The Complete Guide to Server Monitoring (2026)

Server monitoring provides visibility into what's happening inside your infrastructure. While uptime monitoring tells you IF a service is responding, server monitoring tells you WHY—CPU overloaded, memory exhausted, disk full, or process crashed.

This guide covers everything: what to monitor, how monitoring works, tool options, and how to combine server metrics with uptime monitoring.

Table of Contents

1. What Is Server Monitoring
2. Why Server Monitoring Matters
3. Key Metrics to Monitor
4. Agent-Based vs Agentless
5. Setting Up Server Monitoring
6. Alerting on Server Metrics
7. Combining with Uptime Monitoring
8. Tools and Options
9. Common Mistakes
10. Related Resources

What Is Server Monitoring

Server monitoring is the continuous collection and analysis of metrics from your servers:

Server Metrics:
├── CPU usage (system, user, idle)
├── Memory consumption (used, available, swap)
├── Disk space and I/O
├── Network traffic (in/out)
├── Running processes
└── System load

These metrics are collected by software (an agent) running on your servers and sent to a monitoring platform for visualization and alerting.

Learn more: What Is Server Monitoring vs Website Monitoring

Why Server Monitoring Matters

The Blind Spot Problem

Without server monitoring, incidents look like this:

Alert: API timeout
├── What's wrong? Unknown
├── SSH into server
├── Run htop → CPU at 98%
├── Run df -h → Disk at 45%
├── Run free -m → Memory at 92%
├── Root cause found: Memory exhaustion
└── Time to diagnose: 15 minutes

With server monitoring:

Alert: API timeout
├── Dashboard: CPU 45%, Memory 92%, Disk 45%
├── Root cause: Memory exhaustion
└── Time to diagnose: 30 seconds

Learn more: Why Most Uptime Tools Miss Server Failures

Predictive Awareness

Server monitoring catches problems before they cause outages:

Warning: Disk at 85%
├── Current: 85%
├── Growth rate: 2%/day
├── Time to 100%: ~7 days
└── Action: Clean up or expand storage

Incident Context

During incidents, server metrics provide essential context:

Key Metrics to Monitor

CPU Metrics

What high CPU means:

• Compute-bound workload
• Runaway process
• Traffic spike
• Inefficient code

Memory Metrics

What high memory means:

• Memory leak
• Undersized instance
• Too many processes
• Need for optimization

Disk Metrics

What high disk means:

• Growing logs
• Accumulated data
• Need for cleanup
• Need for expansion

Network Metrics

Process Metrics

Agent-Based vs Agentless

Agent-Based Monitoring (Recommended)

An agent runs on your server and collects metrics locally:

Your Server
├── Agent (lightweight process)
│   ├── Collects CPU, memory, disk metrics
│   ├── Monitors running processes
│   └── Sends data to monitoring service
└── Your applications

Pros:

• Detailed metrics
• Efficient (local collection)
• Works behind firewalls
• Process-level visibility

Cons:

• Requires installation
• Agent maintenance

Learn more: Agent-Based Monitoring

Agentless Monitoring

Metrics collected remotely via SNMP, SSH, or APIs:

Monitoring Server → SSH/SNMP → Your Server
                              ├── Run commands
                              └── Parse output

Pros:

• No installation on target
• Works with managed devices

Cons:

• Less detailed
• Network dependent
• Credential management
• Scales poorly

Learn more: Why Agentless Monitoring Fails at Scale

Recommendation

For servers you control: use agent-based monitoring. Modern agents are lightweight (10-20MB memory), secure, and provide much better visibility.

Setting Up Server Monitoring

Step 1: Choose Your Tool

Step 2: Install Agent

Example with Wakestack:

curl -sSL https://wakestack.co.uk/install.sh | bash

The agent:

• Installs as a system service
• Starts automatically
• Uses minimal resources
• Reports to your dashboard

Step 3: Configure What to Monitor

Typically automatic, but you may want to:

• Set specific process monitoring
• Adjust collection intervals
• Configure custom metrics

Step 4: Set Up Alerts

Define thresholds:

CPU > 85% for 5 minutes → Warning
CPU > 95% for 5 minutes → Critical

Memory > 85% → Warning
Memory > 95% → Critical

Disk > 80% → Warning
Disk > 90% → Critical

Step 5: Create Dashboards

Organize visibility:

Production Dashboard:
├── api-prod-01
│   ├── CPU: 45%
│   ├── Memory: 62%
│   ├── Disk: 55%
│   └── Processes: nginx, node
├── api-prod-02
│   └── ...
└── db-prod-01
    └── ...

Alerting on Server Metrics

What to Alert On

What NOT to Alert On

• Normal fluctuations (CPU spike to 70% for 30 seconds)
• Scheduled high usage (batch jobs)
• Non-critical systems during off-hours

Learn more: The Difference Between Monitoring and Alerting

Alert Routing

Combining with Uptime Monitoring

The most powerful setup combines both:

Unified Dashboard

Production API Server
├── External Checks
│   ├── HTTP /health → 200 OK (145ms)
│   └── HTTP /api/status → 200 OK (89ms)
│
└── Server Metrics (via agent)
    ├── CPU: 45%
    ├── Memory: 62%
    ├── Disk: 55%
    └── Processes: nginx ✓, node ✓

Correlated Alerting

When an uptime check fails, immediately see server context:

Alert: api.example.com/health timeout

Context:
├── Server: api-prod-01
├── CPU: 98% ← Root cause
├── Memory: 72%
├── Disk: 45%
└── Process: node at 95% CPU

Learn more: Why Uptime Checks Alone Don't Work | Infrastructure-Aware Monitoring

Nested Host Organization

Organize monitors under their servers:

api-prod-01 (Server)
├── Agent metrics
└── Monitors
    ├── /health
    ├── /api/v1/status
    └── Port 5432 (database)

Learn more: How Nested Infrastructure Changes Monitoring

Tools and Options

Wakestack (Recommended for Combined)

Uptime + server monitoring + status pages:

Try Wakestack free

Self-Hosted Options

Enterprise Options

Learn more: Best Uptime Monitoring Tools | Hidden Costs of Datadog

Common Mistakes

1. Only Monitoring Uptime

Uptime alone doesn't explain WHY things fail.

Fix: Add server monitoring for root cause visibility.

2. Alerting on Every Spike

Short CPU spikes are normal; alerting on them causes fatigue.

Fix: Require sustained duration (e.g., > 85% for 5 minutes).

3. Same Thresholds for All Servers

Database server memory usage differs from web server.

Fix: Tune thresholds per server role.

4. Ignoring Disk Growth

Disk filling up is preventable but often missed.

Fix: Monitor disk with 80% warning threshold.

5. No Process Monitoring

Server can be "healthy" while critical process is down.

Fix: Monitor that expected processes are running.

6. Separate Dashboards

Uptime tool + server tool + logs = context switching during incidents.

Fix: Use unified monitoring (Wakestack) or correlate manually.

Related Resources

Foundational Concepts

• What Is Server Monitoring vs Website Monitoring
• What Is Agent-Based Monitoring
• Why Uptime Checks Alone Don't Work

Implementation

• Agent-Based Monitoring Guide
• How to Monitor Internal Services
• Why Agentless Monitoring Fails at Scale

Integration

• Infrastructure-Aware Uptime Monitoring
• How Nested Infrastructure Changes Monitoring
• Why Most Uptime Tools Miss Server Failures

Related Guides

• Uptime Monitoring Guide
• Status Page Guide

Get Started

Ready to set up server monitoring? Wakestack offers:

• Server agent — Lightweight Go agent for Linux
• Key metrics — CPU, memory, disk, network
• Process monitoring — Track running processes
• Combined view — Uptime + server metrics together
• Nested hosts — Organize monitors under servers

Start monitoring for free — Install the agent in under 2 minutes.