Know exactly what your APIs are doing
Real-time logs and analytics for every request through your gateway — searchable, filterable, and exportable, with consumer-level attribution out of the box.
Most API problems aren't found in dashboards — they're reported by customers
API teams ship faster every quarter, but visibility into the gateway itself usually lags behind. The result: longer outages, blame ping-pong between teams, and a backlog of "we'll add metrics later."
Slow MTTR
Without span-level timing across policies, handlers, and origins, every incident is a manual tour through stack traces and grepped log lines.
Black-box gateway
Your handler logs show what your code did — but not which inbound policy rate limited, blocked, or quietly added 200ms before the request ever got there.
No per-customer visibility
When a customer reports a problem — or a single consumer is hammering your API — can you tell which one, on which endpoint, in a single click?
Blind spots in AI traffic
Token spend, prompt-injection blocks, and semantic-cache hits all happen at the gateway — completely invisible to your application APM.
Observability that pays for itself the first time it saves an incident
Resolve issues 10× faster
Click from a P99 spike straight to the slow span. Logs, metrics, and (soon) traces in one place — with the API key, route, and policy chain already attached.
Understand every customer
Every log, metric, and trace is automatically tagged with the consumer that made the call. Find power users, abusers, and revenue drivers in a single query.
Keep your existing stack
12 prebuilt destinations plus any OTLP-compatible collector. Forward to multiple at once, ship custom payload shapes in TypeScript — nothing to deploy alongside the gateway, no rewrites, no vendor lock-in.
Stop hunting through stack traces
Every request through your gateway lands here in real time — searchable, filterable, and exportable. Find the failing call in seconds, with severity, latency, status, and the API key that made it already attached.
Environment
Time Range
Severity
Skip the dashboard build-out
Track P50/P95/P99 latency, error rates, request volume, and per-customer traffic from day one — without standing up a separate metrics pipeline or a custom Grafana board. Hit your SLOs with statistical confidence and spot regressions before customers do.
Keep the observability stack you already use
Forward logs, metrics, and traces to 12 prebuilt destinations or any OTLP-compatible collector — fan out to multiple at once, nothing to deploy alongside the gateway, and TypeScript hooks for any custom payload your team needs.
The same observability for your AI traffic
Zuplo's AI Gateway runs on the same policy pipeline as the API Gateway, so every LLM call shows up in your logs, metrics, and traces — alongside your REST traffic. Plus AI-specific signals you can't get from a generic APM:
- Token spend per project, model, and consumer — with budget guardrails to stop runaway costs.
- Prompt-injection blocks and PII catches — every guardrail event logged with the offending prompt.
- Time-to-first-byte and semantic-cache hit rates — the latency signals that actually matter for LLM UX.
- Stream every call to Galileo, Comet Opik, or your own collector — full request/response traces with token counts and latency.
Tokens (24h)
4.82M
+18.4%
Spend (24h)
$312.46
72% of daily budget
TTFT P95
348ms
-12ms
Cache hit rate
31.4%
+2.1%
Built for the way modern API teams actually work
Most observability stories stop at "we have integrations." Zuplo's stops at "we already wrote your data the way you need it."
Programmable, not configured
Custom log shapes, custom metric calculations, custom forwarding — all in plain TypeScript. Attach order IDs, tenant IDs, plan tier, or any business event to gateway telemetry without standing up a separate pipeline.
Built into the gateway, not bolted on
Observability runs inside the gateway runtime, not as a sidecar or daemon you maintain alongside it. Logs, metrics, and traces ship straight from the request to your destination across 300+ edge data centers — nothing to deploy, version, or keep in sync with the gateway release.
Per-API-key by default
Because Zuplo issues your API keys, every request is automatically attributed to its consumer — no instrumentation code, no manual tagging. Per-customer dashboards work on day one.
One pipeline for every protocol
REST, GraphQL, WebSockets, SOAP-over-HTTP, MCP servers, and AI Gateway calls all flow through the same observability stack. One story across your entire API surface.
What teams use this for
“My P99 just spiked. Where's the bottleneck?”
Click the spike → in-portal trace → slowest span. Roughly 30 seconds from alert to root cause, without leaving Zuplo.
“Which customer is hammering us right now?”
Filter analytics by consumer. Top 10 by request count, error rate, or P95 latency — straight from the dashboard.
“Are we approaching the LLM budget?”
AI Gateway dashboards roll up token spend per project, model, and consumer — with budget guardrails to cut off runaway costs.
“Did my last deploy regress anything?”
Compare the same endpoint before and after a release. Latency distribution, error rate, and request volume side by side in seconds.
More observability is on the way
In-portal tracing, external API monitoring, threshold alerts, and breaking-change detection are all on the roadmap. Sign up to get early access the moment they ship.
See the public roadmapFrequently Asked Questions
Common questions about API observability with Zuplo.
Ready to see your APIs in action?
Spin up a free Zuplo project and watch the logs and analytics start flowing in real time.