Provides an observability platform that integrates logs, traces, and performance metrics to help engineering teams identify incidents, understand system performance, and monitor user impact. By aggregating data across services and users, it enables faster incident resolution and actionable insights without the need for manual data digging. Supports seamless integration with tools like Slack, GitHub, and AWS Lambda, requiring only two lines of code for setup.
Funding
Funding not disclosed
Founders
Product
Problem
Modern engineering teams struggle to efficiently identify incidents, understand system performance, and monitor user impact due to fragmented data across various services and users. Manual data digging is often required, leading to slower incident resolution and delayed insights.
Solution
IUDEX provides an observability platform that unifies logs, traces, and performance metrics, enabling engineering teams to proactively identify and resolve incidents. By aggregating data across services and users, IUDEX facilitates faster incident resolution and provides actionable insights without manual data analysis. The platform supports integrations with tools like Slack, GitHub, AWS Lambda, and various frameworks, and requires minimal code for setup. IUDEX helps teams understand the performance of their systems and the impact on users by providing aggregated metrics and narratives.
Target Audience
IUDEX is designed for modern engineering teams that require comprehensive monitoring and user analytics, including developers working with Next.js, Python, and other popular frameworks.
Features
- Aggregates logs, traces, and performance metrics into a unified dashboard
- Provides error alerts with traces and impacted user data
- Offers uptime dashboards for monitoring service availability
- Supports log and trace search for efficient troubleshooting
- Integrates with Next.js, Python, OpenAI, AWS Lambda, Supabase, Slack, PagerDuty, Linear, and GitHub
- Offers a two-line setup for quick integration
- Includes anomaly detection powered by AI to identify hidden bugs
- Provides log pattern analysis using Agglomerative Hierarchical Embeddings-based Log Parsing (A HELP)