provisioned or Timeout
- Resolve issues quickly with ML-powered insights. See contextual information about the issue and recommendations on the possible fix
Keep-alive
- Automatic scaling of lambda function to avoid Cold Starts
End-to-End Monitoring
- Avoid digging through a large number of traces during an incident with AI-powered anomaly detection of distributed traces. Only look at the traces that are not normal
Root-cause Analysis
- Automatic discovery and dependency mappings
- Breaks down silos between logs, metrics, and traces
- Identify, scope, and resolve issues with AI-based root-cause analysis with context. Root-cause analysis removes siloes and saves time and money by expediting recovery from downtime
Services
Our Services
Copilot for Serverless Application Management
Anomaly Detection
Expedite detection and troubleshooting of incidents using sophisticated machine learning (ML) and deep learning (DL) models that automatically surfaces the anomalous service(s) and provides insights and recommendations to quickly resolve the incident.
Root-cause Analysis
Speeds up incident resolution with near realtime root-cause analysis at the time of an incident. Our sophisticated models detect patterns across the distributed cloud services and applications and identifies the root-case.
Automated Context
Get all necessary information (logs, metrics, traces, etc.) about the incident and avoid costly investigations. Save time and money and avoid data siloes.
Monitoring
Highly scalable service that automatically scales as your workloads grow or shrink. Out-of-the-box integration of AWS Services.
Centralized Logging
Enterprise grade and highly scalable service with multi-AZ support. Sophisticated log parsing. Highly secure with out-of-the-box integration with AWS IAM, Cognito.
Distributed Tracing
Performance and latency analysis for distributed microservices based architecture. Service dependency analysis. Automatic detection of anomalous traces.
Build Your Busniess
Take the stress out of your cloud operations by leveraging start-of-the-art ML/DL techniques! Augment your SRE & operations teams with AI-powered solutions such as observability, anomaly detection, root-cause analysis – all designed and purpose built for serverless applications.
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