The Hidden Challenges in Modern Data Centers
AI workloads and surging rack densities are pushing data centers beyond the limits of traditional monitoring. Four critical obstacles stand out:
Operational Complexity
Cooling, power, and compute telemetry sit in silos, blocking a unified view and slowing response times.
Unpredictable Demand
Modern AI workloads drive volatile spikes that static monitoring and capacity planning cannot handle.
Blind Spots
Surging rack densities demand real-time thermal and power insight, yet legacy tools lack the fidelity to act before failures.
Limited Visibility
Legacy dashboards overwhelm with charts but offer no intelligence, slowing operators when every second counts.
Why Legacy Monitoring Breaks Under AI Load
Traditional monitoring was designed for predictable IT environments. The rise of AI-driven workloads has made data centers far more volatile, with surging densities and split-second orchestration demands. Legacy systems can’t transform siloed telemetry into decisions, leaving operators unable to meet the new standard for uptime, efficiency, and AI-readiness.
Demand for AI-ready data center capacity will rise at an average rate of 33 percent a year. Around 70 percent of total demand for data center capacity will be for data centers equipped to host advanced-AI workloads by 2030.
McKinsey & Company
The HiveMQ Advantage for AI-Ready Data Centers
HiveMQ provides the enterprise-grade platform that transforms siloed telemetry into real-time, decision-ready intelligence. Four core capabilities set HiveMQ apart:
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Enterprise Data Streaming
Legacy systems deliver poor-quality data that weaken billing accuracy, compliance, and SLAs. HiveMQ provides secure, high-fidelity MQTT and Sparkplug streaming, ensuring data is accurate, real time, and trusted for compliance and business-critical decisions.
Real-Time Intelligence
Dashboards stop at data and leave operators blind to fast-moving risks. HiveMQ structures telemetry into decision-ready intelligence, powering predictive analytics, workload orchestration, and faster operator action when reliability matters most.
Scalable and Resilient
Traditional systems collapse under growth, slowing site onboarding and straining capacity. HiveMQ’s distributed architecture with high availability supports rapid expansion, powers millions of connections, and delivers proven reliability at enterprise scale.
Future-Proof for AI
Most platforms stop at monitoring and cannot support advanced workloads. HiveMQ prepares data centers to deliver structured, context-rich telemetry that fuels analytics, predictive optimization, and emerging AI-driven services across modern infrastructure.
Proven Business Outcomes
↑ 25%
Operational Efficiency
↓ 30%
Unplanned Downtime
99.999%
Service Reliability
What Customers Achieve with HiveMQ
HiveMQ delivers measurable results for the world’s most demanding data centers. By unlocking real-time data intelligence, operators achieve higher efficiency, reliability, and AI-readiness.
Legacy silos waste resources. HiveMQ unifies data to optimize cooling, power, and workloads, reducing costs and improving overall performance.
Traditional monitoring reacts too late. HiveMQ provides predictive insights that minimize downtime and ensure continuity.
Poor visibility drives waste and inflates energy costs. HiveMQ delivers accurate telemetry on power and environmental systems, helping operators cut consumption, and lower costs.
Billing errors and SLA gaps erode confidence. HiveMQ delivers transparent insights that strengthen compliance, billing accuracy, and customer confidence.
Common Use Cases in Data Centers
HiveMQ addresses the most urgent challenges operators face today, from compliance and onboarding to preparing infrastructure for AI-driven workloads.
Accurate Billing and Compliance
Stream high-fidelity EPMS and BMS data in real time to guarantee transparent billing, SLA compliance, and ESG reporting. HiveMQ ensures operators can meet customer and regulatory commitments with confidence.
Faster Site Onboarding
Simplify and accelerate the activation of new data center capacity. HiveMQ’s reliable, scalable streaming platform reduces operational bottlenecks and enables faster deployment of customer services.
AI/ML-Ready Infrastructure
Prepare data centers for next-generation services by structuring telemetry with Sparkplug and real-time streaming. HiveMQ powers predictive optimization, advanced analytics, and seamless integration with AI/ML platforms.
HiveMQ Platform for AI-Ready Data Centers
AI workloads, rising rack densities, and strict SLA requirements demand real-time visibility across power, cooling, and workloads. HiveMQ unifies telemetry from EPMS, BMS, DCIM, and environmental sensors into a trusted data backbone that feeds IT and AI systems. This enables operators to cut energy costs, improve uptime, and deliver AI-ready infrastructure.
The Intelligence Backbone of the AI Data Center
HiveMQ powers the shift from siloed monitoring to AI-native operations. By unifying OT, IT, and cloud ecosystems, HiveMQ transforms raw telemetry into distributed intelligence that drives efficiency, uptime, compliance, and AI readiness at scale.
Unlock Legacy OT Systems
Connect cooling, power, and environmental infrastructure with OPC UA, Modbus, BACnet, and more. HiveMQ streams high-fidelity telemetry in real-time, providing operators with a trusted foundation for informed action.
Deliver Distributed Intelligence
HiveMQ turns raw signals into contextual, decision-ready streams. This intelligence enables predictive maintenance, workload optimization, and faster response across the data center.
Integrate with Enterprise Systems
HiveMQ connects with Kafka, Snowflake, Databricks, and cloud platforms. By providing structured, reliable data, HiveMQ ensures analytics and AI pipelines deliver outcomes operators can trust.
Get started with HiveMQ today
Choose between a fully-managed cloud or self-managed platform. Our experts can help you with your solution and demonstrate HiveMQ in action.
