Moving Beyond SolarWinds: A Guide to Modern Observability
LogicMonitor Sales Engineers David Wells and Wayne Tolliver walked through what it actually takes to migrate off SolarWinds, from the hidden costs, the deployment realities, and where AI-driven alerting changes the math.
Industry-leading observability experts provide strategic guidance on why and how modern IT teams are successfully moving beyond SolarWinds to more resilient, cloud-native platforms.
The move from SolarWinds to a modern observability platform isn’t a multi-year project. Experts David Wells and Wayne Tolliver shared how teams are accelerating migration, cutting down on noise, and achieving genuine unified visibility.
The hidden cost of legacy is engineering time. Legacy monitoring tools demand constant care and feeding (managing VMs, patching OS, and maintaining infrastructure)– time that could be spent on innovation. Modern SaaS-based observability eliminates this overhead, allowing teams to get back to what’s important.
Cloud-native is not the same as cloud-hosted. A platform “born SaaS” handles the ephemeral, elastic nature of modern cloud workloads automatically. Tools simply “lifted and shifted” from an on-premises architecture struggle to track resources that spin up and down, requiring manual intervention for visibility.
Migration time is weeks, not years. With automated device discovery and professional services support, deployment can be achieved rapidly.
AI is the key to turning data into actionable insight. Every monitoring tool collects data, but AI-driven correlation cuts alert noise by 80% or more, freeing teams from alert fatigue and accelerating incident response. into Slack, Teams, or ServiceNow, is one of the more effective ways to drive actual platform adoption.
IT teams running SolarWinds often know the pain points well before they start evaluating alternatives: separate modules for different monitoring needs, a self-hosted deployment model that requires ongoing maintenance, and pricing that gets harder to predict after each acquisition. What’s less obvious is how much engineering time gets absorbed just keeping the tooling functional.
David Wells and Wayne Tolliver, observability experts on the Sales Engineering team at LogicMonitor covered the practical side of moving to a SaaS-based observability platform—what the migration actually looks like, where teams typically get stuck, and how to drive adoption once the new platform is in place.
What Experts Discussed
The real cost of legacy monitoring
The conversation focused on costs that don’t show up in the licensing invoice. Beyond software fees, teams running on-premises monitoring tools carry the overhead of managing virtual machines, applying OS updates, and provisioning infrastructure. Wells pointed out that this burden often leaves organizations running outdated, unpatched software. Not because they don’t want to upgrade, but because they don’t have the bandwidth to do it safely.
What unified observability actually means in practice
One of the clearest points was that modern environments (spanning on-premises data centers, hybrid clouds, and edge devices) need a single system for metrics, events, logs, and traces. With over 3,000 out-of-the-box integrations covering everything from traditional servers to SD-WAN and cloud-managed access points, the goal is to give NOC staff enough visibility to troubleshoot without immediately escalating to senior engineers.
Getting adoption right from the start
A recurring theme was that new monitoring platforms fail when they’re too complex for the people who need to use them. Wells and Tolliver walked through how role-based access control, showing each team how to focus on just the specific dashboards relevant to their work. That, combined with direct integrations into tools like Slack and ServiceNow, keeps alerts from getting buried and encourages teams to actually engage with the platform.
How fast migration can realistically move
Wells and Tolliver pushed back on the assumption that migrating off a legacy system takes a year or more. With automated discovery and professional services support, the timeline compresses significantly. A major global airline example (10,000 devices onboarded in eight weeks) was the clearest illustration of what’s possible when the preparation is done upfront.
Notable Insights
“Cloud-native” is a meaningful distinction. When evaluating SaaS observability platforms, it matters whether the software was built for the cloud or retrofitted from an on-premises architecture. True cloud-native platforms track ephemeral resources that expand and contract automatically. Lifted-and-shifted tools typically require manual intervention to keep up.
SaaS doesn’t mean giving up security controls. Moving away from on-premises infrastructure raises legitimate concerns about data control. Modern platforms address this through certifications like FedRAMP Moderate, TLS 1.3 encryption in transit, and unique key encryption at rest—standards that meet the requirements of regulated industries like healthcare and finance.Data volume isn’t the problem. As Wells put it: “Every monitoring tool collects a lot of data, but what you do with the data is what’s important.” The value of AI-driven correlation isn’t that it collects more. It’s that it surfaces what actually needs attention.
Watch the On-Demand Webinar
See how teams are moving beyond SolarWinds with an AI-first observability platform made for today and tomorrow.
Why IT Teams Are Switching from SolarWinds to LogicMonitor — Explores why IT teams are moving away from SolarWinds in favor of LogicMonitor, citing simpler deployment, stronger scalability, unified visibility, and AI-driven capabilities that help reduce alert noise and speed up troubleshooting.
LogicMonitor vs. SolarWinds — Compares LogicMonitor and SolarWinds across deployment, maintenance, visibility, and platform experience, showing how LogicMonitor’s SaaS model, AI-powered insights, and more predictable pricing help teams reduce tool sprawl and resolve issues faster.
How to Reduce MTTR with AI — Covers how AI helps ops teams detect issues earlier and pinpoint root causes faster, directly relevant to the alert correlation discussion in this session.
The Benefits of Network Monitoring — Explains how proactive network visibility helps teams catch abnormal patterns before they escalate, a useful companion to the case for unified observability.
Hybrid Cloud Clarity Powered by AI — LogicMonitor and AWS walk through unified visibility across on-premises and cloud environments, with AI-driven alert prioritization.
Sofia leads content strategy and production at the intersection of complex tech and real people. With 10+ years of experience across observability, AI, digital operations, and intelligent infrastructure, she's all about turning dense topics into content that's clear, useful, and actually fun to read. She's proudly known as AI's hype woman with a healthy dose of skepticism and a sharp eye for what's real, what's useful, and what's just noise.
Disclaimer: The views expressed on this blog are those of the author and do not necessarily reflect the views of LogicMonitor or its affiliates.
