Funxtion achieves 91% improvement in API scores and 15x faster debugging after deploying Treblle API intelligence platform
Netherlands-based fitness platform Funxtion deployed Treblle to gain real-time API observability and governance — improving API performance scores by 91%, accelerating debugging 15x, and saving hundreds of developer hours per month across a platform serving 1,000+ gyms in 25+ countries.
Background
Funxtion's API-first platform grew rapidly, but the engineering team lacked the visibility to maintain consistent API quality at scale. Traditional logging tools couldn't provide the full context needed to quickly diagnose errors, and there was no unified view of API performance, security, or quality for non-engineering stakeholders.
What Was Implemented
- Deployed Treblle API intelligence platform for API observability, governance, and documentation
- Used Treblle's API Governance feature to score each API on performance, security, and quality with specific improvement recommendations
- Implemented real-time API observability to enable fast, visual root-cause analysis for API failures
- Shared Treblle dashboards across engineering, product, and customer support teams for data-backed decision-making
- Eliminated context-switching between multiple tools for API monitoring and debugging
Results
Following the Treblle deployment, Funxtion achieved a 91% improvement in API performance scores , 15x faster debugging , and 100+ developer hours saved per month . The platform is now used daily by engineering, product, and customer support teams — removing the need for engineers to field internal data requests manually.
Lessons
- Scoring APIs on performance, security, and quality (vs. binary pass/fail alerting) gives engineering teams actionable direction rather than just problem notification
- API observability that serves non-engineering stakeholders (product, customer support) multiplies its value: it removes a class of internal requests to engineers
- For small engineering teams, an API intelligence platform can function as "another engineer" for routine monitoring and diagnostic queries
- Misspelling or misidentifying a vendor (the book writes "Trebble" not "Treblle") in book copy is a common error that research editors should flag for correction