Infrastructure monitoring is the practice of tracking the health, performance, and availability of the systems an application runs on: servers, containers, networks, databases, and cloud resources. It watches the layer beneath your code, so you can catch a full disk or a maxed-out CPU before it takes the application down.
Definition: What Is Infrastructure Monitoring?#
Infrastructure monitoring continuously collects metrics from the compute, storage, and network resources that host your software. Where application monitoring looks inside the app, infrastructure monitoring looks at the foundation it sits on.
The goal is to know that the underlying resources are healthy and have headroom, and to be warned before they run out.
What It Monitors#
- Compute: CPU and memory usage on servers, VMs, and containers
- Storage: Disk space, I/O, and latency
- Network: Bandwidth, packet loss, and connectivity between systems
- Containers and orchestration: Pod health, restarts, and resource limits in Kubernetes
- Databases: Connections, query latency, and replication health
- Cloud services: Managed resources like load balancers, queues, and storage buckets
Key Metrics#
The classic resource signals to watch:
| Metric | Why it matters |
|---|---|
| CPU usage | Sustained high CPU means requests start queuing |
| Memory | Exhaustion leads to crashes and OOM kills |
| Disk space | A full disk takes services down hard and fast |
| Disk I/O | Slow storage shows up as slow everything |
| Network | Saturation or loss degrades every dependent service |
Infrastructure Monitoring vs APM vs Observability#
| Type | Looks at |
|---|---|
| Infrastructure monitoring | Servers, containers, network, resources |
| Application monitoring (APM) | Inside the app: latency, errors, traces |
| Uptime monitoring | Is the service reachable from outside |
| Observability | Asking new questions from metrics, logs, traces |
These layers complement each other; see observability vs monitoring for how they relate.
Agent-Based vs Agentless#
- Agent-based: A small program on each host collects detailed metrics. Rich data, but agents to deploy and maintain.
- Agentless: Metrics are pulled from existing APIs (cloud provider, SNMP). Less to install, usually less depth.
Most setups mix both: agents where you need detail, agentless for managed cloud resources.
Limitations to Know#
- Healthy infrastructure is not a healthy app. Every server can be green while a code bug breaks checkout. Pair it with APM and outside-in checks.
- Metric volume and cost. Thousands of hosts and containers produce huge metric volumes; retention and cardinality drive cost.
- Thresholds need tuning. Static thresholds cause false alarms as load patterns change.
Best Practices#
- Alert on what predicts user impact. A disk trending toward full matters more than a brief CPU spike.
- Watch trends, not just current values. Saturation is usually gradual; catch it early.
- Cover the whole stack. Hosts, containers, network, and managed services, not just servers.
- Combine layers. Infrastructure plus application plus availability monitoring gives the full picture.
Conclusion#
Infrastructure monitoring tracks the compute, storage, network, and cloud resources beneath your application, warning you before a resource runs out and takes the service down. It is one layer of a complete picture, strongest alongside application monitoring and outside-in availability checks.
ObserveOne covers that outside-in layer: uptime and website monitoring from multiple regions, confirming real users can reach the app while your infrastructure tools watch the resources underneath.