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Nimbus reduces Datadog costs by more than 60% without Manual Effort
Our mission is to enable FANG-like observability for every organization in the world. We're starting with an optimization engine to reduce datadog costs by an order of magnitude without manual effort from developers.
Nimbus optimizes observability data by reducing log volume and costs without losing data. It analyzes traffic and applies optimizations to cut volume, aiming for substantial cost savings while preserving observability.
Nimbus configures by modifying four lines in the existing agent to send data to Nimbus. It analyzes all incoming logs to identify patterns, then applies optimizations with a single click to reduce log volume without dropping data. It provides intelligent traffic analysis, lossless log compression, monitoring compatibility with existing dashboards, and configurable bypass rules for critical events. It offers dashboards, charts, and reports, along with attribute mapping and previews for intelligent attribute handling.
Who it’s for: Observability teams and engineering organizations using Datadog (or other vendors) seeking to lower log costs while maintaining visibility.
case studies and pricing visible; trial offered; mentions of SOC2 audit process; references to customers (case study) and vendor integrations
AmazonEx-amazon, dev, founder of Nimbus.dev (Reduce Datadog Cost By 60% Without Manual Effort). Previous founder of Dendron.so (Organize information at scale)
Formerly “Dendron” · why startups rename →
Open source alternative to DataDog
Eliminate Cloud Waste. Attribute and Track Savings. Engage Engineers.
