See the spike while it is happening
Live traffic view grouped by API key, endpoint and country. Sort by rejected requests and you have your answer in one click, not one afternoon of grepping.
API rate limiting & abuse protection
Stop API abuse before it costs you.
ThrottleBox sits in front of your API, throttles bad actors automatically and shows you exactly who is hammering which endpoint - so a single scraper never turns into a 3am incident and a five-figure bill.
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Developers protecting APIs
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Requests screened monthly
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Edge uptime, trailing 90 days
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The problem
Hand-rolled rate limiting breaks at the worst possible time.
Most teams start with a counter in Redis. It works until traffic is spiky, until you run more than one instance, until someone rotates through 400 IP addresses, or until you need to explain to a customer why their legitimate burst got blocked. Then it becomes a side project nobody owns.
ThrottleBox replaces that counter with a policy you can read: limits per key, per endpoint and per plan, enforced at the edge in under a millisecond, with a live view of every decision it made and a one-click override when you get it wrong.
Sub-millisecond at the edge
Limits are evaluated in 38 regions, so protection never costs you latency.
Policies as plain config
One YAML block per plan tier. Version it, review it, roll it back.
Block abuse, not customers
Burst allowances, soft limits and per-key overrides mean a paying customer with a busy Monday gets a warning header, while a scraper gets a 429.
How it works
Three steps, one afternoon.
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Point your traffic at us
Change one DNS record, or install the middleware package for your framework.
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02
Describe your limits
Requests per minute, burst size and quota, per plan tier or per endpoint.
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Watch and tune
Start in monitor-only mode, review what would have been blocked, then enforce.
Testimonials
What teams say after the first incident it caught.
“We had a scraper pulling our catalogue every four seconds for a week before we noticed. ThrottleBox flagged the same pattern in under an hour.”
Platform lead, Ledgerly
“I deleted 400 lines of Redis counter logic and two on-call runbooks. The config file now fits on one screen and the whole team can read it.”
Backend engineer, Wavepoint
“Monitor-only mode sold it internally. We shipped enforcement two weeks later with real numbers instead of a guess about who we might break.”
CTO, Orbitly