See infrastructure change cascades before they cascade
The Impact Intelligence Verification Graph Engine (VGE) maps infrastructure change dependencies across:
- Racks, power circuits, and cooling dependencies
- Network topology and redundant path analysis
- Service tiers, SLA commitments, and customer impact
- Maintenance windows and change request scheduling
Preview mode lets you model decommissions, migrations, and maintenance before your change window opens.
Rack dependency traversal
Map every dependency before decommission or migration:
- Services, network paths, and power circuits
- Cooling dependencies and capacity thresholds
- Cross-rack redundancy relationships
Service tier impact prediction
Identify customer and service impact before scheduling:
- SLA-protected customers affected
- Critical services and failover readiness
- Service tier degradation risk
Maintenance window orchestration
Detect conflicts before approving change requests:
- Scheduling conflicts across maintenance windows
- Capacity constraints and resource contention
- Redundancy violations during overlapping changes
Console preview
Change intelligence report
Seed change
Rack decommission: RACK-DC2-R14 - 9 services, 2.8 kW power draw
Change impact
47 of 250 nodes (19%)
across 5 domains
Severity hotspots
4
critical
NRE estimate
$71K – $121K
likely $92K
Schedule delta
+12d
critical path
Impact cascade / sample path
Rack hosts 9 services - U18-U22, 2.8 kW draw
via dcim
2 PDU circuits require reprovisioning
via power_management
Cooling loop CL-07 rebalance needed
via cooling
3 VLANs need TOR switch migration
via network_topology
2 Tier-1 SLA commitments at risk
via service_catalog
2 other maintenance windows overlap this rack zone
- ├─ MW-0892 UPS firmware upgrade - Zone B power bus 3 shared nodes scheduled
- └─ MW-0887 Network fabric migration - spine switch pair 5 shared nodes in progress
Verification pack / draft
- 9 service migration validations
- 2 PDU circuit provisions
- 3 VLAN reassignments
- 2 SLA protection verifications
Cost estimate: NRE $71K – $121K (likely $92K) · Recurring +$340/mo
- ├─ Service migration labor: $24K – $36K (9 services across 3 teams)
- ├─ Power rebalancing: $8K – $14K (2.8 kW redistribution)
- ├─ Downtime risk: 4h maintenance window if hot migration fails
- ├─ Schedule penalty: +12d pushes next rack refresh cycle
- ├─ Recurring: +$340/mo temporary overflow to adjacent zone
The problem
Infrastructure changes hide cascading dependencies until it's too late
A routine rack decommission looks straightforward in your DCIM tool until you discover it affects 23 services, 5 network paths, 2 SLA-protected customers, and conflicts with 3 other scheduled maintenance windows. By the time you've traced the dependencies manually, you've blown past your change approval deadline.
Hidden cost of blind changes
- Rack decommission affects 23 production services across 5 service tiers, discovered during execution instead of planning.
- Planned circuit maintenance triggers redundancy loss for 12 critical systems that share the same backup power path.
- Topology change breaks 7 redundant network paths, leaving SLA-protected services on single points of failure.
- Three overlapping change requests compete for the same rack, power, and cooling resources during a 4-hour maintenance window.
Key capabilities
Active intelligence for data centers + infrastructure changes.
Rack dependency traversal
Map every service, network connection, power circuit, cooling dependency, and cable plant link for any rack in seconds. See which customers, applications, and service tiers are affected before scheduling decommissions or migrations.
Service tier impact mapping
Identify which SLA-protected customers and critical services are downstream of any infrastructure change. Preview tier-1 production impacts before they become customer escalations.
Power and cooling cascade analysis
Trace power circuit dependencies across primary, backup, and UPS paths. Detect redundancy violations and capacity constraints before maintenance execution.
Network path verification
Validate that every affected service maintains redundant network paths after topology changes. Catch single-point-of-failure conditions before they reach production.
Maintenance window conflict detection
Preview resource contention and scheduling conflicts across overlapping change requests. Ensure capacity and redundancy requirements are met for every maintenance window.
Capacity rebalancing preview
Model rack migrations and service relocations against current capacity constraints. Identify power, cooling, and network bandwidth limits before starting moves.
SLA protection checking
Automatically flag changes that affect customers with service-level guarantees. Ensure tier-1 and tier-2 services maintain required redundancy during maintenance.
Cable plant impact assessment
Map fiber, copper, and power cable dependencies for any infrastructure change. Preview which cable paths need rerouting or replacement before cutting over.
How it works
From change signal to verified action.
Model your infrastructure graph
Import racks, services, power circuits, network topology, and service tier metadata from your DCIM, IPAM, and monitoring systems. EquatorOps builds a dependency graph linking physical infrastructure to logical services and customer SLAs.
Define impact analysis policies
Configure service tier rules (which tiers require redundancy), maintenance window constraints, capacity thresholds, and SLA protection requirements. Policies guide automated impact predictions.
Submit change requests with infrastructure context
Engineers submit change requests specifying racks, circuits, network devices, or services affected. EquatorOps accepts requests via UI, API, or ticketing system integration.
Traverse dependency graph in real-time
The impact analysis engine traverses from the change scope through physical and logical dependencies (rack placement, power circuits, cooling zones, network paths), then rolls up the impact to affected services, customers, and SLA tiers.
Detect conflicts and violations
Identify redundancy losses, capacity limit breaches, SLA protection failures, and maintenance window overlaps. Flag policy violations before change approval.
Preview impact in change approval UI
Engineers and change managers review a visual dependency map showing affected services, customers, and infrastructure. Drill into specific paths, tier breakdowns, and conflict details.
Execute with confidence or reschedule
Approve low-impact changes immediately. Reschedule high-impact changes to avoid conflicts, notify affected customers, or provision additional capacity. Every decision is backed by complete dependency visibility.
Hybrid graph model
EquatorOps models data center infrastructure as a directed graph where racks, services, power circuits, network devices, and cable paths are nodes. Edges represent physical dependencies (power, cooling, cabling), logical dependencies (service hosting, network routing), and policy constraints (SLA tiers, maintenance windows). Impact analysis traverses this graph to predict cascades.
Hosts
Rack hosts service (physical placement). Changes to rack assignment cascade through power circuits, cooling zones, and network paths that depend on physical location.
Powers
Power circuit supplies rack (primary or backup). Maintenance on a circuit surfaces every rack losing redundancy and every service at risk of single-point-of-failure.
Connects
Network device carries traffic for service (redundant or primary link). Topology changes reveal which services lose redundant connectivity and which SLA tiers drop below protection thresholds.
Data Centers + Infrastructure impact scenarios
Real change scenarios in data centers + infrastructure.
Impact Intelligence adapts to your domain’s change patterns, compliance frameworks, and verification workflows. These are representative output examples from the VGE computation pipeline.
Data Centers + Infrastructure
Services affected · SLA exposure · Power path changesTrigger
Rack migration
Impact
Power paths, network connections, service dependencies, customer SLAs
Verification Pack
Migration impact summary, power path verification, service dependency check
Metrics
Services affected · SLA exposure · Power path changes
Data Centers + Infrastructure
Customers affected · Routing changes · Redundancy impactTrigger
Network topology change
Impact
Service routing, customer connectivity, redundancy levels, monitoring coverage
Verification Pack
Network impact report, routing verification, monitoring update plan
Metrics
Customers affected · Routing changes · Redundancy impact
Data Centers + Infrastructure
Racks affected · Power budget delta · Cooling capacity changeTrigger
Capacity adjustment
Impact
Power allocation, cooling requirements, service headroom, growth constraints
Verification Pack
Capacity analysis, power budget update, cooling requirement revision
Metrics
Racks affected · Power budget delta · Cooling capacity change
Data Centers + Infrastructure
SLA windows at risk · Overlapping changes · Availability impactTrigger
Maintenance window request
Impact
Service availability, customer SLAs, overlapping change requests, incident readiness
Verification Pack
Window conflict analysis, SLA impact summary, incident response plan
Metrics
SLA windows at risk · Overlapping changes · Availability impact
Data Centers + Infrastructure
Procedures affected · Escalation changes · RTO impactTrigger
Incident response procedure update
Impact
Escalation paths, runbook steps, notification chains, recovery time objectives
Verification Pack
Procedure diff report, escalation update, RTO impact assessment
Metrics
Procedures affected · Escalation changes · RTO impact
Impact Intelligence for Data Centers + Infrastructure
Operational scale that makes impact analysis possible.
VGE runs on tenant-owned data: schema depth, API breadth, and deterministic telemetry that keeps change reviews consistent.
Domain providers
15+
5 cross-industry baseline + 10 domain-specific providers (composition structures, compliance, verification, 3D/geometric, procurement, inventory, capital assets, execution chains), each self-describing with SemVer and cost tiers.
Sync analysis
≤2s
Typical graph traversal (≤1K nodes) with batch-first providers and per-request caching.
Async analysis
≤30s
Complex traversals (≤10K nodes) with optional Redis acceleration and per-provider timing.
Impact demo
Impact Intelligence for Data Centers + Infrastructure
Preview change impact, severity scoring, and verification packs before approvals.
Change impact
47 nodes
Projected change
Severity hotspots
4
Projected change
NRE estimate
$92K
Projected change
Schedule delta
+12d
Projected change
Sample finding
Map every dependency before decommission or migration:
Impact cascade
Model your infrastructure graph
Hosts
Powers
Connects
API preview
Schema-stable endpoints for impact intelligence.
Impact Intelligence is designed as a tenant-owned API surface with preview-first semantics, deterministic run snapshots, and export-ready results.
Preview vs apply
Every request can run in preview mode to generate impact results without mutating data. Apply mode uses idempotency keys to persist verification packs safely.
View developer docsPOST Preview rack decommission impact
Preview impact of decommissioning a rack: affected services, network paths, power circuits, and customer SLAs.
POST /api/v1/change-controls/{id}/impact/runThe ChangeControl record (created separately) carries the change details: decommission RACK-DC2-R14 and migrate 9 hosted services to RACK-DC2-R31, change window CHG-2026-0934, affecting PDU-B-14 primary feed and cooling loop CL-07.
Request
{
"detect_collisions": true
}Response
{
"schema_version": "vge.graph_result.v1",
"run_id": 934,
"nodes": [
{
"node_ref": {
"resource_type": "service_instance",
"resource_id": 934001,
"display_name": "prod-payment-gateway / RACK-DC2-R14-U18",
"display_code": "SVC-PAY-GW-01",
"status": "Active - SLA Tier 1",
"tags": [
"Tier-1",
"PCI-DSS",
"redundancy-group-RG-04"
]
},
"severity": 0.95,
"depth": 1
},
{
"node_ref": {
"resource_type": "power_circuit",
"resource_id": 934002,
"display_name": "PDU-B-14 / Circuit C3 - Primary Feed",
"display_code": "PWR-DC2-PDU-B-14-C3",
"status": "Active - 12.4 kW allocated",
"tags": [
"208V/30A",
"UPS-backed",
"redundancy-pair-PWR-A-14"
]
},
"severity": 0.88,
"depth": 1
},
{
"node_ref": {
"resource_type": "network_path",
"resource_id": 934003,
"display_name": "TOR-DC2-R14 → SPINE-DC2-01 / VLAN 220",
"display_code": "NET-PATH-R14-SPINE01",
"status": "Active - dual uplink",
"tags": [
"10GbE",
"VLAN-220",
"BGP-peered"
]
},
"severity": 0.82,
"depth": 2
},
{
"node_ref": {
"resource_type": "sla_commitment",
"resource_id": 934004,
"display_name": "Acme Corp - 99.99% uptime SLA",
"display_code": "SLA-ACME-T1-2026",
"status": "Active - 3 services protected",
"tags": [
"Tier-1",
"penalty-clause",
"quarterly-review"
]
},
"severity": 0.91,
"depth": 3
}
],
"edges": [
{
"source": {
"resource_type": "rack",
"display_code": "RACK-DC2-R14"
},
"target": {
"resource_type": "service_instance",
"display_code": "SVC-PAY-GW-01"
},
"edge_type": "HOSTS",
"provider": "dcim",
"label": "Rack hosts service - U18-U22, 2.8 kW draw"
},
{
"source": {
"resource_type": "rack",
"display_code": "RACK-DC2-R14"
},
"target": {
"resource_type": "power_circuit",
"display_code": "PWR-DC2-PDU-B-14-C3"
},
"edge_type": "POWERED_BY",
"provider": "power_management",
"label": "Primary feed from PDU-B-14 circuit C3 - 12.4 kW allocated"
},
{
"source": {
"resource_type": "service_instance",
"display_code": "SVC-PAY-GW-01"
},
"target": {
"resource_type": "network_path",
"display_code": "NET-PATH-R14-SPINE01"
},
"edge_type": "ROUTED_VIA",
"provider": "network_topology",
"label": "TOR uplink - VLAN 220 to spine fabric"
},
{
"source": {
"resource_type": "service_instance",
"display_code": "SVC-PAY-GW-01"
},
"target": {
"resource_type": "sla_commitment",
"display_code": "SLA-ACME-T1-2026"
},
"edge_type": "PROTECTED_BY",
"provider": "service_catalog",
"label": "Tier-1 SLA - 99.99% uptime, 5-min RTO"
}
],
"stats": {
"node_count": 47,
"edge_count": 83,
"provider_counts": {
"dcim": 18,
"power_management": 9,
"network_topology": 11,
"service_catalog": 6,
"cooling": 3
},
"truncated": false,
"collisions": {
"collision_count": 2,
"collision_severity": "HIGH"
}
}
}POST Analyze power circuit maintenance
Analyze impact of power circuit maintenance: redundancy losses, affected racks, capacity constraints.
POST /api/v1/change-controls/{id}/impact/runThe ChangeControl record (created separately) specifies scheduled maintenance on primary power circuit PWR-A-23, with failover to backup circuit PWR-B-23 during a 4-hour window. Impact analysis identifies racks losing N+1 redundancy and services at risk of single-point-of-failure.
Request
{
"detect_collisions": true
}Response
{
"schema_version": "vge.graph_result.v1",
"run_id": 934,
"nodes": [
{
"node_ref": {
"resource_type": "power_circuit",
"resource_id": 934010,
"display_name": "PWR-A-23 / Bus A - Primary Feed",
"display_code": "PWR-DC1-A-23",
"status": "Maintenance Scheduled",
"tags": [
"480V/60A",
"Bus-A",
"8 racks served"
]
},
"severity": 0.93,
"depth": 0
},
{
"node_ref": {
"resource_type": "rack",
"resource_id": 934011,
"display_name": "RACK-DC1-R23 - loses N+1 redundancy",
"display_code": "RACK-DC1-R23",
"status": "Active - 14.2 kW load",
"tags": [
"Pod-C",
"redundancy-loss",
"6 services hosted"
]
},
"severity": 0.87,
"depth": 1
}
],
"edges": [
{
"source": {
"resource_type": "power_circuit",
"display_code": "PWR-DC1-A-23"
},
"target": {
"resource_type": "rack",
"display_code": "RACK-DC1-R23"
},
"edge_type": "POWERS",
"provider": "power_management",
"label": "Primary feed - rack drops to single-path power during maintenance"
}
],
"stats": {
"node_count": 34,
"edge_count": 52,
"provider_counts": {
"power_management": 16,
"dcim": 10,
"service_catalog": 8
},
"truncated": false,
"collisions": {
"collision_count": 0,
"collision_severity": "NONE"
}
}
}POST Validate network topology changes
Validate network topology changes: redundant path preservation, bandwidth impacts, service tier coverage.
POST /api/v1/change-controls/{id}/impact/runThe ChangeControl record (created separately) describes a core switch firmware upgrade on SW-CORE-01, temporarily rerouting traffic for VLANs 100, 200, and 300 through alternate spine paths during the upgrade window.
Request
{
"detect_collisions": true
}Response
{
"schema_version": "vge.graph_result.v1",
"run_id": 934,
"nodes": [
{
"node_ref": {
"resource_type": "network_device",
"resource_id": 934020,
"display_name": "SW-CORE-01 / Spine Fabric",
"display_code": "SW-CORE-01",
"status": "Firmware Upgrade Scheduled",
"tags": [
"spine-layer",
"BGP",
"3 VLANs affected"
]
},
"severity": 0.9,
"depth": 0
},
{
"node_ref": {
"resource_type": "service_instance",
"resource_id": 934021,
"display_name": "prod-api-cluster / VLAN 200",
"display_code": "SVC-API-CLUSTER-02",
"status": "Active - SLA Tier 1",
"tags": [
"Tier-1",
"dual-path",
"drops-to-single-path"
]
},
"severity": 0.86,
"depth": 2
}
],
"edges": [
{
"source": {
"resource_type": "network_device",
"display_code": "SW-CORE-01"
},
"target": {
"resource_type": "service_instance",
"display_code": "SVC-API-CLUSTER-02"
},
"edge_type": "ROUTED_VIA",
"provider": "network_topology",
"label": "VLAN 200 primary path - drops to single uplink during upgrade"
}
],
"stats": {
"node_count": 29,
"edge_count": 41,
"provider_counts": {
"network_topology": 18,
"service_catalog": 7,
"dcim": 4
},
"truncated": false,
"collisions": {
"collision_count": 0,
"collision_severity": "NONE"
}
}
}POST Model service migration impact
Model service migration impact: capacity headroom, cable plant changes, network path validation.
POST /api/v1/change-controls/{id}/impact/runThe ChangeControl record (created separately) describes migrating the production authentication service from RACK-DC1-R12 to RACK-DC2-R08, requiring cross-datacenter cable plant changes, new power circuit provisioning on PDU-A-08, and VLAN re-assignment for the target rack.
Request
{
"detect_collisions": true
}Response
{
"schema_version": "vge.graph_result.v1",
"run_id": 934,
"nodes": [
{
"node_ref": {
"resource_type": "service_instance",
"resource_id": 934030,
"display_name": "prod-auth-svc / RACK-DC1-R12-U06",
"display_code": "SVC-PROD-AUTH",
"status": "Active - migration pending",
"tags": [
"Tier-1",
"cross-DC",
"auth-critical"
]
},
"severity": 0.94,
"depth": 0
},
{
"node_ref": {
"resource_type": "cooling_loop",
"resource_id": 934031,
"display_name": "CL-03 / Target Rack Zone - 82% utilized",
"display_code": "CL-DC2-03",
"status": "Near Capacity",
"tags": [
"Zone-B",
"CRAC-04",
"threshold-warning"
]
},
"severity": 0.79,
"depth": 2
}
],
"edges": [
{
"source": {
"resource_type": "service_instance",
"display_code": "SVC-PROD-AUTH"
},
"target": {
"resource_type": "cooling_loop",
"display_code": "CL-DC2-03"
},
"edge_type": "COOLED_BY",
"provider": "cooling",
"label": "Target rack cooling loop at 82% - adding 1.6 kW heat load"
}
],
"stats": {
"node_count": 22,
"edge_count": 36,
"provider_counts": {
"dcim": 8,
"network_topology": 6,
"power_management": 4,
"cooling": 3,
"service_catalog": 1
},
"truncated": false,
"collisions": {
"collision_count": 0,
"collision_severity": "NONE"
}
}
}GET Detect maintenance window conflicts
Detect scheduling conflicts across overlapping change requests for shared infrastructure.
GET /api/v1/change-controls/{id}/impact/collisionsResponse
{
"collision_count": 2,
"colliding_change_ids": [
928,
931
],
"collision_severity": "HIGH",
"top_overlapping_nodes": [
{
"node_key": "rack:dc2r14:head",
"severity": 0.91,
"change_ids": [
934,
928
],
"display": "RACK-DC2-R14 - overlaps with CHG-928 (PDU-B-14 firmware upgrade scheduled same window)"
},
{
"node_key": "service_instance:paygw01:head",
"severity": 0.88,
"change_ids": [
934,
931
],
"display": "SVC-PAY-GW-01 - overlaps with CHG-931 (network path failover test targeting same service tier)"
}
]
}GET Verify SLA protection during changes
Verify SLA-protected services maintain redundancy and tier requirements during infrastructure changes.
GET /api/v1/change-controls/{id}/impactResponse
{
"run_id": 934,
"sla_violations": [
{
"service_code": "SVC-PAY-GW-01",
"sla_tier": "Tier-1",
"customer": "Acme Corp",
"sla_code": "SLA-ACME-T1-2026",
"required_redundancy": 2,
"post_change_redundancy": 1,
"violation": "Power path redundancy drops from N+1 to N during rack decommission. Single PDU feed on migration target RACK-DC2-R31",
"severity": 0.93
},
{
"service_code": "SVC-CACHE-CLUSTER-03",
"sla_tier": "Tier-2",
"customer": "Globex Industries",
"sla_code": "SLA-GLOBEX-T2-2026",
"required_redundancy": 2,
"post_change_redundancy": 1,
"violation": "Network path drops to single uplink when TOR-DC2-R14 is decommissioned. No redundant spine path on VLAN 220",
"severity": 0.85
}
],
"services_checked": 14,
"services_compliant": 12,
"services_violated": 2
}POST Estimate infrastructure change cost
Estimate NRE costs for rack migrations (decommission labor, cable plant rerouting, power provisioning, network reconfiguration, cooling rebalance, and service migration coordination) with min/likely/max uncertainty bounds and schedule impact.
POST /api/v1/change-controls/{id}/cost-estimateResponse
{
"estimate_id": 1547,
"impact_analysis_run_id": 934,
"line_items": [
{
"cost_driver_type": "nre",
"description": "Physical decommission of RACK-DC2-R14: disconnect 6 power whips, 12 fiber runs, 4 copper patches, remove 9 service hosts",
"quantity": 1,
"unit_rate": 18500,
"cost_phase": "nre",
"min_cost": 14000,
"likely_cost": 18500,
"max_cost": 24000,
"confidence": 0.85
},
{
"cost_driver_type": "nre",
"description": "Fiber and copper rerouting to RACK-DC2-R31: 12 fiber paths through patch panel PP-DC2-07, 4 copper runs to TOR-DC2-R31",
"quantity": 16,
"unit_rate": 1200,
"cost_phase": "nre",
"min_cost": 15000,
"likely_cost": 19200,
"max_cost": 25600,
"confidence": 0.8
},
{
"cost_driver_type": "nre",
"description": "New PDU circuits on RACK-DC2-R31: provision 2 redundant feeds from PDU-A-31 and PDU-B-31, install 4 branch circuits",
"quantity": 4,
"unit_rate": 3800,
"cost_phase": "nre",
"min_cost": 12000,
"likely_cost": 15200,
"max_cost": 19000,
"confidence": 0.82
},
{
"cost_driver_type": "nre",
"description": "TOR switch migration and VLAN re-assignment: move 3 VLANs (220, 310, 415) to TOR-DC2-R31, update BGP peering",
"quantity": 3,
"unit_rate": 4500,
"cost_phase": "nre",
"min_cost": 10000,
"likely_cost": 13500,
"max_cost": 18000,
"confidence": 0.78
},
{
"cost_driver_type": "nre",
"description": "Cooling loop CL-07 rebalancing: adjust CRAC-03 airflow for reduced heat load in Zone A, verify CL-09 capacity at RACK-DC2-R31",
"quantity": 2,
"unit_rate": 5200,
"cost_phase": "nre",
"min_cost": 8000,
"likely_cost": 10400,
"max_cost": 14000,
"confidence": 0.75
},
{
"cost_driver_type": "nre",
"description": "Live migration coordination for 9 services: change window scheduling, rollback plans, SLA notification for 3 Tier-1 customers",
"quantity": 9,
"unit_rate": 1700,
"cost_phase": "nre",
"min_cost": 12000,
"likely_cost": 15300,
"max_cost": 20000,
"confidence": 0.83
}
],
"nre_range": {
"min": 71000,
"likely": 92100,
"max": 120600
},
"recurring_range": {
"min": 280,
"likely": 340,
"max": 420,
"currency": "USD",
"description": "Monthly recurring cost increase from higher power density and cooling at target rack location"
},
"schedule_impact": {
"min_schedule_days": 8,
"likely_schedule_days": 12,
"max_schedule_days": 18,
"critical_path_nodes": [
"power_circuit:pdu_b_31:head",
"service_instance:paygw01:head"
]
},
"confidence": 0.8,
"confidence_notes": "Estimate calibrated from your operational data. PDU provisioning lead time and Tier-1 SLA change window availability are the primary uncertainty drivers.",
"justification_summary": "Rack decommission of RACK-DC2-R14 drives $92K NRE (physical decommission, cable plant rerouting to RACK-DC2-R31, power circuit provisioning on PDU-A/B-31, network reconfiguration across 3 VLANs, cooling rebalance for 2 loops, and live migration of 9 services including 3 SLA-protected). Power provisioning and Tier-1 change window coordination form the critical path at 12 days."
}Preview endpoints reflect the planned VGE surface. Final routes may adjust as the engine deploys to production.
FAQ
Common questions about Impact Intelligence for data centers + infrastructure.
How does Impact Intelligence handle service tier SLAs?
EquatorOps imports service tier metadata (tier-1 production, tier-2 staging, tier-3 dev) and SLA commitments from your CMDB or service catalog. Impact analysis automatically flags changes affecting SLA-protected tiers and validates that redundancy requirements (e.g., N+1 power, dual network paths) are maintained. Change managers see tier breakdowns in the impact preview UI and can block approval if SLA protections are violated.
Can Impact Intelligence detect maintenance window conflicts?
Yes. When multiple change requests target the same racks, power circuits, or network devices, EquatorOps detects scheduling overlaps and resource contention. The conflict detection engine checks capacity constraints (e.g., only 2 racks can be offline simultaneously in a pod), redundancy requirements (e.g., both circuits can't be down at once), and sequential dependencies (e.g., cooling must be upgraded before adding high-density racks). Change managers see a consolidated view of conflicts and can reschedule or stagger overlapping requests.
How does capacity planning work in the impact preview?
EquatorOps models power budget (watts per rack, circuit breaker limits), cooling capacity (BTU/hr per zone, CRAC unit headroom), and network bandwidth (port utilization, uplink capacity) for every rack and zone. When you preview a service migration or rack decommission, the capacity analysis shows current utilization, post-change utilization, and headroom against thresholds. Engineers see warnings like 'Target rack will reach 82% power budget, exceeds 80% threshold' before starting migrations, allowing them to select alternate racks or provision additional capacity.
How do you verify redundancy during network topology changes?
EquatorOps maintains a network path graph linking services to switches, routers, and uplinks. When you propose a topology change (e.g., decommissioning a core switch), impact analysis walks the graph to identify which services lose redundant paths. The preview UI highlights services dropping from dual-path to single-path and flags SLA violations (e.g., tier-1 services must maintain dual paths). Network engineers can validate proposed routing changes in the graph before deploying to production.
Can Impact Intelligence track cable plant dependencies?
Yes. EquatorOps models fiber, copper, and power cable connections between racks, patch panels, network devices, and power distribution units. When you preview a rack decommission or migration, cable plant impact analysis identifies which cables need disconnection, rerouting, or replacement. The visual map shows cable paths color-coded by type (fiber, copper, power) and flags cables shared across multiple services. This prevents accidental disconnections and helps plan cable installation work in advance of migrations.
How do you handle cross-data-center dependencies?
EquatorOps supports multi-site infrastructure graphs where services span multiple data centers (e.g., active-active replication, geographic redundancy). Impact analysis traverses dependencies across sites, identifying which remote services are affected by local changes. For example, if you decommission a rack in DC1 that hosts a replication target for DC2 services, the impact preview flags the cross-site dependency and warns about potential replication failures. This ensures disaster recovery and geo-redundant architectures remain intact during infrastructure changes.
What integrations are required for data center impact analysis?
EquatorOps integrates with DCIM tools (Sunbird, Nlyte, Device42) for rack and power circuit data, IPAM/network management (NetBox, Infoblox, Cisco DNA Center) for network topology, monitoring systems (Datadog, Prometheus, Nagios) for real-time service health, and ticketing systems (ServiceNow, Jira) for change request workflows. We provide REST APIs, webhook listeners, and pre-built connectors for common platforms. Initial graph coverage typically comes online in weeks, expanding iteratively as additional data sources are connected.
How fast is impact analysis for large data centers?
Impact analysis completes in seconds for typical infrastructure graphs (racks, services, circuits, network devices). For very large environments, graph partitioning and incremental analysis keep response times interactive. Engineers see impact previews in real-time as they draft change requests, enabling 'what-if' planning without waiting for batch processing.
How does Impact Intelligence support MOP and backout plan verification?
Verification packs generated by Impact Intelligence include the dependency context needed to validate Methods of Procedure (MOPs) and backout plans. For each change, the pack identifies which services, power paths, and network links are affected, what redundancy state exists during the maintenance window, and which rollback dependencies must hold for a clean backout. Change managers and CAB reviewers can verify MOP completeness against the actual dependency graph instead of relying on manual checklists.
Does Impact Intelligence integrate with change calendar and CAB workflows?
Yes. EquatorOps integrates with ticketing systems (ServiceNow, Jira) to pull change requests, maintenance windows, and change freeze periods into the dependency graph. Impact analysis respects change calendar constraints, flagging conflicts with freeze windows, CAB cutoff dates, and existing approved changes. Change managers see a consolidated view of all scheduled changes, their overlapping blast radii, and any policy violations before the CAB review.