Full New Relic Setup Guide: Server Monitoring, APM, and Alerting

Imagine: your site suddenly slows down, users complain about errors. Logs show no obvious cause, server load is normal. Without observability, you could spend hours searching for the needle in a haystack. New Relic provides transparency for every transaction—from HTTP request to SQL query against the database.

One of our clients—an e-commerce store with 10,000 orders per day—faced TTFB rising to 3 seconds. After configuring New Relic, we found that a suboptimal Redis cache was the culprit. Optimization took 2 hours, and TTFB dropped to 300 ms. “New Relic saved us thousands in lost sales,” said their CTO. Such diagnosis without monitoring would have taken days, and customer loss would have been in the thousands.

The importance of server monitoring

Without monitoring, you're operating blind. If the site lags at a specific moment, you don't know whether the server, database, or external API is at fault. New Relic collects real-time metrics: CPU, RAM, disk I/O, network latency. This allows quick root cause identification, reducing MTTR by 60%.

Problems New Relic solves

• APM tracks every transaction: execution time, call count, errors. You see which endpoint is slowest—often the 95th percentile spike is due to a missing index.
• Infrastructure monitoring shows server load: if CPU is 90%, you may need an upgrade or optimization that saves 30% on cloud costs.
• Browser monitoring captures real user experience: LCP, CLS, INP. New Relic provides recommendations for improvement—we’ve seen 40% LCP reduction after implementing them.

New Relic Pro allows longer data retention and more flexible alerts. For most projects, the free tier is sufficient, but under heavy load we recommend Pro. Our setup costs start at $1,500 and typically pay back within a month through improved performance and reduced downtime.

What you get after setup (deliverables)

• Fully configured dashboards for infrastructure, APM, and business metrics
• Custom NRQL alerts targeting error rates, slow queries, and business events
• Agent deployment on all servers (Infrastructure, APM for PHP/Node.js)
• Team training session (1 hour) and written documentation
• 2 weeks of post-launch support for fine-tuning

How we set up New Relic: turnkey process

1. Analysis: identify critical transactions, endpoints, servers. We estimate 4 hours.
2. Install Infrastructure agent on all servers – we use automation scripts.
3. Install APM agent for PHP and/or Node.js – includes distributed tracing.
4. Configure custom metrics for business events (e.g., order placement).
5. Create NRQL alerts for errors and slow queries – we set thresholds based on your data.
6. Integrate with CI/CD: monitor versions after deployment.
7. Hand over documentation and train your team.

Agent installation and configuration

Install the Infrastructure agent with a single command:

curl -Ls https://download.newrelic.com/install/newrelic-cli/scripts/install.sh | \
  bash && sudo NEW_RELIC_API_KEY="NRAK-..." \
         NEW_RELIC_ACCOUNT_ID="1234567" \
         /usr/local/bin/newrelic install

Then configure /etc/newrelic-infra.yml:

license_key: your-license-key
display_name: web01.example.com
custom_attributes:
  environment: production
  app: myapp
  region: eu-west-1

For PHP, install the APM agent and add settings to php.ini:

wget https://download.newrelic.com/php_agent/archive/10.x.x/newrelic-php5-10.x.x-linux.tar.gz
tar -xzf newrelic-php5-*.tar.gz
cd newrelic-php5-*/
sudo ./newrelic-install install

extension = newrelic.so
newrelic.license = "your-license-key"
newrelic.appname = "MyApp (Production)"
newrelic.distributed_tracing_enabled = true
newrelic.transaction_tracer.enabled = true
newrelic.transaction_tracer.threshold = 500

For Node.js, install the newrelic module and add require('newrelic') as the first line in the entry point. Configuration via environment variables.

Custom metrics and NRQL alerts

Custom metrics allow tracking business indicators. Example in PHP:

newrelic_custom_metric('Custom/OrderProcessing/Duration', $durationMs);
newrelic_custom_metric('Custom/Orders/Total', $order->total);
newrelic_record_custom_event('OrderPlaced', [
    'orderId'  => $order->id,
    'userId'   => $user->id,
    'total'    => $order->total,
    'items'    => $order->items->count(),
]);

NRQL alerts allow instant reaction to anomalies. For example, an alert on error percentage: SELECT percentage(count(*), WHERE error IS true) FROM Transaction WHERE appName = 'MyApp (Production)' SINCE 5 minutes ago. Or a dashboard with top-20 slow database queries.

Typical setup mistakes

• Wrong license or API key. Agent cannot authenticate, data is not sent. Verify the key is active and matches the account.
• Distributed tracing not enabled. Transactions are not linked across services, losing the full picture. Enable via newrelic.distributed_tracing_enabled = true for PHP or config.distributed_tracing.enabled: true for Node.js.
• Too low alert threshold. Constant false alarms tire the team. Set thresholds based on statistics (e.g., 95th percentile).

What does New Relic observability provide?

After setup, you get a complete performance picture: response time of each transaction, server load, real user experience. This reduces diagnosis time from hours to minutes. For example, you can see that the 95th percentile response time has grown to 2 seconds, and immediately find the cause—a slow database query or a stuck external API.

Timelines and scope

Basic setup (Infrastructure + APM) takes 1 day. If custom metrics and alerts are needed—2-3 days. We hand over documentation and train your team. After launch, we provide 2 weeks of technical support.

Why choose us?

We've been in the market for over 10 years and have set up monitoring for 40+ projects on various stacks (PHP, Node.js, Python). Our engineers are certified in observability. We guarantee that after setup, you'll receive alerts about issues before they affect users. New Relic identifies root cause of failures 2x faster than competitors. Contact us for a free project estimate. Order our turnkey New Relic monitoring setup and get transparency into your application.

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.