Lumigo

Distributed tracing for serverless and containers

For developers working on distributed cloud systems, Lumigo offers a way to follow requests across services and find faults. It is built for microservice environments, serverless functions and containerized systems, and it shows where a fault sits when a request passes through several services. The company says its aim is to help developers identify and resolve critical issues quickly, using smart monitoring and end-to-end tracing.

Tracing without code changes

End-to-end tracing can be set up in minutes without changing application code, for AWS, Kubernetes and OpenTelemetry environments, according to the company. The platform builds a visual map of the services involved in each transaction, and developers can search and filter that map to find the step that failed.

AI root cause analysis

The platform uses AI to identify and analyze problems automatically, which the company says cuts the hours spent reading logs by hand. Lumigo also captures request payloads, which it describes as a way to troubleshoot precisely. Real-time alerts flag problems as they appear, and the company presents its root cause analysis as one of its main features.

Logs, metrics and cost

Logs are gathered in one place and enriched with trace and payload data. The company says its log management runs on a custom data ingestion pipeline designed to cut logging costs. Custom metrics and real-time monitoring let teams watch the health of their applications, and the company says it helps teams optimize serverless environments for both performance and cost.

Guidance on AWS Lambda

The company publishes guides on AWS Lambda basics, the wider serverless ecosystem, performance optimization, deployment, serverless debugging, serverless monitoring, performance testing, OpenTelemetry, cloud-native monitoring and microservices monitoring. These guides sit alongside the product and cover the topics its users are likely to face.

Who builds with it

The product is aimed at developers, and its material shows use in serverless and containerized environments. It presents the platform as suited to teams working on microservices and cloud-native systems, which is the environment the company sets out to serve.