Case Study: Posh achieves deep observability fast with groundcover

Posh gains trace-level insight in 1 day with groundcover

Posh, a venture-backed conversational AI company for the banking industry, faced significant challenges with its existing observability stack. Using Datadog APM and logs, costs became prohibitively high, forcing them to limit monitoring to only their production environment and leaving development and staging with minimal coverage. Their attempt to build a self-hosted Prometheus/Grafana stack was a major time sink for their small platform team and still lacked critical capabilities like distributed tracing, leaving them with blind spots, especially in their GraphQL services.

By implementing groundcover, Posh deployed a lightweight sensor across their Kubernetes clusters in minutes with no code changes. groundcover provided immediate, deep insights into all environments, including the ability to trace individual GraphQL operations, which was previously impossible. The results included a dramatic reduction in observability costs due to groundcover's predictable, node-based pricing, faster troubleshooting that resolved issues in hours instead of days, and the elimination of wasteful engineering effort spent on maintaining their previous tools.

Posh