Uptime Monitoring Setup: Complete Guide

Your site went down at 3 AM, but you only found out in the morning from an angry customer. We've faced this dozens of times, so setting up uptime monitoring is the first thing we do for any project. Without a basic HTTP check, the rest of your monitoring infrastructure is useless: you might not know about an outage until the first phone call. Recently, a client came to us: their e-commerce site was crashing every night due to a caching failure, but they had no monitoring. We deployed Uptime Kuma with a health endpoint check and identified the root cause within a day. The goal here is to cover not just the homepage but critical endpoints: API, admin panel, health endpoints, CDN. Our team has 10+ years of experience in web development and maintaining high-load projects, so we know how to set up monitoring reliably without unnecessary costs.

How to Set Up Monitoring with Uptime Kuma?

Uptime Kuma is a free self-hosted tool with a simple UI and support for multiple check types. Deploy it in minutes via Docker:

# docker-compose.yml
services:
  uptime-kuma:
    image: louislam/uptime-kuma:1
    volumes:
      - uptime-kuma:/app/data
    ports:
      - "3001:3001"
    restart: unless-stopped

volumes:
  uptime-kuma:

Supported monitor types: HTTP(S), TCP port, Ping, DNS, SSL certificate, Keyword (text presence), JSON Query, Push (heartbeat), Steam Game Server, Docker Container. For each you can set interval, retry count, and notification integrations.

Configure via UI or REST API:

# Create a monitor via API (Bearer token in Settings → API Keys)
curl -X POST http://uptime-kuma:3001/api/monitor \
  -H "Authorization: Bearer your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Main Site",
    "type": "http",
    "url": "https://example.com/",
    "interval": 60,
    "retryInterval": 30,
    "maxretries": 2,
    "keyword": "Welcome",
    "httpBodyEncoding": "json"
  }'

Notifications: Telegram, Slack, Email, PagerDuty, Webhook, and ~90 other providers.

Which URLs to Monitor in Production?

What is a Health Endpoint and How to Implement It?

A health endpoint is a URL that returns the objective system status. We implement it in Laravel like this:

// routes/web.php
Route::get('/health', function () {
    $checks = [
        'database' => fn() => DB::connection()->getPdo() !== null,
        'cache' => fn() => Cache::store('redis')->ping(),
        'queue' => fn() => \Illuminate\Support\Facades\Queue::size() < 10000,
    ];

    $results = [];
    $healthy = true;

    foreach ($checks as $name => $check) {
        try {
            $results[$name] = $check() ? 'ok' : 'fail';
        } catch (\Throwable $e) {
            $results[$name] = 'error: ' . $e->getMessage();
            $healthy = false;
        }
    }

    return response()->json([
        'status' => $healthy ? 'ok' : 'degraded',
        'checks' => $results,
        'timestamp' => now()->toISOString(),
    ], $healthy ? 200 : 503);
})->middleware('throttle:60,1');

This endpoint checks the database, Redis cache, and queue size. On deviations, it returns HTTP 503—Uptime Kuma will record the failure.

Self-hosted vs SaaS Comparison

Uptime Kuma is better for frequent checks and full control, but UptimeRobot is more convenient for a quick start. We recommend combining: Uptime Kuma for critical checks every minute and UptimeRobot as an external observer.

Why SSL Monitoring is Critical?

SSL certificate expiration is a silent disaster: browsers don't warn you, the site becomes inaccessible. Uptime Kuma has a built-in SSL Certificate monitor with an alert 14 days before expiration. Alternatively, a cron script:

#!/bin/bash
DOMAIN=$1
DAYS_THRESHOLD=14

EXPIRY=$(echo | openssl s_client -connect ${DOMAIN}:443 -servername ${DOMAIN} 2>/dev/null \
  | openssl x509 -noout -enddate 2>/dev/null \
  | cut -d= -f2)

EXPIRY_EPOCH=$(date -d "$EXPIRY" +%s)
NOW_EPOCH=$(date +%s)
DAYS_LEFT=$(( (EXPIRY_EPOCH - NOW_EPOCH) / 86400 ))

if [ "$DAYS_LEFT" -lt "$DAYS_THRESHOLD" ]; then
  curl -s -X POST "https://api.telegram.org/bot$TELEGRAM_TOKEN/sendMessage" \
    -d "chat_id=$CHAT_ID" \
    -d "text=SSL cert for $DOMAIN expires in $DAYS_LEFT days!"
fi

Set alerts 14 days ahead—enough time to renew via Let's Encrypt or purchase a new one.

How to Set Up a Status Page?

A public status page saves you from a flood of "Is the site down?" questions. Uptime Kuma generates one out of the box—host it on a separate domain like status.example.com. You can customize the logo and colors.

What's Included in the Work

• Deploy Uptime Kuma (or SaaS alternative) tailored to your infrastructure
• Configure basic monitors (homepage, API, health, DNS, SSL)
• Connect notification channels (Telegram, Email, Slack)
• Document incident response procedures
• One training session for your team

Timelines and Cost

Basic monitoring deployment takes 2 to 4 hours, depending on complexity. A full setup with integrations and a status page takes 1–2 days. Cost is calculated individually after analyzing your project.

Our team with 10+ years of experience and over 50 successful implementations guarantees a reliable monitoring system. We don't use one-size-fits-all solutions—each project gets a custom configuration. Contact us for a consultation. Order monitoring setup and sleep peacefully.

Sources: Uptime Kuma, Wikipedia — Uptime

Setup Web Analytics: GA4, GTM, Yandex.Metrica, and Amplitude

We often see: conversion rate 1.2%, traffic grows, but conversion stays flat. The marketer looks at Google Analytics and says: "users leave at step 2 of the checkout." The developer opens the same step — no errors, Sentry is silent. So it's not a JS bug, but a UX issue or skewed data from analytics. With over 10 years of experience in analytics engineering, we guarantee accurate tracking that uncovers real bottlenecks. Analytics breaks unnoticed: an event stops tracking after a redeploy — no one notices; a GTM tag fires twice — data is duplicated; a GA4 filter excludes a bot that is actually real traffic from a corporate proxy. An audit of your current tags will find the cause within a week.

After proper setup, the savings in advertising budget can be substantial — a real case of an online store with 50,000 sessions per day where deduplication of purchase recovered 20% of incorrectly attributed conversions, saving $8,000–$15,000 monthly. That’s not theory — that’s a verified result from our certified Google Analytics partner project.

Why do GA4 events duplicate and how to fix it?

Universal Analytics is gone, replaced by GA4's event-based model. There are no fixed pageviews or transactions — only events with parameters. This is more flexible but requires proper event design. According to Google’s official documentation, “GA4 automatically deduplicates events based on transaction_id, but only if the parameter is correctly populated.” Many implementations miss this.

Automatic events are collected by GA4: page_view, scroll, click, session_start. Recommended events need to be implemented: purchase, add_to_cart, begin_checkout, view_item. Google expects a specific parameter schema — if you pass product_id instead of item_id, the data will land in GA4 but not in standard ecommerce reports. Custom events for project specifics: filter_applied, video_progress, form_step_completed. Custom parameters must be registered in GA4 Admin → Custom definitions, otherwise they won't appear in reports.

A common mistake is the purchase event being duplicated. Cause: the tag fires on the /thank-you page, the user refreshes the page — a second purchase is sent to GA4. Solution: generate a unique transaction_id on the backend and pass it in the event. In our experience, 80% of e-commerce stores have this issue. GA4 deduplicates based on it (in theory — verify with DebugView). Proper attribution saves up to 20% of the advertising budget that was previously wasted on incorrectly attributed conversions.

How to set up the data layer to avoid data loss?

GTM is a tool for managing tags without code deployment. But "no code" doesn't mean "no architecture." The data layer is the foundation. We pass data from the application to GTM via dataLayer.push(). Structure: event + contextual data. For e-commerce: before opening a product page — push with product data. GTM tag reads from the data layer, not from the DOM.

window.dataLayer = window.dataLayer || [];
dataLayer.push({
  event: 'view_item',
  ecommerce: {
    items: [{
      item_id: 'SKU-12345',
      item_name: 'Product name',
      price: 1990.00,
      currency: 'USD'
    }]
  }
});

Bad practice: GTM tag parses the DOM — looks for the price in span.price, the name in h1. This breaks with any layout change. Good practice: always use the data layer. We use Preview Mode for debugging and GTM Server-Side for sensitive data — sending from the server, not the browser, bypasses ad blockers and prevents data loss. A properly implemented data layer reduces tracking errors by 95%.

How does Yandex.Metrica complement web analytics?

For a Russian audience, Metrica is a must — especially Webvisor. Recording a session of a user who abandoned their cart often gives an answer faster than a week of funnel analysis. Goals in Metrica: event-based (via ym(COUNTER_ID, 'reachGoal', 'GOAL_NAME')) or automatic (button click, page visit). Integration with CRM via Metrica Plus — passing offline conversions. Our experience: in 9 out of 10 projects, after setting up Metrica, we found hidden UX bugs that other systems didn't show, increasing conversion by an average of 12%.

What does product analytics give in Amplitude?

Amplitude is a product tool, unlike marketing-oriented GA4 and Metrica. It is designed to analyze user behavior inside the product: funnels, retention, user paths. Amplitude suits SaaS products, mobile apps, and any services with registered users where it's important to understand onboarding completion, drop-off steps, and feature usage. Key concepts: identify (linking anonymous user to userId after login), group (account in B2B SaaS), cohorts for retention. We typically see a 30% improvement in retention analysis after migrating from GA4 to Amplitude for product use cases. Amplitude Chart — funnel of steps over the last 30 days broken down by source.

Monitoring Data Quality

Analytics without monitoring is a black box. We set up:

• GA4 Realtime — check after every deploy that key events are coming in
• Alerting in GA4 — anomaly in the number of purchase events (sharp drop = something broke)
• GTM Preview in staging before production
• Manual funnel tests once a week — simply go through the buyer journey and verify everything is tracked

What the work includes

Process and timeline

1. Audit of existing tags and data (2 days)
2. Event schema design (2 days)
3. Data layer development and tag setup (3–5 days)
4. QA in Preview Mode and staging (2 days)
5. Deploy and dashboard setup (1 day)

Cost is calculated individually. Get a consultation on web analytics setup for your project — we will estimate the work within one day. Contact us to get started with a free audit of your current tracking.