Predictive and Intelligent Spares Management (PRISM)

From Signals to Spare Parts 

PRISM ingests signals from a variety of sources—component and server-health telemetry from disks, memory and Graphics Processing Units (GPUs) to broader platform signals—and uses an ensemble of machine learning models to generate actionable predictions: what part is likely to fail, where it will be needed, and when. 

Those predictions seamlessly integrate with forecasting and planning systems so spare parts can be mobilized to the right datacenter before they are needed. 

A Hack with a Supply-Chain Heartbeat 

PRISM caught momentum at the Microsoft Global Hackathon 2024, where a cross-functional team in Cloud Supply Chain asked a bold question:
“What if we could forecast failures and spare parts like weather?” 

That challenge galvanized engineers, data scientists, and operations leaders to prototype fast, iterate faster, and pursue sponsorship. 

“Think big, start small, and scale it,” says Vaibhav Gupta. “Once you bring even a small start with a vision, others join—and momentum does the rest.” 

This is classic Garage: coaching, scrappy iteration, shared momentum. The team refined their story in late-night pitch reps, partnered with several teams across Microsoft Azure to wire up the right data, and amplify impact. 

“Before every major presentation,” recalls Jaideep Seevaraj, “the leader is trying to learn your project. That positivity changed how we showed up.” Or as teammate Manikanta Piratla put it: “The Garage is basically our startup incubator.” 

Credibility That Compounds 

Their recognition grew beyond the Hackathon. A joint research paper with Azure Failure Prediction & Detection (AFPD)—won Best Paper at the IEEE Cloud Summit, validating the technical foundation of the work. Inside Microsoft, PRISM earned multiple Pinnacle Innovators’ Arena honors, amplifying awareness and unlocking new conversations across engineering and operations.  

These well-earned recognitions reflect PRISM’s cross-functional traction and strategic relevance.

Lakshmi Misra, Director, The Garage-Noida emphasized, “Through Garage coaching, I witnessed PRISM’s remarkable agility—absorbing input, iterating swiftly, and consistently exceeding expectations. Their journey from Hackathon to production revealed a team rich in insight, resilience, and brilliance.”

Predictions That Move Inventory 

As part of an early pilot, PRISM’s predictive technology was deployed at a datacenter.  It first showcased it’s potential when it analyzed operational data and forecasted when and where a critical part would be needed. Acting on this prediction, the team proactively transferred a spare component from another datacenter. 

Shortly after the part arrived, the predicted failure occurred. Because of PRISM’s foresight, technicians were able to immediately restore the affected server, avoiding downtime and ensuring continued service. Over the two-month pilot, PRISM’s predictions helped prevent more than 60 potential outages, demonstrating the tangible value of predictive maintenance in keeping cloud infrastructure reliable.

Every Second Counts: The Five Nines Standard 

Azure’s commitment to reliability is measured by the industry’s “five nines” standard (99.999% reliability), meaning services can be unavailable for no more than five minutes and fifteen point six seconds per year. This level of uptime is essential for customers running life-critical workloads, from emergency response systems and healthcare to global sporting events and financial services. Even a brief outage can have far-reaching consequences, making predictive solutions like PRISM vital for maintaining trust and uninterrupted service.  

Outcomes You Can Count 

Now, PRISM is live and integrated. It augments traditional failure-rate based models with live telemetry in the planning loop—preventing stockouts and keeping the fleet healthy. Coverage is expanding, with early phases reaching about twenty three percent of scope and plans to expand with partner teams. Behind the scenes, the Synapse-based data engine processes hundreds of gigabytes of telemetry daily, generating thousands of predictions each month through an ensemble of advanced models. 

“We were amazed by the structure—how the framework showed where we could take PRISM. It kept us from wandering and focused us on outcomes,” says Vaibhav Gupta. 

Scale 

The path forward is clear. PRISM continues to expand its reach by tapping into broader, cleaner telemetry across storage and network domains. Deeper integration with partner teams will help convert more predictions into just-in-time part availability, reinforcing the forecast-plan-fulfil loop so customers never feel the break. 

The vision is bold: to extend this model across the entire Azure fleet, encompassing every server & network component. PRISM is transforming cloud supply chain and fleet management—shifting from reactive to proactive, and ultimately, to predictive.