Quick facts
- Best for
- Cloud security
- Pricing
- Freemium
- Editor rating
- 4.5 / 5
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About Kestrel AI
Kestrel AI is an AI-Native Cloud Incident Response Platform designed to detect, investigate, and fix Cloud and Kubernetes incidents swiftly. It connects with your clouds, Kubernetes clusters, observability tools, and code, fixing cloud infrastructure and application issues automatically through cloud APIs, Infrastructures as Code (IaC), and GitOps.Kestrel AI can monitor Cloud round the clock to spot incidents, trace their root causes, and generate immediate fixes either through auto-remediation or single-click approval. It employs AI Chat Copilot feature, where cloud questions can be asked and complex multi-dependency incidents can be probed in plain English. This chat feature provides instant answers and ready-to-apply fixes. The platform integrates with your existing CI/CD pipelines, converting every AI-generated fix into a pull request. This keeps your team in full control. With this, teams are enabled to manage complex infrastructure and application issues such as CoreDNS resolution failures, HTTP 5xx spikes, Kubernetes, VPC routing conflicts, and Kafka broker issues in the cloud. Kestrel AI system even learns from each incident, improving its performance over time, and offers a complete overview of your entire Cloud infrastructure. It can detect and compute precise fixes to intricate infrastructure and application failure patterns before they cause a complete production outage. The Risk Assessment function deploys AI agents to identify cross-domain security risks and provides exact remediation steps, helping to avert potential incidents.
Pros
- Detects cloud incidents
- Investigates cloud incidents
- Fixes cloud incidents
- Automates through cloud APIs
- Uses Infrastructures as Code
- Employs Git
- Constant cloud monitoring
- Root cause analysis
- Auto-remediation capability
- Single-click approval for fixes
- Plain English interaction
- Seamless CI/CD pipeline integration
Cons
- No Multi-Language Support
- Limited Cloud Providers Compatibility
- No Standalone Application
- Dependent on Git
- No Offline Functionality
- Limited to Kubernetes environments
- Auto-remediation Needs Explicit Approval
- No Cross-Platform Training