Providence Builds Custom Network Telemetry to Deliver Enterprise-Grade Reliability

To ensure consistent and high-quality digital service delivery across a massive health system, Providence has designed and implemented a proprietary telemetry monitoring platform that captures, interprets, and responds to network and application issues in real time. The result: a data-driven approach to diagnosing impairments, improving uptime, and supporting clinicians in delivering uninterrupted care.

“We started with the network because, frankly, nothing works if the network is down or if users can’t log in,” said Kellie Larkin, VP, Identity, Networking & Data Engineering, Providence. “Our objective was to create a level of situational awareness that went beyond traditional monitoring—to give our team and our clinical colleagues a real-time understanding of application impact when something isn’t performing as expected.”

Engineering a Smarter Network

The initiative began with a shift away from a costly MPLS infrastructure toward a software-defined wide area network (SD-WAN) design optimized for performance, cost efficiency, and observability. Providence selected a mix of regional carriers and private fiber links, creating a redundant mesh that ensured minimal latency across diverse geographies. That new foundation allowed the system to introduce granular, dynamic routing between sites and cloud-based assets.

The team incorporated both public and private pathways into the architecture, with encrypted traffic flowing through the most performant route at any given moment. As a result, latency was reduced by up to 60% in some areas, improving performance for clinicians and back-office users alike.



But to truly capitalize on the new infrastructure, Providence needed better visibility. The organization invested heavily in telemetry to capture live signals from the environment and align them with operational expectations. “We didn’t want to just know that something failed,” said Larkin. “We wanted to understand how that failure translated to the clinical experience.”

That meant designing a telemetry system that could correlate physical network data—packet loss, jitter, latency—with application responsiveness and the subjective experience of the user.

Quantifying Impairment and Prioritizing Resolution

The team developed a user experience algorithm, informed by years of ServiceNow ticket history, incident response patterns, and application metadata. The result was a real-time scoring system that classifies performance as good, impaired, or non-functional. These scores were then mapped to clinical impact levels.

By treating “impairment” as a continuum rather than a binary event, Providence was able to characterize issues with far more nuance. A brief slowdown in image rendering for a radiologist, for example, could be prioritized over an administrative portal loading slowly, depending on the clinical context.

“Our radiologists talk about milliseconds or brain cells, milliseconds or heart cells, when it’s an emergency,” Larkin noted. “If an image doesn’t arrive quickly, it can impact care. So we set performance standards in collaboration with clinical leadership—and we built telemetry around those benchmarks.”

The system can now verify whether a specific imaging transaction met the agreed-upon service level by analyzing timing, route, and destination. If it didn’t, engineers can investigate root causes with precision. In one instance, the system identified that a radiologist’s local workstation was underpowered for rendering high-resolution studies. Although the network had delivered the data properly, the end device created the bottleneck. The user was then reprovisioned with higher-performance equipment.

This kind of post-event analysis, enabled by a vast repository of time-stamped telemetry data, allows Providence to continuously refine service delivery and close feedback loops with clinical departments.