AlertMend is an AI-powered production operations platform that unifies Kubernetes monitoring, observability, log management, and incident response. The platform correlates metrics, logs, and traces on a single timeline, generates evidence-backed root cause analyses, and executes remediation runbooks only after human approval via Slack or Teams. It also includes FinOps capabilities that identify recoverable cloud spend, such as right-sizing opportunities and idle GPU resources.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Developer Tools
- Enterprise Software
- Software Only
Funding
Founders
Product
Problem
Modern infrastructure teams managing Kubernetes clusters, VMs, and cloud environments face fragmented monitoring tools that separate metrics, logs, and traces, making incident diagnosis slow and error-prone. On-call engineers spend excessive time manually correlating signals across disparate systems, which prolongs mean time to resolution and increases operational toil during critical outages.
Solution
AlertMend provides a unified production operations platform that correlates metrics, logs, and traces on a single timeline, giving teams complete visibility across Kubernetes clusters, pods, nodes, and cloud infrastructure. The platform's AI-driven root cause analysis automatically identifies the underlying cause of incidents with supporting evidence, typically within seconds. Once a root cause is identified, AlertMend executes approved remediation runbooks that are gated by human approval through Slack or Teams, ensuring automated fixes only run with explicit consent. The platform also includes log management with SQL querying, on-call scheduling and escalation, and FinOps capabilities for cost optimization, all accessible through a single console.
Target Audience
Primary customers are SRE teams, DevOps engineers, and platform engineering groups at startups and enterprises running production workloads on Kubernetes, VMs, or cloud infrastructure who need to reduce MTTR and automate incident response.
Features
- Unified observability console that correlates metrics, logs, and traces with a service map, supporting OpenTelemetry, eBPF, and PromQL
- AI root cause analysis that generates evidence-backed explanations by correlating deployment changes, trace data, logs, and metric anomalies in approximately 15 seconds
- Remediation runbooks with human-in-the-loop approval via Slack or Teams, including automatic rollback and full audit trail
- SQL-based log management for Kubernetes and VMs with sub-40ms query performance across millions of log lines
- Kubernetes monitoring and management covering clusters, pods, nodes, and health with support for 1,000+ pod deployments
- FinOps tools that identify recoverable spend through right-sizing recommendations, idle GPU detection, and YAML preview with per-namespace rollback
- On-call and incident management with schedules, escalation policies, and context-rich pages via Slack, WhatsApp, and phone
- GPU and MLOps support for H100/A100 fleets and ML pipeline monitoring