How to Monitor Proxy Performance Over Time

Proxies age like milk, not wine.

Just because a proxy works today doesn’t mean it’ll be useful tomorrow. Free and public proxies degrade fast—slowing down, getting blocked, or ghosting you entirely. If you’re using proxies for scraping, SEO, or automation, you need to track how each one’s performing over time. Otherwise, you’re wasting requests, bandwidth, and time.

Why Monitoring Matters

Monitoring isn't just about keeping score—it's about maintaining uptime and maximizing efficiency. Proxies are volatile by nature, especially public ones. A proxy that worked flawlessly yesterday may now be rate-limited, geo-blocked, or completely dead.

You need to know:

• Is this proxy still alive?
• Has latency spiked or dropped?
• Is it now blocked on Google, Netflix, Amazon, etc.?
• How has this proxy behaved over the last day, week, or month?

If you’re not tracking this, you’re flying blind—and wasting cycles retrying broken proxies.

Key Metrics to Track

• Uptime %: Track how often the proxy successfully connects versus how often it fails.
• Latency: Log how long the response takes—slow proxies bottleneck everything.
• Blocked Status: Check whether the proxy is being denied by high-value targets like search engines and ecommerce platforms.
• Last Checked: Timestamp every test so you know how fresh your data is.

Sample Python Logger

import requests
import time
from datetime import datetime

proxy = {
  'http': 'http://123.45.67.89:8080',
  'https': 'http://123.45.67.89:8080'
}

def test_proxy():
    start = time.time()
    try:
        r = requests.get('http://httpbin.org/ip', proxies=proxy, timeout=5)
        latency = round(time.time() - start, 2)
        return True, latency
    except:
        return False, None

alive, latency = test_proxy()
timestamp = datetime.utcnow().isoformat()

with open("proxy_log.csv", "a") as f:
    f.write(f"{timestamp},{proxy['http']},{alive},{latency}\n")

This logs each test with a timestamp, proxy IP, status, and latency—perfect for tracking performance history.

Advanced Tips for Ongoing Monitoring

• Automate with Cron: Set up your logger script to run every 10–30 minutes using a cron job or task scheduler.
• Use SQLite or MySQL: For more complex tracking and filtering, use a database to log proxy results.
• Visualize with Charts: Use tools like matplotlib (Python) or Google Sheets to plot latency and uptime trends.
• Track Failures: Keep a failure counter for each proxy—retire any that fail X times in a row.
• Include Target Checks: Try accessing Google, Amazon, or Netflix and log their response codes too.

What to Do with the Data

Once you have a history of performance, you’ll see which proxies are worth keeping. Rank them by uptime and latency. High performers can be moved to a production list, while poor performers can be discarded or flagged for manual testing.

Over time, this helps you build a lean, reliable proxy pool instead of constantly playing whack-a-mole with flaky IPs. You’ll waste less bandwidth, get fewer bans, and scrape more data—faster and smarter.

Real-World Use Case

Let’s say you're running a sneaker monitor or price tracker. By logging latency and failures, you’ll quickly spot proxies that fall behind. Drop them before they slow down your system—or worse, get you rate-limited on the target site. It's proactive performance management.

Final Thoughts

You wouldn’t drive cross-country without a dashboard. Don’t run proxies blind. Monitoring transforms guesswork into informed strategy—helping you avoid downtime, scale your operations, and keep your infrastructure sharp.

Watch your proxies. Watch your success grow.