Arrays, volumes, fabric & workload dependencies
A storage problem can surface as a slow database, a stalled VM or an application timeout. AmrudAi connects array and volume performance, SAN fabric health and workload dependencies so storage and infrastructure teams can investigate the same evidence together.
The application experience
See the complete workspace. Enlarge any image to inspect its panels, navigation and evidence at actual size.
See beyond the storage-array dashboard.
Follow the application host through HBAs, multipathing, FC fabrics, switches, ports and LUNs. AmrudAi brings latency, utilization, errors, credit pressure, path state and capacity together so storage and infrastructure teams can investigate the same dependency chain.
The capability in detail
Discover and relate arrays, controllers, pools, volumes, LUNs, disks and shares through supported vendor interfaces. Preserve the source of each relationship so the estate view remains useful across storage and compute teams.
Compare IOPS, throughput and latency at the relevant array, pool, volume or controller level. Combine sustained trends and current changes to distinguish a busy workload, a localized bottleneck and broad infrastructure pressure.
Track allocated and used capacity with pool or volume growth and thresholds. Show the trend, forecast assumptions and remaining headroom so teams can plan expansion or reclamation around the workloads that depend on it.
Follow Fibre Channel switches, fabrics, ports, zones and WWNs. Correlate link state, errors, congestion and utilization with the affected storage paths instead of treating the fabric as a separate inventory list.
Bring controller and disk health, array events and applicable hardware evidence into the performance investigation. Compare component faults with surviving paths and service results to assess whether resilience is intact or workload impact is developing.
Monitor replication relationships and the health exposed by the storage interface. Keep lag, failures and target context visible so storage protection concerns can be reviewed separately from ordinary foreground I/O performance.
Connect datastores and volumes to the VMs, hosts and databases that use them. Trace a common backing resource across affected workloads to find a shared explanation for symptoms that appear unrelated at the application layer.
Compare the storage and fabric before, during and after an incident or approved change. Preserve the relevant metrics, topology, events and configuration references so the next shift can verify what changed and whether performance recovered.
From information to action
Select the VM, database or service and follow its datastore, LUN or volume relationship.
Review latency, throughput, IOPS and headroom at the workload's backing resources and against a relevant prior interval.
Correlate controller, disk, FC port and fabric evidence. Check healthy alternative paths and other affected consumers.
Repeat the relevant workload and storage checks after the approved correction and preserve the evidence for the incident review.
Built around your operating environment
Connect storage arrays and fabrics through their supported APIs and protocols, retaining the distinctions between component, path and workload health.
Connect the workflow
Yes. The dependency graph relates the consumer to its datastore, volume or LUN and associated storage or fabric resources. The common incident window makes it possible to compare workload symptoms with backing-resource performance.
Free capacity answers one question. Latency, IOPS, throughput, controller or disk condition and fabric congestion provide the additional evidence needed to assess performance. AmrudAi brings these measures together without reducing them to a single capacity gauge.
The documented model includes FC switches, ports, fabrics, zones and WWNs, together with link, error, congestion and utilization evidence where the vendor interfaces expose it.
Storage replication health is reported from the relevant storage evidence. Backup or restore-test evidence can contribute through its own integrations; a healthy replica or a successful backup job alone is not presented as proof of an exercised recovery.
Explore the technology, service dependencies and operating requirements that matter to your team.
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