Metoro

Metoro is an observability platform specifically designed for Kubernetes (K8s) environments. It provides comprehensive monitoring and troubleshooting capabilities, leveraging auto-instrumentation and artificial intelligence to simplify the process of gathering and analyzing telemetry data from cloud-native applications.

Key features:
- Auto-instrumentation: Utilizes eBPF technology to automatically collect metrics, logs, and distributed tracing data from Kubernetes clusters without manual intervention.
- Continuous Profiling: Offers ongoing application profiling with minimal overhead using eBPF, identifying performance bottlenecks without code changes.
- AI-Driven Root Causing: Analyzes and summarizes issue root causes using structured observability data and generative AI, reducing manual analysis time.
- Automated Alert Investigation: Proactively investigates alerts as they occur, providing insights before manual intervention is needed.
- Custom Metrics Integration: Allows ingestion of custom metrics to enhance observability of specific application aspects.
- Alerting System Integration: Integrates with Opsgenie and plans to support PagerDuty for seamless incident management workflows.

How it works:
1. Metoro auto-instruments applications running in Kubernetes using eBPF technology.
2. Telemetry data is automatically captured without manual instrumentation.
3. Users access the web application interface to view metrics, logs, traces, and AI-generated insights.
4. API access is available for integrating observability data into existing workflows or custom applications.

Integrations:
Opsgenie, Custom Metrics, OpenAI Models Hosted in Azure

Use of AI:
Metoro employs generative artificial intelligence for advanced features such as AI-driven root cause analysis and automated alert investigation. This technology helps analyze structured observability data to identify patterns and anomalies, offering actionable insights to users and reducing mean time to resolution for issues.

AI foundation model:
Metoro relies on OpenAI models hosted in Azure for its AI-driven features. These models are deployed in major regions to ensure data sovereignty and performance.

Target users:
- Developers seeking reduced MTTR and deeper insights into application performance issues
- Support teams needing to triage issues effectively without comprehensive system understanding
- Site Reliability Engineers (SREs) looking to prioritize work efficiently by understanding common causes of issues across the organization

How to access:
Metoro offers a 14-day free trial of its Business tier without requiring a credit card. After the trial, users can choose to continue with a free tier or select a paid plan. For enterprises requiring a self-hosted solution, Metoro provides a version deployable as a helm chart in Kubernetes.