Datadog Monitoring: Agent, APM, Logs & Alerts

Why Datadog for Server Monitoring?

Have you noticed your site loading slowly but can't pinpoint the bottleneck? Errors 500 without a stack trace, and users are leaving for competitors. We've faced this many times: production environment is a black box until you implement the right tooling. Datadog solves this: a SaaS monitoring platform with an agent on servers. It collects infrastructure metrics, APM (request tracing), logs, and synthetic tests in a single interface. Our engineers hold Datadog certifications and have 10+ years of web development experience, so we guarantee a quality turnkey setup.

Datadog cloud subscription starts at $15 per host per month, but our setup service pays for itself by preventing downtime. Datadog documentation confirms that companies using APM reduce mean time to root cause by 50%.

Why Datadog over Open-Source Stacks?

Prometheus + Grafana is a powerful combination, but it requires manual alert configuration, metric storage, and APM integration. Datadog provides ready-made dashboards, automatic service discovery (e.g., via Docker labels), and a unified interface for logs, metrics, and traces out of the box. Compare: setting up Prometheus from scratch takes 3–5 days, while Datadog takes 1–2 days. Additionally, Datadog supports 600+ integrations, including AWS, GCP, Azure, which is critical for hybrid infrastructure.

Problems We Solve with Datadog

Invisible Errors in Production

Without APM, you only see HTTP statuses. Datadog automatically collects error stacks and links them to specific transactions. For example, in Laravel we configure DDTrace\GlobalTracer to catch exceptions in services. This helps detect that OrderService::processOrder() fails with PDOException due to a PostgreSQL lock.

N+1 Queries and Slow SQL

Datadog APM shows the duration of each SQL query. We see that a catalog page makes 200 queries instead of 5. The solution: add eager loading or caching via Redis. Without Datadog, you'd be guessing; with it, you get exact numbers: avg: 342ms per query.

Memory Leaks and CPU Spikes

Infrastructure monitoring: system.cpu.user and system.mem.used. Datadog alerts trigger when CPU exceeds 85%. In one project, we found a memory leak in Node.js due to suboptimal setInterval. Datadog showed heap growth, and we replaced the loop with worker_threads.

How We Set Up Monitoring

The process includes several stages:

Agent Installation

# Ubuntu/Debian DD_API_KEY="your-api-key" DD_SITE="datadoghq.eu" \ bash -c "$(curl -L https://s3.amazonaws.com/dd-agent/scripts/install_script_agent7.sh)" # Docker docker run -d --name datadog-agent \ -e DD_API_KEY="your-api-key" \ -e DD_SITE="datadoghq.eu" \ -e DD_LOGS_ENABLED=true \ -e DD_LOGS_CONFIG_CONTAINER_COLLECT_ALL=true \ -e DD_APM_ENABLED=true \ -v /var/run/docker.sock:/var/run/docker.sock:ro \ -v /proc/:/host/proc/:ro \ -v /sys/fs/cgroup/:/host/sys/fs/cgroup:ro \ gcr.io/datadoghq/agent:7 

Agent Configuration

# /etc/datadog-agent/datadog.yaml api_key: your-api-key site: datadoghq.eu hostname: web01.example.com tags: - env:production - app:myapp - region:eu-west-1 logs_enabled: true apm_config: enabled: true process_config: enabled: true # Integrations integrations: nginx: - nginx_status_url: http://localhost/nginx_status php_fpm: - status_url: http://localhost/status ping_url: http://localhost/ping postgres: - host: localhost username: datadog password: ENC[k8s_secret,v1.0/namespace/secret/pass] dbname: myapp 

PostgreSQL: Monitoring User

CREATE USER datadog WITH PASSWORD 'secure-password'; GRANT pg_monitor TO datadog; GRANT SELECT ON pg_stat_database TO datadog; 

APM for Laravel

// composer.json // "datadog/dd-trace": "^0.90" // Custom operation tracing use DDTrace\GlobalTracer; class OrderService { public function processOrder(Order $order): void { $tracer = GlobalTracer::get(); $span = $tracer->startActiveSpan('order.process'); try { $span->setTag('order.id', $order->id); $span->setTag('order.total', $order->total); $this->validateInventory($order); $this->chargePayment($order); $this->sendConfirmation($order); } catch (\Throwable $e) { $span->setError($e); throw $e; } finally { $span->finish(); } } } 

Alerts via Datadog Monitor

resource "datadog_monitor" "cpu_high" { name = "High CPU on web servers" type = "metric alert" query = "avg(last_5m):avg:system.cpu.user{env:production} by {host} > 85" message = <<-EOT CPU usage exceeded 85% on {{host.name}}. @slack-monitoring EOT thresholds = { critical = 85 warning = 75 } notify_no_data = true renotify_interval = 60 tags = ["env:production", "app:myapp"] } resource "datadog_monitor" "error_rate" { name = "High error rate" type = "metric alert" query = "sum(last_5m):sum:trace.web.request.errors{env:production}.as_count() / sum:trace.web.request.hits{env:production}.as_count() * 100 > 5" message = "Error rate > 5% @pagerduty-oncall" thresholds = { critical = 5, warning = 2 } } 

How Datadog Helps Optimize Budget

Datadog reduces incident detection time by 2x compared to Prometheus+Grafana. Synthetic tests catch issues before they affect users. We set up monitoring for key scenarios (login, catalog, cart) in one day. Each prevented outage saves an average of $5000 per hour for e-commerce projects.

Timelines and What's Included

We connect to your project remotely via VPN. After setup, we hand over access and an operations manual. We guarantee stable monitoring: within 30 days after implementation, we fine-tune alerts and dashboards for free based on your feedback.

How Datadog Helps Find Bottlenecks

APM tracing shows every HTTP request from entry to exit. For example, in Laravel we see that OrderController@store takes 2.5 seconds, of which 2 seconds is an external API call. Without Datadog, it would be a black box. With Datadog, you know exactly: the problem isn't in your code but in a third-party service. Learn more about APM in the official Datadog documentation.

Order monitoring setup from us — get a free consultation. Contact us to discuss your project. We'll prepare a custom proposal within one business day.