Daniel Salinas, Chief Operating Officer, Lakeside Software
When a critical service fails, the first minutes are often the most expensive. Multiple teams scramble to collect information, users are contacted for details, logs are pulled from disparate systems, and everyone tries to prove the problem lies elsewhere. Valuable time is lost in this relay race while the business impact mounts. The absence of immediate, reliable root cause analysis (RCA) means resolution takes far longer than necessary, and the true cause may only be confirmed long after service is restored.
Fortunately, root cause analysis in enterprise IT is evolving rapidly from a slow, retrospective task into a proactive capability that can keep pace with live incidents. Where RCA once relied on ad hoc debugging and partial event correlation, it can now draw on predefined models, detailed dependency maps, and real-time data streams.
Packet captures and post mortems will always have a role, but in 2025, powerful tools exist to collect and correlate operational data as incidents unfold, giving engineers the ability to pinpoint and address the true cause far sooner. Today’s enterprise networks span on-premises, cloud, SaaS, and remote endpoints, creating thousands of potential failure points. Without correlated data across these layers, even experienced teams can spend hours chasing symptoms instead of causes.
Real-world incidents demonstrate the significant benefits of having high-quality endpoint data and specific service checks in place, resulting in faster outcomes. In July, Cloudflare’s public resolver 1.1.1.1 failed for just over an hour. Many organisations experienced widespread application failures that appeared to originate within their own networks. Time-aligned endpoint data showing DNS failures, together with health checks to alternative resolvers, would have revealed the actual cause within minutes and prevented wasted effort on internal escalation. Just days earlier, users found they could not log in to Microsoft 365 Outlook. Symptoms were indistinguishable from WAN failure. A correlated diagnostic view showing that other services were functioning normally while only Microsoft authentication failed would have pinpointed the service provider as the cause rather than the internal infrastructure.
This underlines why packet-only diagnostics are no longer enough. With modern encrypted transports and complex dependencies, visibility at the endpoint is essential. RCA depends on signals that remain observable, such as DNS resolution, TCP connectivity, SSL handshake success, application process behaviour, and local configuration changes. Aligning these on a single timeline enables engineers to replay incidents and pinpoint causes in minutes rather than hours. Additionally, today’s platforms can detect abnormal patterns and trigger fixes before issues escalate, reducing help desk tickets and keeping users productive without them ever experiencing an outage.
Lakeside’s own guidance on what an effective RCA solution should include points to three core capabilities. First is depth of telemetry, capturing real-time and historical endpoint data at high granularity, from CPU and memory usage to network throughput, DNS query behaviour, and application response times. Second is intelligent analysis, which utilises automation and AI to identify patterns across vast datasets and surface likely causes without relying on manual guesswork. Third is the ability to trigger investigative workflows or even predefined fixes when certain conditions are met, turning RCA from a purely investigative function into one that actively shortens recovery times.
These capabilities create a measurable return on investment. Independent validation found that an AI-driven endpoint observability platform delivered a 259% return over three years for a 30,000-user organisation, generating over £8 million in benefits. Much of this value came from faster resolution, fewer support tickets, and the prevention of repeat incidents.
Beyond the financials, robust RCA also repairs the human side of incident management. In many organisations, unresolved issues bounce between help desk, network, server, and application teams, wasting time and eroding trust. Objective, time-stamped evidence ends this cycle. When data shows that a slowdown was caused by a SaaS authentication fault rather than the WAN, the correct team can act immediately, and finger-pointing stops.
For network engineers, effective RCA not only resolves today’s issues but also upskills teams for tomorrow’s challenges. By working from complete, correlated evidence, engineers sharpen diagnostic skills, improve cross-team collaboration, and embed more efficient workflows into future operations.
Root cause analysis is a practical, forward-looking discipline that strengthens both network resilience and team effectiveness. Applied with the right tools, it works alongside detection and response to keep services reliable and users productive. By continuously capturing and correlating the right signals, network teams can resolve issues in minutes, reduce ticket volumes, and prevent repeat incidents. The result is faster recoveries, lower costs, and stronger collaboration. In 2025, RCA stands as a cornerstone of proactive, high-performing network operations that anticipate and prevent problems before they escalate.
