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Reliability & Capacity

Catch issues weeks before they become incidents.

Memory leaks, capacity exhaustion, full PVs, and scheduling delays — Wave predicts them all weeks in advance.

The Problem

Kubernetes is good at restarting failed pods. It is not good at warning you before they fail. Memory leaks grow silently until OOMKill. Cluster capacity fills up until pods go pending. PVs hit 100% until services crash. Pod scheduling delays degrade latency until someone checks the scheduler queue. By the time alerts fire, the incident is already live.

The Wave Solution

  • 1Memory Leak Detection monitors abnormal memory growth trends and alerts your team hours-to-days before a pod hits its OOM limit.
  • 2Cluster Resource Forecast uses ML trend analysis to predict CPU, memory, and pod-count limit breaches 7–60 days in advance.
  • 3PV Capacity Forecast predicts storage exhaustion per volume, and PV Auto-Expansion automatically increases volume size before writes fail.
  • 4Pod Scheduling Delay Detection surfaces per-workload scheduling lag with root-cause breakdown — node pressure, resource fragmentation, or scheduler backlog.

Expected Outcomes

  • ✓OOM risk surfaced hours-to-days before kill — not after
  • ✓7–60 day advance notice for capacity exhaustion
  • ✓Zero storage outages from full PVs via automatic expansion
  • ✓Per-workload scheduling delay visibility with actionable root cause

"We only find memory leaks when OOMKill wakes someone at 3 a.m."

Threshold-based alerts miss slow-burn memory growth. By the time a pod hits its Limit and gets killed, the incident is already live and the on-call is paged.

OOM risk prediction hours-to-days before kill
Memory Leak DetectionAlerts

"We ran out of cluster capacity before procurement arrived"

Growth trends are visible in Grafana, but no one's forecasting them. The cluster fills up, pods go pending, and capacity requests become emergencies instead of quarterly plans.

7–60 day cluster resource forecast
Cluster Resource Forecast

"A PV filled up and took a whole service down"

Persistent Volume growth is invisible until the disk is 100% full. Then writes fail, services crash, and teams scramble to resize manually.

PV capacity forecast + automatic expansion before exhaustion
PV Capacity Forecast

Frequently Asked Questions

How early can Wave predict capacity exhaustion?▼
Wave's Cluster Resource Forecast uses ML trend analysis to predict CPU, memory, and pod-count limit breaches 7–60 days in advance. This converts capacity requests from emergencies into planned quarterly procurement — teams get actionable forecasts long before pods go pending.
Can Wave detect memory leaks before OOMKill happens?▼
Yes. Wave's Memory Leak Detection monitors abnormal memory growth trends continuously. Unlike threshold alerts that only fire when a pod hits its Limit, Wave identifies slow-burn growth patterns hours to days before the OOMKill event — giving your team time to investigate and remediate without a 3 a.m. page.
Does Wave handle PV outages automatically?▼
Wave's PV Capacity Forecast predicts when a Persistent Volume will reach exhaustion per-volume, and PV Auto-Expansion automatically increases the volume size before writes fail. This eliminates the class of incidents where a full disk causes service crashes and teams scramble to resize volumes manually under pressure.

See how Wave catches issues before they become incidents

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