How Uno.ai Unified Observability Across Three Clouds and Cut Costs from Day One with OpenObserve

Uno.ai, an AI-native GRC and risk-management platform serving large regulated enterprises, adopted OpenObserve to reduce escalating observability costs while maintaining reliable monitoring across GCP, AWS, Azure, Kubernetes, ephemeral workloads, and frontend applications. Because service availability affects customer SLAs and potential financial penalties, the company had embedded observability, failover, and metrics collection into its systems from its founding, but found that cloud-native tools and other options delivered only baseline monitoring at disproportionately high prices. After considering an in-house stack, Datadog, and OpenTelemetry-based alternatives, Uno.ai selected OpenObserve for its engineering-focused collaboration, standards support, data compression and storage efficiency, flexible querying, integrations, and self-service dashboard configuration. Prior use of StatsD and OpenTelemetry allowed the company to migrate with minimal effort by changing telemetry destinations, while OpenObserve’s RUM SDK consolidated frontend error and performance data previously distributed across Sentry and internal systems. Uno.ai reports that the platform has improved engineering agility, centralized telemetry from its multi-cloud infrastructure and client applications, and helped contain observability spending as the company grows.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.