UsageFlow
API usage metering, rate-limits and usage reporting
Details
- External ID
- 45998953
- Source
- HN
- Company
- —
- Product
- —
- Website domain
- —
- Launched
- Nov. 20, 2025
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.0982532751091703
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:25 p.m.
- Updated at
- Sept. 7, 2026, 9:25 p.m.
Description
I’m launching UsageFlow, a simple tool for API owners who want automatic API usage metering and full control over their endpoints — all without any hassle.With just a few lines of code, the UsageFlow SDK gives you:Automatic discovery of API endpointsUser identificationUsage meteringRate-limits and automatic blockingReporting usage events to your existing billing or metering systemSupports: Go (Gin), Python (FastAPI, Flask), Node.js (Express, Fastify, NestJS)Perfect for AI APIs or SaaS platforms that want to scale fast — focus on building your product while UsageFlow handles usage tracking automatically.No developer skills required to:Update usage rulesApply limitsReport usageEverything works with a few clicks — your entire usage platform is in your hands, instantly.I’m opening this for first testers. If you run an API and want to try UsageFlow, comment below or DM me — I will create your account and get you started in minutes.Learn more at: https://usageflow.io
Enrichment
- Theme
- generative AI model API gateways
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Commercial product
- Normalized one-liner
- api metering and rate limiting
- Manually corrected
- False
Could you build this?
Partial Building client SDK wrappers and basic dashboards is straightforward, but building ultra-low-latency, distributed, highly available rate limiting and high-throughput event metering infra requires systems engineering.
What it would actually take: The system requires an edge reverse-proxy / SDK middleware that syncs counters to a distributed, low-latency in-memory datastore (e.g., Redis cluster using sliding window or token bucket algorithms) coupled with an asynchronous event-streaming pipeline (Kafka/ClickHouse) for analytics. It demands distributed systems engineering to handle high-throughput traffic without adding latency overhead or dropping usage records.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one — 36 launches clear the similarity bar, closest 8 shown.
Attention rank: #35 of 37 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 9 days after the earliest competitor.
- nestjs-quota · github · 2026-09-27 · 10 upvotes · similarity 0.46
- RateGuard · ph · 2026-09-10 · 1 upvotes · similarity 0.44
- QuotaMint · ph · 2026-09-27 · 16 upvotes · similarity 0.44
- UsageGate · ph · 2026-09-20 · 2 upvotes · similarity 0.43
- SHOW HN: A usage circuit breaker for Cloudflare Workers · hn · 2026-03-10 · 29 upvotes · similarity 0.42
- Claude Meter · hn · 2026-02-10 · 9 upvotes · similarity 0.41
- Diet Claude · ph · 2026-08-25 · 430 upvotes · similarity 0.40
- Understand and reduce token usage with ContextSpy context profiler · hn · 2026-06-15 · 6 upvotes · similarity 0.39
Other launches for this product
- No other launches for this product.
Same idea, different domain
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