Monitor storage as a set of related signals across workloads, pools, services, hosts, and devices—not as one cluster-wide utilization number. Track read and write IOPS, throughput, latency, capacity with clearly defined accounting, and recovery behavior together. Ceph provides a useful documented example, but its metric names and defaults are product-specific; verify them against the release you run.
Start with service outcomes and the storage layers
Decide which client operations and workloads matter, what degradation should trigger an alert, and which tenants, pools, or volumes need separate visibility. Map the path from client or tenant through pool or volume, storage service, host, device, and network, including the monitoring pipeline itself. This lets an operator connect a user-visible symptom to the layer where it originates.
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Set service objectives and alert thresholds from application requirements and representative workload baselines. Ceph’s documentation describes metrics and dashboards, but does not prescribe universal service-level objectives or thresholds.
Collect performance signals as a set
IOPS, throughput, and latency answer different questions. IOPS describes the rate of operations, throughput describes the volume of data moved, and latency describes request delay. Collect read and write measurements separately: a healthy change in one may conceal a problem in the other.
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Client and pool performance
At the client or pool level, collect read and write operation rates, bytes per second, and latency. Ceph’s monitoring documentation gives PromQL examples using ceph_osd_op_r, ceph_osd_op_w, ceph_osd_op_r_out_bytes, and ceph_osd_op_w_in_bytes, along with latency counters. These are Ceph-specific names, not universal storage metrics. Check definitions and labels for the release in use before adopting queries: Ceph Monitoring Overview.
Read rate, throughput, and latency together. Throughput can rise because demand is growing; rising latency at a stable operation rate may instead indicate contention or saturation. Where the platform exposes latency distributions or percentiles, examine them alongside averages. Choose acceptable levels from application objectives and validated baselines; the cited Ceph material does not establish universal latency targets.
Object workload visibility
Ceph Object Gateway exposes operation counts, bytes, and latency, including put and get metrics. Its documentation describes sending these metrics to Prometheus to build cluster-wide usage views. This gives object workloads a useful view beyond generic cluster aggregates: Ceph Object Gateway metrics.
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Track capacity with explicit accounting
Capacity metrics are comparable only when they measure the same thing. Distinguish physical or raw capacity consumed from client data stored before protection, and label each series clearly. In Ceph, ceph_osd_stat_bytes reports OSD capacity; ceph_pool_bytes_used represents raw capacity consumed, including metadata and redundancy; and ceph_pool_stored represents client data before data protection. Treat these as distinct measures, not interchangeable definitions of “used.” See the Ceph monitoring metric examples.
Show current headroom and configured warning or danger state together. The Ceph Dashboard describes used capacity and warning/danger states associated with nearfull and full thresholds. Make threshold status legible in text or numbers as well as color: Ceph Dashboard documentation.
Forecasting requires a consumption history and a stated planning horizon. Document the local forecasting method and its uncertainty, and account for planned growth, protection overhead, metadata, uneven placement, maintenance, and degraded recovery. The cited sources do not prescribe a universal reserve percentage or forecasting formula.
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Drill down from cluster averages to nodes and devices
A cluster aggregate can look healthy while a particular OSD or physical drive is overloaded. Keep per-OSD views and pair storage-system counters with host and device metrics. Ceph documents label-based per-OSD queries and describes combining node-exporter data with Ceph metrics to derive physical-media performance information: Ceph Monitoring Overview.
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Plan for failure and recovery, not just steady-state usage
Monitor cluster health, daemon and service availability, recovery throughput, and capacity-threshold state. Recovery consumes resources and shifts placement, so capacity that appears adequate in a healthy state may not be adequate after a failure.
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Ceph’s hardware recommendations warn that losing a host containing a large share of cluster capacity can cause recovery to push OSDs beyond the full ratio, mon_osd_full_ratio. Ceph halts operations in that condition to prevent data loss. Assess headroom by failure domain and under realistic loss scenarios, rather than assuming capacity is evenly distributed: Ceph Hardware Recommendations.
Visualize and alert on actionable symptoms
Ceph’s documented monitoring stack uses ceph_exporter for daemon performance counters and a manager Prometheus module for cluster-level metrics. The project identifies Prometheus, Alertmanager, Grafana, and scripting as options for exploration and customized monitoring; its Dashboard surfaces selected health, capacity, and utilization views. See the monitoring overview and Dashboard documentation.
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When choosing an approach, compare coverage of workloads, pools, services, hosts, devices, and network; resolution and retention; metric semantics; scale and label cardinality; integration with alerting and incident workflows; failure-domain analysis; and compatibility with the deployed storage version. These factors determine whether the system can show a brief incident, explain an apparent capacity discrepancy, and support a recovery decision.
Interpret metric limitations before acting
CephFS subvolume I/O is windowed
CephFS subvolume IOPS, throughput, and latency are calculated over a sliding window. The documented default is 30 seconds, configurable with subv_metrics_window_interval; this is a CephFS implementation default, not a general storage-monitoring standard. The same metrics do not update for metadata-only actions such as directory and attribute operations, so they do not represent the complete metadata workload. See CephFS metrics documentation.
Metric availability and meaning can vary
Ceph metrics and labels differ by daemon and release. The cited latest documentation identifies itself as development documentation, so verify names and behavior against the installed release before deploying queries or alerts. The relevant references include the monitoring overview, CephFS metrics, hardware recommendations, and Object Gateway metrics.
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Control metric cardinality
Detailed labels can improve diagnosis but increase series volume, memory use, and monitoring cost. Ceph Object Gateway documentation cautions that exporting all metrics may be impractical in large systems and describes labeled counters stored in caches. Select dimensions that serve a concrete operational question before enabling every available metric: Ceph Object Gateway metrics.
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