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Cloud security

Kestrel AI ✓

AI agents resolve cloud incidents in seconds.

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AI Incident Response API Open Source
More categories (4)
Cloud Incident Detection Cloud Infrastructure Management Cloud Incident Investigation Cloud security
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Trial; then from $300/mo

Verdict

A quick read before you dig into the full page.

Best if
AI agents resolve cloud incidents in seconds
Skip if
Limited to Kubernetes environments
Pick this when
Detects cloud incidents

Considering Upwind.io instead? Compare side by side

Overview

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.

Kestrel AI website

Access & connections

Where you can use Kestrel AI, and what it plugs into.

Platforms

Web CLI

Integrations

Kubernetes MCP

API

Public API available

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Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Tabular

Output

  • API
  • Text

Highlights

  • Agents
  • API
  • MCP

Supported features

  • Agents
  • API
  • Assistant
  • Automation
  • CLI
  • Cybersecurity
  • Data Analysis
  • Integrations
  • MCP
  • Memory
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  • SOC 2 Compliance

Pros & cons

Pros

  • Detects cloud incidents
  • Investigates cloud incidents
  • Fixes cloud incidents
  • Automates through cloud APIs
  • Uses Infrastructures as Code
  • Employs GitOps
  • Constant cloud monitoring
  • Root cause analysis
Show 33 more
  • Auto-remediation capability
  • Single-click approval for fixes
  • Plain English interaction
  • Seamless CI/CD pipeline integration
  • Team retains full control
  • Manages complex infrastructure issues
  • Handles application issues
  • Learns from each incident
  • Improves performance over time
  • Offers cloud infrastructure overview
  • Predicts infrastructure failure patterns
  • Prevents production outage
  • Identifies cross-domain security risks
  • Calculates exact remediation steps
  • Resolves incidents swiftly
  • Comprehensive Cloud Infrastructure Map
  • Visualizes real-time traffic
  • Fast Setup
  • 24/7 cloud monitoring
  • Real-time Incident Response
  • IAC and GitOps Integration
  • Instant ready-to-apply fixes
  • Autonomous Risk Assessment
  • Precise config fixes
  • Cloud Infrastructure Visualization
  • Real-Time Traffic monitoring
  • Direct Deployment of changes
  • Interactive Config Review
  • GitOps Integration
  • Multi-cloud Support
  • Automated Deployment
  • End-to-End Incident Management
  • Enterprise-Grade Security

Cons

  • No Multi-Language Support
  • Limited Cloud Providers Compatibility
  • No Standalone Application
  • Dependent on GitOps
  • No Offline Functionality
  • Limited to Kubernetes environments
  • Auto-remediation Needs Explicit Approval
  • No Cross-Platform Training

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Releases 1

Initial release October 22, 2025 Current
Initial release of Kestrel AI.

FAQ 12

What is Kestrel AI and how does it work?
Kestrel AI is an AI-Native Cloud Incident Response Platform designed to swiftly detect, investigate, and fix Cloud and Kubernetes incidents. The platform communicates with your clouds, Kubernetes clusters, observability tools, and code, hereby directly addressing cloud infrastructure and application issues through cloud APIs, Infrastructures as Code (IaC), and GitOps. It functions round the clock to identify incidents, determine their root causes, and formulate immediate fixes that can be implemented either through auto-remediation or single-click approval. Over time, Kestrel AI learns from each incident to enhance its performance and offers an exhaustive overview of your entire Cloud infrastructure.
What is the AI Chat Copilot feature in Kestrel AI?
The AI Chat Copilot is a feature in Kestrel AI that allows you to ask cloud questions and investigate complex multi-dependency incidents in plain English. This feature provides real-time responses and ready-to-apply solutions, allowing for quick and concise probing of issues within your cloud infrastructure and applications. This simplifies the process of understanding and resolving incidents while skipping command-line tools and dashboards.
How does Kestrel AI integrate with my existing CI/CD pipelines?
Kestrel AI seamlessly integrates with your existing CI/CD pipelines by converting every AI-generated fix into a pull request. This allows every change to be carefully scrutinized and approved, ensuring your team has total governance over updates made to your infrastructure.
How does Kestrel AI detect and remediate cloud and Kubernetes incidents?
Kestrel AI uses AI algorithms to continuously monitor your Cloud and Kubernetes clusters, identifying incidents as soon as they occur. Once detected, it traces their root causes, and creates precise fixes which can be implemented either automatically or upon approval. This proactive approach minimizes downtime and swiftly addresses intricate infrastructure and application failure patterns before they escalate to full-blown production outages.
What is the Auto-Remediation feature offered by Kestrel AI?
The Auto-Remediation feature in Kestrel AI paves the way to automatic resolution of detected incidents. It deploys AI agents that identify security risks across domains and provides exact steps to remediate these risks. Interwoven with its cloud incident response capability, it either auto-remediates or creates a fix that can be implemented through single-click approval, enhancing response times and minimising the impact of incidents on the cloud infrastructure.
How does Kestrel AI perform root cause analysis?
Kestrel AI conducts root cause analysis by tracing the genesis of cloud incidents. It identifies issues by continuously monitoring cloud resources and, once an incident has been detected, it investigates and traces the cause. This aids in creating precise fixes, thereby swiftly resolving the incident and reducing its impact.
What type of issues Kestrel AI can handle in my cloud infrastructure?
Kestrel AI is capable of managing a variety of complex infrastructure and application issues. These include but are not limited to CoreDNS resolution failures, HTTP 5xx spikes, Kubernetes issues, VPC routing conflicts, and Kafka broker issues in the cloud. This broad capability allows for the swift resolution of most incident types, reducing downtime and improving cloud performance.
How does Kestrel AI monitor Cloud round the clock?
Kestrel AI's round-the-clock cloud monitoring is ensured by its AI-operated incident detection capabilities. It works non-stop to identify cloud incidents, trace their root causes, and produce immediate fixes either through auto-remediation or by generating a solution for single-click approval.
What is single-click approval in Kestrel AI?
Single-click approval in Kestrel AI means that every single AI-generated fix comes with a comprehensive review interface where changes can be examined with detailed diffs, explanations, and approval workflows. Once approved, these changes are deployed directly to your cloud or Kubernetes clusters, allowing you to maintain control while swiftly addressing incidents.
What are the key features of Kestrel AI in managing infrastructure failure patterns?
Kestrel AI has several key features in managing infrastructure failure patterns. It employs advanced algorithms to detect intricate infrastructure and application failure patterns. Once these patterns are identified, it computes precise fixes before they lead to complete production outages. Kestrel AI also incorporates a learning mechanism where it improves with each detected and resolved incident, helping to proactively foresee and mitigate potential issues.
How does Kestrel AI's Risk Assessment function work?
Kestrel AI's Risk Assessment function functions by deploying AI agents to identify cross-domain security risks in the cloud infrastructure. It not only identifies these risks, but also provides exact steps to remediate them, helping to prevent potential incidents even before they occur.
How can Kestrel AI prevent a potential production outage?
Kestrel AI prevents potential production outages by detecting intricate infrastructure and application failure patterns and computing precise fixes even before these issues escalate. As it learns from each incident, its ability to anticipate and address issues improves over time, helping to maintain a resilient and stable cloud infrastructure.
Kestrel AI Trial; then from $300/mo
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