What is Uptime?

How Uptime Is Measured

Uptime is calculated as the share of a measurement window during which a service was available: total time minus downtime, divided by total time, expressed as a percentage. Providers measure it with monitoring probes that check the service at short intervals from multiple locations, counting the service as down when consecutive checks fail. The measurement window matters — 99.9% over a year permits far more consecutive downtime than 99.9% over each individual month.

Availability is often described in nines. Two nines (99%) allows roughly 7.3 hours of downtime per month, three nines (99.9%) about 43 minutes, and four nines (99.99%) about 4.4 minutes. Service level agreements (SLAs) define exactly what counts: which components are covered, whether scheduled maintenance is excluded, and what compensation applies when the target is missed.

For proxy networks, uptime is layered. The infrastructure a customer connects to — the endpoints, authentication layer, and dashboard — has its own availability, while individual exit IPs come and go constantly, especially in residential pools where addresses belong to real consumer devices. A well-designed network stays up even as individual IPs churn, because traffic is transparently routed to healthy addresses.

Why Uptime Matters for Scraping and Data Collection

Data collection pipelines usually run continuously and unattended. When the proxy layer goes down, crawlers stall, scheduled jobs miss their windows, and time-series datasets — price histories, availability snapshots, ranking trackers — develop gaps that are difficult to backfill accurately. For monitoring use cases, an hour of proxy downtime is an hour of blind spots.

Downtime also has second-order costs. Retry storms after an outage can trip target-site rate limits, and failure-handling code paths that rarely run are a common source of bugs. Tracking proxy-endpoint availability separately from target-site errors makes diagnosis faster: a connection refused at the proxy endpoint points to an availability problem, while an HTTP 403 from the target points to blocking.

Practical Notes and Common Misconceptions

Uptime is not the same thing as success rate. A proxy network can be fully operational while a fraction of requests still fail because of target-side blocks, slow exit IPs, or timeouts; success rate captures those request-level outcomes, uptime does not. ProxyOmega, for example, publishes a 99.7% request success rate — a stricter, request-level metric that complements availability.

Treat round-number availability claims with care: every service needs maintenance, and 100% figures usually reflect a short or favorable measurement window. Read the SLA definition of downtime, and run your own lightweight health checks against the exact endpoints you use rather than relying solely on a provider status page.