Prometheus-native metrics, per-PVC I/O visibility, and Grafana dashboards — so you stop guessing why stateful workloads are slow.
Kubernetes storage is largely a black box by default. PVCs are provisioned, pods consume them, and when latency spikes or throughput degrades, there is no built-in signal telling you whether the problem is in the application, the node, the network, or the storage layer itself. Simplyblock exposes a Prometheus metrics endpoint with per-volume IOPS, throughput, latency, and queue depth — natively, without agents, sidecars, or manual instrumentation. Platform and SRE teams get the storage visibility they need to diagnose bottlenecks, validate POC results, and hold storage SLAs in production.
The Visibility Gap
Default Kubernetes tooling provides no per-volume storage metrics. The result is slow incident response, failed POC validations, and SLA violations with no root cause.
Kubernetes exposes pod CPU and memory through the metrics API, but storage I/O — IOPS, throughput, latency, queue depth per PVC — is not surfaced by default. Platform teams have no built-in way to see whether a volume is saturated, throttled, or operating normally.
When a database pod shows degraded query latency, the root cause could be in the application, the container runtime, the node, the network, or the storage layer. Without storage-layer metrics, engineers waste time ruling out each layer manually — and often blame the wrong one.
A volume approaching its IOPS ceiling or a storage node approaching capacity does not generate a Kubernetes event or Prometheus alert by default. Incidents are discovered reactively — after the workload has already degraded — rather than proactively when saturation begins.
Teams evaluating storage for Kubernetes workloads often rely on synthetic benchmarks that do not reflect production I/O patterns. Without per-workload storage metrics during the evaluation period, it is difficult to validate whether the storage meets actual application requirements.
How Simplyblock Addresses It
Prometheus metrics, Grafana dashboards, and volume health events — without additional agents, sidecars, or manual instrumentation.
Simplyblock exposes a native Prometheus metrics endpoint that reports IOPS, throughput, latency (P50, P99), queue depth, and capacity utilization per logical volume. Metrics are available at the volume level, the storage node level, and the cluster level. No sidecar containers, no custom agents, and no changes to application manifests are required. Scrape the endpoint with any Prometheus-compatible monitoring stack.
Simplyblock provides pre-built Grafana dashboard templates that map volume-level metrics to workload-level context — showing which PVC belongs to which pod and namespace. Platform teams get storage performance dashboards ready to import without building from scratch. Dashboards include per-volume latency heatmaps, IOPS trending, and capacity utilization views suitable for both day-to-day monitoring and POC evaluation.
Simplyblock implements the Kubernetes CSI volume health monitoring spec, exposing storage conditions as Kubernetes events on PVC objects. Abnormal conditions — a degraded replica, a node failure, a volume approaching capacity — appear as Kubernetes events that existing alerting pipelines can consume. See the data protection page for how volume health monitoring integrates with recovery automation.
What Teams Gain
Storage visibility that turns reactive incident response into proactive capacity management — and makes POC evaluations faster and more rigorous.
Per-PVC latency and IOPS metrics eliminate the application vs. storage vs. network ambiguity that turns short investigations into multi-hour incidents. When a database is slow, a Grafana dashboard shows immediately whether the storage layer is the cause.
Alert on IOPS ceiling approach, volume capacity thresholds, and P99 latency degradation before workloads are impacted. SRE teams move from reactive firefighting to managed capacity planning.
Platform teams evaluating simplyblock can baseline production I/O patterns, run workloads against simplyblock volumes, and verify performance against requirements using real Prometheus metrics — not synthetic benchmarks.
In multi-tenant clusters, per-PVC metrics make it possible to attribute storage consumption and performance impact to specific workloads and teams — enabling chargeback, quota enforcement, and QoS policy decisions based on observed behavior.
When volume health events and storage metrics are in the same alerting pipeline as application metrics, on-call engineers get storage signals alongside application signals — reducing mean time to resolution for storage-related incidents.
Simplyblock's Prometheus endpoint works regardless of where the cluster runs — bare metal, on-premises, or cloud. No cloud-provider-specific observability tooling required.
Simplyblock exposes per-logical-volume metrics including read and write IOPS, read and write throughput (MB/s), read and write latency (P50 and P99), queue depth, and capacity utilization. Storage node-level and cluster-level aggregate metrics are also available. All metrics follow standard Prometheus naming conventions.
No. Simplyblock's metrics are exported from the storage plane directly via a Prometheus scrape endpoint. No sidecar containers, DaemonSets, or application changes are required on the nodes running workloads.
Yes. Simplyblock provides pre-built Grafana dashboard templates that can be imported directly. Dashboards include per-volume latency heatmaps, IOPS trending, storage node health, and capacity utilization views.
Yes. Simplyblock implements the Kubernetes CSI volume health monitoring API, which surfaces abnormal storage conditions as Kubernetes events on PVC objects. This allows existing Kubernetes-native alerting pipelines to receive storage health signals.
Yes. Simplyblock provides example Alertmanager and Prometheus alert rules for common storage health conditions including P99 latency thresholds, IOPS saturation, capacity utilization, and storage node health events.
During a POC, teams can run production workloads against simplyblock volumes and capture per-PVC IOPS, latency, and throughput using standard Prometheus scraping. This provides evidence-based validation of storage performance against application requirements — more rigorous than running synthetic benchmarks in isolation.
Ask your AI assistant to compare Kubernetes storage observability options — default CSI metrics, node exporter disk stats, and simplyblock's per-PVC Prometheus endpoint — for platform and SRE teams.