How a global hospitality enterprise unified infrastructure operations across 7,000+ properties
A global hospitality organization implemented Selector to consolidate operational visibility across property networks, datacenter infrastructure, SD-WAN environments, and enterprise operational systems such as Wifi, DNS, ISP, and NAC, enabling faster issue detection, AI-assisted troubleshooting, and scalable operational governance across one of the industry’s largest distributed environments.
At a glance
Global hospitality enterprise
Hospitality
Hybrid enterprise deployment across property, WAN network — including SD-WAN, datacenter, and cloud environments
- Unify visibility across 7,000+ global properties
- Reduce MTTD and MTTR across network operations
- Consolidate telemetry from disparate infrastructure and operational tools
- Modernize legacy monitoring and reporting workflows
- Improve inventory governance and operational reporting
- Enable AI-assisted operations and natural language interaction
- Event correlation and AI-driven RCA
- Natural language ChatOps
- Topology mapping and infrastructure relationships
- NetFlow driven traffic insights
- WAN and SD-WAN monitoring
- Environmental telemetry monitoring
- Inventory discovery and enrichment
- SLA and maintenance-aware reporting
- DNS monitoring and alerting
- WiFi monitoring and alerting
- LoadBalancer health monitoring and alerting
- Firewall health monitoring and alerting
- Demand and capacity forecasting and alerting
- ISP health monitoring
- NAC monitoring to find disconnected devices to improve security posture
- Application reachability insights based on Selector Pingmesh as well as ThousandEyes integration
- A one stop shop for all monitoring and correlating signals from vastly different sources
- Faster incident investigation and operational triage
- Improved visibility across global property operations
- Reduced alert fatigue and troubleshooting overhead
- More accurate operational reporting and SLA visibility
- Scalable foundation for proactive infrastructure operations
- Stronger inventory governance and operational consistency
Challenge
Operational telemetry was fragmented across property networks, data centers, monitoring platforms, and operational teams, making it difficult to correlate incidents, maintain inventory accuracy, and troubleshoot issues efficiently at global scale.
Solution
Selector created a centralized operational intelligence layer that unified telemetry, reporting, topology visibility, AI-assisted correlation, and natural language workflows across thousands of distributed properties and enterprise systems.
Impact
The organization improved visibility across more than 24,000 devices, accelerated operational workflows, reduced manual troubleshooting effort, and established a scalable foundation for proactive infrastructure operations and AI-assisted network management.
Building a shared operational view across a global hospitality network
The organization operated one of the largest distributed hospitality infrastructure environments in the world, spanning thousands of hotel properties, enterprise locations, data center environments, WAN services, and cloud-connected operational systems. Supporting this environment required coordination across multiple infrastructure and operations teams responsible for maintaining connectivity, guest services, property systems, and enterprise operations around the clock.
As the environment expanded, operational workflows became increasingly fragmented across separate monitoring platforms, infrastructure teams, and operational silos. Property telemetry, SD-WAN visibility, inventory records, network alerts, environmental health metrics, and operational reporting existed in disconnected systems with limited contextual alignment between them. Teams often had to pivot across dashboards and manually correlate information to understand service impact or isolate root causes.
The organization wanted to modernize its operational model by improving visibility across property and enterprise infrastructure while reducing the operational burden associated with manual troubleshooting and legacy monitoring workflows. Selector was implemented to unify telemetry, automate correlation, improve reporting accuracy, and create a scalable operational intelligence layer spanning more than 7,000 properties and over 24,000 monitored devices.
Key challenges
Fragmented infrastructure visibility
Property networks, data centers, SD-WAN environments, and operational tooling existed across disconnected monitoring domains with limited shared context.
Manual troubleshooting workflows
Operations teams frequently relied on manual investigation across multiple dashboards to determine root cause and operational impact.
Legacy monitoring limitations
Existing monitoring approaches lacked the automation, topology awareness, and contextual intelligence needed for large-scale distributed operations.
Inventory governance gaps
Device metadata, inventory relationships, and operational tagging required significant normalization and governance improvements.
High operational scale
The environment required consistent monitoring and reporting across thousands of geographically distributed locations and multiple infrastructure domains.
Reactive operational workflows
Teams needed faster anomaly detection, correlation analytics, and more proactive operational insight to reduce incident response time.
Operational complexity was growing faster than existing workflows
When operational issues occurred, teams often had to manually assemble telemetry from separate monitoring platforms, property systems, SD-WAN environments, and infrastructure dashboards to determine what was actually happening. A single issue could generate multiple downstream alerts across WAN services, routing infrastructure, ISP connectivity, or property devices, forcing engineers to pivot across systems before they could isolate probable cause.
The organization also lacked a scalable way to correlate infrastructure conditions across its global property footprint. Network telemetry, environmental health metrics, inventory data, NetFlow analytics, routing information, and operational reporting existed in separate operational domains with inconsistent metadata and varying operational workflows. This made it difficult to understand broader operational patterns or assess regional impact quickly.
At the same time, the environment itself continued to evolve. Teams were expanding cloud-connected infrastructure, modernizing reporting workflows, integrating additional operational systems, and improving governance around inventory and operational metadata. Existing monitoring models could not easily support the scale, flexibility, or operational intelligence required for the next phase of infrastructure operations.
The organization needed a centralized operational model capable of combining telemetry, inventory context, reporting, and AI-assisted analysis into a more cohesive operational workflow without disrupting existing systems or requiring a large-scale rip-and-replace initiative.
Creating a unified operational intelligence layer across properties and enterprise infrastructure
Selector was deployed as a centralized operational intelligence platform spanning property networks, data center environments, SD-WAN infrastructure, environmental telemetry systems, and enterprise operational tooling. The deployment integrated telemetry from SNMP polling, NetFlow, PingMesh, SD-WAN platforms, DNS infrastructure, syslog pipelines, routing telemetry, collaboration workflows, and operational inventory systems.
The implementation provided unified dashboards and topology-aware operational workflows capable of correlating infrastructure conditions across thousands of distributed locations. Teams could move from high-level regional visibility into property-level drilldowns showing device health, routing conditions, WAN performance, environmental telemetry, and operational anomalies within a shared operational context.
Selector also introduced AI-assisted workflows for anomaly detection, alert trend analysis, BGP monitoring, hazard condition analysis, and event correlation. Natural language operational queries through ChatOps integrations enabled engineers to interact with infrastructure data conversationally through Slack-based workflows and operational dashboards.
Beyond live operational visibility, the deployment also modernized inventory governance and reporting workflows. Automated discovery, metadata normalization, maintenance-aware reporting, topology mapping, and infrastructure enrichment helped improve reporting accuracy while reducing manual operational overhead.
What Selector enabled
AI-assisted event correlation
Correlated alerts, telemetry, and infrastructure conditions into higher-fidelity operational incidents.
Natural language operations
Enabled conversational operational queries and ChatOps workflows through Slack integrations.
Topology-aware visibility
Provided LLDP-based infrastructure mapping across property and cloud-connected environments.
Environmental telemetry monitoring
Integrated temperature, fan, power, CPU, and memory health monitoring across multi-vendor infrastructure.
Maintenance-aware reporting
Improved SLA and availability reporting accuracy by accounting for scheduled maintenance windows.
Inventory enrichment and governance
Normalized infrastructure metadata and improved operational inventory consistency across thousands of devices.
Improving operational scale without replacing additional systems
One of the most important aspects of this deployment was the ability to improve operational workflows without forcing teams to abandon existing infrastructure investments. Selector integrated with current monitoring platforms, telemetry pipelines, operational dashboards, and collaboration systems while creating a centralized operational layer above them.
This mattered because the organization’s operational challenges were not caused by a lack of telemetry. The challenge was the difficulty of turning large volumes of fragmented operational data into usable operational understanding at global scale. By correlating telemetry, enriching operational context, and improving visibility across infrastructure domains, teams could work from clearer operational signals instead of manually stitching information together.
The deployment also established a scalable foundation for future operational maturity. Because the platform supported hybrid infrastructure, cloud-connected services, distributed telemetry collection, and AI-assisted workflows, the organization could continue expanding observability coverage and operational automation without redesigning its operational model from scratch.
Supporting faster and more proactive global infrastructure operations
The deployment gave the organization a more unified operational model across property infrastructure, datacenter operations, WAN environments, and enterprise operational systems. Teams could investigate incidents faster because telemetry, inventory context, topology relationships, and operational analytics were available within a shared operational workflow.
Operational reporting also improved significantly. Maintenance-aware reporting, inventory normalization, dynamic dashboards, and enhanced drilldowns provided more accurate visibility into infrastructure health and service conditions across the global environment. Teams gained stronger operational consistency while reducing repetitive manual effort associated with inventory correction, reporting, and cross-tool investigation.
Just as importantly, the work established a foundation for more proactive operational workflows. AI-assisted anomaly detection, hazard analysis, environmental telemetry monitoring, routing analytics, and natural language operational interaction positioned the organization to continue modernizing infrastructure operations as operational scale and complexity continue to grow.
Results snapshot
Properties Monitored
7,000+ global properties
Devices Monitored
24,000+ infrastructure devices
Operational Coverage
Property, datacenter, WAN, SD-WAN, and cloud-connected infrastructure, DNS, ISP, WiFi, NAC, Firewalls, and LoadBalancers.
Reporting Improvements
Maintenance-aware SLA and availability reporting
AI-Assisted Operations
Event correlation, anomaly detection, hazard analysis, and NLQ workflows, capacity utilization forecasting
Expanding toward more predictive and autonomous operations
With a centralized operational intelligence foundation in place, the organization is continuing to expand observability coverage across additional infrastructure domains, cloud-connected systems, and operational workflows. Ongoing initiatives include enhanced NetFlow analytics, hybrid cloud monitoring, topology-aware operational mapping, and deeper infrastructure correlation capabilities.
The operational model also creates a path toward more predictive infrastructure operations over time. Expanded AI-assisted workflows, routing intelligence, proactive alerting, and broader automation initiatives position the organization to improve resilience, operational efficiency, and service reliability across one of the world’s largest hospitality infrastructure environments.
