Partner Perspective: Application Rationalization Combined with a Move Towards Zero Trust Will Improve Chances of Network Stability

All the fancy apps in the world won’t do users a bit of good if the network is down. And, in fact, sometimes having a bunch of fancy apps from different vendors introduces the type of complexity that makes it more likely the network will, in fact, go down. So it’s no surprise that a huge trend among CIOs today is application rationalization. It’s one of a number of initiatives that look to drive towards simplicity in the IT ecosystem and, in the process, give CIOs and CISOs a better chance of keeping the lights on.

















When a health system’s EHR goes dark or telehealth connections drop mid-consult, patient care

is at risk. Rob Johnson, VP and Global Head of Solutions Engineering at SolarWinds, described

how the complexity of healthcare IT environments demands a shift toward observability,

simplification, and preemptive remediation.

Navigating Chaos with Clarity

Health system CIOs, Johnson noted, often face three persistent problems: too many tools, limited

resources, and widespread data silos. These pressures have intensified with the rise of digital

front doors, remote care delivery, and cloud-based services. “System availability is absolutely

critical,” he said. “The uninterrupted functioning of IT systems underpins nearly every aspect of

healthcare delivery.”





Visibility across the full IT stack—from infrastructure to applications—can support performance and reliability, Johnson said. He pointed to the interconnected nature of systems such as patient portals, billing platforms, and EHRs, and emphasized the potential ripple effects of instability.

Common sources of disruption include misconfigured firewalls, outdated firmware, and inconsistent change management. Johnson suggested that even small actions—like plugging in unauthorized devices or omitting documentation—can contribute to larger systemic risks.

Fragmented incident response protocols and the lack of standardized processes may exacerbate these challenges. Johnson pointed to health systems with non-uniform documentation practices as being particularly vulnerable to escalated issues.

Technical issues also present hurdles. Legacy infrastructure, siloed tools, and bandwidth limitations can complicate operations. “We’ve seen organizations running dozens of monitoring tools that don’t talk to each other,” Johnson said, calling attention to the challenges that fragmented systems introduce.

Cybersecurity threats such as phishing and ransomware further compound the risks. Technical debt and uneven integration, particularly in organizations that have grown through acquisition, also make troubleshooting and scalability difficult. Unauthorized changes, inconsistent firmware patching, and a lack of disaster recovery planning all contribute to system instability.

Johnson described additional risks that are often overlooked, including improper hardware handling and the physical placement of equipment. “Something as simple as a wall can disrupt connectivity if Wi-Fi signals aren’t properly accounted for,” he said. Similarly, non-technical incidents such as accidental data deletion or improper segmentation of IT environments can have cascading consequences.

A Case for Observability and Automation

To address these challenges, Johnson pointed to observability tools that incorporate AI and machine learning. He described how performance monitoring systems can identify anomalies and reduce false positives through pattern recognition. For instance, a spike in EHR latency might be linked to a backup process rather than an actual outage—an insight that AI tools can

help confirm.

Johnson argued that machine learning can support IT teams by filtering noise and offering context-aware alerts. This approach,