In this article, Kevin Kline introduces The High-Performance DBA webcast series, drawing on insights from our recent State of Database Report to explain why DBA burnout is rising and how teams can move beyond constant reactivity.
Read The High-Performance DBA Series
Over the past 15 years, Agile and DevOps have accelerated application delivery, enabling faster, more reliable releases. Yet the database layer often remains a blind spot for observability and performance monitoring.
In this article, Kevin Kline shows why closing the database observability gap is critical to improving performance, efficiency, and resilience for DBAs, developers, and the businesses that depend on their data.
Federal AI readiness is becoming more urgent as federal and defense agencies adopt AI faster than they can update the systems, policies, and oversight practices around it.
Many organizations that adopt enterprise service management don’t set out to build one. It starts as an IT service desk, and only later does someone in HR or Facilities ask why their department doesn’t have anything like it. That question is usually the clearest sign the platform is ready to expand.
We are excited to announce our latest updates for SolarWinds Service Desk.
In this release, we’re giving teams more flexibility in how they configure integrations, connect Service Desk to Microsoft Teams, and tailor index views to the work that matters most. It also adds clearer controls and visibility across the asset checkout lifecycle, from availability and overdue tracking to checkout history and notifications.
SAP HANA performance comes from deliberate architectural choices. It keeps active data in memory, relies heavily on columnar storage, and supports transactional and analytical workloads on the same platform.
Understanding those choices helps explain why SAP HANA can be fast, why sizing and query design matter, and why architecture-aware monitoring is important in production.
“We’re at an inflection point in IT service management. AI adoption is no longer the hard part – the hard part is building the organizational discipline to make AI deliver. The teams that get this right aren’t just running a faster service desk; they’re running a fundamentally different operation. At SolarWinds, our job is to make that transition as straightforward as possible – giving customers the platform, the data foundation and the governance they need to move from AI activity to real AI payoff.”
-Brad McGinity, GM of ITSM, SolarWinds
“AI is not a set-it-and-forget-it capability. It needs ownership, current knowledge, reliable data, and human judgment in the places where it matters most. Service desks that plan for that work are in a better position to get lasting value from AI.”
—Jasmine Park, Staff PMM, ITSM, SolarWinds
In this blog, Owen Murphy explores how to investigate application slowdowns by connecting distributed traces to database queries. When an application slows down, the first alert is only the beginning of the investigation. The real challenge is determining whether the delay comes from the application, infrastructure, network, or database—and finding the evidence to prove it.
Distributed tracing can show where a request spends its time, while database observability reveals what is happening inside the query itself. Together, they help teams connect application latency to database behavior and move from a vague performance symptom to a focused root-cause investigation.
