Best for Cloud Native Apps
Handle any size and complexity with automatic anomaly detection and root-cause analysis
Benefits
AI-Driven
- Improved End-user Satisfaction – Delivers better application uptime resulting in reduced customer churn and increased revenue.
- Reduced Noise & Alert Fatigue – Avoids dealing with large volumes of statically configured alerts that are hard to maintain and not productive.
- Real-time & Actionable Insights - Sophisticated anomaly detection with root-cause-analysis expedites detection and troubleshooting of incidents.
- Productive – Go from zero to observability in minutes. Reduce your overhead by letting someone else maintain intelligent observability SaaS services for you.
- Large Economic Impact - Enterprises can produce millions of logs per day and have thousands of KPIs. To analyze such data during an incident can be time comsuming. CloudAEye AI models can analyze accurately near real-time and can save customers hours of effort, downtime, and money.
Features
Modern Observability
- Comprehensive & AI-powered – Cloud application management reimagined with most comprehensive and modern AI-powered observability solution.
- Topology Based – Conquer any complexity by ingesting data from sources. Use standards based techniques to unify your data for AI-driven automatic analysis and resolutions.
- Cloud Scale – Rely on cloud scale observability with massive horizontal scalability. Automatically scale the services as your workload grows.
- Integrations – Enjoy a rich set of out-of-the-box integrations with services you normally use in your cloud applications.
- Sophisticated Dashboards - Unlimited dashboards from Grafana, Kibana.
- Secure – Leverage enterprise grade security with out-of-the box integrations.
- Sophisticated Logs Parsing – Parse any data and enrich your logs using an exhaustive set of plugins.
AI-Powered Observability
Applications
Supported Environments
Key Features
Logs
Metrics
Traces
Standards
AI Models
Services
Our Services
Autopilot for Distributed Cloud 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.
Automated Root-cause Analysis
Speeds up incident resolution with near realtime root-cause analysis at the time of incident. Our sophisticated models detect patterns across the distributed cloud services and applications and identifies the root-case of an incident.
Automated Context
Get all necessary information (logs, metrics, traces, etc.) about the incident and avoid costly context switching and investigations to find relevant information. This expedites troubleshooting and increases productivity of operations team.
Proactive Monitoring
Highly scalable Prometheus service that automatically scales as your workloads grow or shrink. Use Prometheus query language (PromQL) to filter, aggregate, and alarm on metrics. Out-of-the-box integration of AWS Services such as Amazon EKS (Kubernetes). Dedicated Grafana instance per tenant with unlimited dashboards.
Centralized Logging
Enterprise grade and highly scalable Elasticsearch service with multi-AZ support. Integrated Kibana dashboard. 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 Business
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 cloud native applications.
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