How to Build a Proxy Pool

Source and Aggregate Proxy Addresses

Start by collecting proxy endpoints from your providers. If you use a single provider with a gateway endpoint, your pool might contain different configuration variants of that gateway (different geographic targets, session types, or proxy tiers). If you use multiple providers, aggregate all their endpoints into a unified pool structure so your scraper code interacts with one consistent interface regardless of which provider serves any given request.

Store each proxy entry with metadata: the full connection URL (protocol, host, port, credentials), the provider name, proxy type (residential, datacenter, ISP, mobile), geographic location (country, optionally city), cost per request or per GB, maximum concurrent connections allowed, and any rate limits imposed by the provider. This metadata enables intelligent routing decisions later.

For providers offering dedicated IPs (common with datacenter proxies), list each IP individually in your pool. For providers offering rotating gateways (common with residential proxies), create a single pool entry per geographic configuration since the provider handles individual IP rotation internally. Your pool manages provider-level rotation while each provider manages IP-level rotation within their infrastructure.

Validate all proxy entries on initial load. Connect to each proxy, send a test request to a known endpoint (like httpbin.org/ip), and verify that the response comes from the expected IP range and geographic location. Remove any entries that fail validation before they can waste actual scraping requests. Schedule periodic revalidation (every 30 to 60 minutes) to catch proxies that degrade over time.

Implement Health Tracking Per IP

Every proxy in your pool needs a health profile that updates in real time based on its performance. The minimum viable health tracking includes: total requests sent through this proxy, successful responses received, failed responses received, current success rate (calculated as a rolling window over the last 100 requests rather than all-time to detect recent degradation), average response time over the last 50 requests, timestamp of last successful request, timestamp of last failure, and current cooldown expiration (if any).

Track health metrics per target domain, not just globally. A proxy might perform well on one website but poorly on another due to that site's specific blocking rules. Maintain a nested data structure where each proxy has global health metrics plus per-domain metrics for each target you scrape. When selecting a proxy for a request to target X, use the proxy's performance history against target X specifically, falling back to global metrics for targets the proxy has not yet been used against.

Implement a sliding window for success rate calculation rather than using all-time averages. A proxy that worked perfectly for 1,000 requests but has failed the last 20 consecutively still shows 98% all-time success, masking the fact that it is currently broken. A 100-request sliding window catches degradation within minutes, enabling fast cooldown activation before too many requests are wasted.

Store health data in memory for performance (proxies may be selected thousands of times per minute), but persist snapshots to disk periodically so that pool state survives application restarts without losing all historical performance data. On restart, load the persisted state and resume with full context rather than treating all proxies as fresh.

Build the Rotation Selection Algorithm

The selection algorithm answers the question: given a request to target domain X requiring geography Y, which proxy from the pool should handle it? A good algorithm considers multiple factors weighted by importance.

First, filter by hard requirements: remove proxies that do not match the required geography, are currently in cooldown for this target, or have exceeded their concurrent connection limit. This produces a candidate set of eligible proxies.

Second, score each candidate using weighted factors. Success rate against this specific target contributes the most weight (a proxy with 95% success is strongly preferred over one with 70%). Time since last use provides a freshness bonus that distributes load evenly and prevents hammering one proxy repeatedly. Cost per request provides an economic preference toward cheaper options when multiple candidates have similar success rates. Response time provides a speed preference when latency matters.

Third, select from the scored candidates using weighted random sampling rather than always picking the top-scored proxy. Weighted random ensures that highly-scored proxies get selected more often while still giving lower-scored candidates occasional chances to prove themselves. This prevents a single "best" proxy from receiving all traffic (which would quickly burn it) and allows recovering proxies to demonstrate improvement.

Implement target-specific routing rules as an override layer above the general algorithm. You might know that target A requires residential proxies while target B works fine with datacenter. Encode these rules as filter configurations that restrict the candidate pool before scoring begins, so the algorithm only considers appropriate proxy types for each target.

Add Cooldown and Recovery Logic

When a proxy fails against a target, it should not immediately be excluded from all future requests. Implement graduated cooldown based on failure severity and frequency. A single timeout might just lower the proxy's health score without triggering cooldown. Two consecutive failures against the same target trigger a short cooldown (1 to 5 minutes). Continued failures after cooldown recovery trigger progressively longer cooldowns using exponential backoff: 5 minutes, then 15 minutes, then 1 hour, then 4 hours.

Cooldown should be target-specific, not global. A proxy blocked by Amazon might still work perfectly for other targets. Its cooldown for Amazon should not prevent it from serving requests to other domains. Maintain separate cooldown timers per proxy per target domain to maximize proxy utilization.

After cooldown expires, do not immediately restore the proxy to full rotation. Instead, use a "probation" state where the proxy receives a small percentage of traffic (1 to 5% of its normal volume) to test whether the underlying block has cleared. If probation requests succeed, gradually increase the proxy's traffic allocation back to normal. If probation requests fail, extend the cooldown with longer backoff. This prevents flooding a still-blocked proxy with traffic immediately after cooldown expiry.

Set a maximum failure threshold that permanently retires proxies from the pool for a specific target. If a proxy fails 50 consecutive requests against one target with multiple cooldown cycles, it is likely permanently blocked by that site and should not waste further requests. Remove it from that target's candidate pool entirely while keeping it available for other targets where it still functions.

Monitor Pool Health and Set Up Alerts

Aggregate pool metrics provide visibility into overall system health. Track these at minimum: total active proxies (not in cooldown), percentage of pool in cooldown by target, aggregate success rate across all proxies by target, average response time trending, total bandwidth consumed per provider (for cost tracking), and requests per minute throughput.

Set alert thresholds on critical metrics. If the aggregate success rate drops below 70% for any target, something has changed (the target updated its anti-bot rules, your proxy provider is having issues, or your request patterns have become detectable). Alert immediately so you can investigate and adjust. If more than 50% of your pool enters cooldown for a single target simultaneously, you have a systematic problem rather than individual IP issues.

Build a simple dashboard or log output that shows pool state at a glance. For each target domain, display: active proxy count, average success rate, requests in the last hour, and failures in the last hour. For each provider, show: bandwidth consumed today, current cost tracking, and average latency. This visibility prevents surprises on your monthly proxy bill and catches degradation before it impacts data collection completeness.

Log every proxy selection decision with enough detail to debug problems later. Record which proxy was selected, what factors influenced the selection, whether the request succeeded or failed, and the response time. This audit trail helps you tune scoring weights, identify misconfigured proxies, and understand why certain targets experience higher failure rates at certain times.