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SolarWinds Adds New AI-Powered Observability Capabilities

SolarWinds announced enhancements to its SaaS-based and self-hosted, on-premises observability solutions built to monitor and observe complex, distributed environments from anywhere.

The AI-powered enhancements enable teams to manage on-prem, hybrid, or cloud-native ecosystems with full-stack visibility across networks, infrastructure, databases, applications, user experiences, and security through a unified, integrated solution available either on-premises or in the cloud.

These transformative updates to the SolarWinds solutions come as organizations face increased monitoring and issue resolution challenges associated with their digital transformation efforts—from cloud migration to SD-WAN networks, modern application frameworks, and persistently hybrid workforces. Recent Gartner® research has suggested that through 2027, 50% of critical applications will reside outside of centralized public clouds. With proven SolarWinds AI-powered observability solutions, organizations can gain full, unified visibility into the entire technology stack through both a self-hosted solution and a born-in-the-cloud SaaS offering.

SolarWinds enables enterprises to integrate on-prem and cloud ecosystems into one holistic view—so they can improve the user experience and increase performance through proactive issue detection and accelerated problem-solving.

“The rapidly evolving technology landscape and organizations’ ongoing modernization journeys drive the digital complexity they face. When operating in a hybrid, multi-cloud, containerized microservices world, there’s one thing we know for sure: this complexity isn’t magically going away,” said Cullen Childress, SolarWinds SVP, Product. “At the same time, uptime and service level requirements continue to become more stringent while budgets remain stagnant. For nearly 25 years, we’ve given IT pros the tools they need to do their jobs more easily and with greater satisfaction. That’s why our message today is clear: with SolarWinds, you can see everything from anywhere.”

The new capabilities in SolarWinds observability solutions include further enhancements to its proven broad and deep network and infrastructure Observability, offering complete hybrid visibility across on-premises and cloud networks. This includes on-premises and cloud network devices, virtual machines, hypervisors, containers, Kubernetes, and infrastructure-as-a-service resources. SolarWinds further extends its world-class database observability capabilities by adding query explorer and visual explain plans. Additionally, AIOps-enabled pattern recognition and anomaly detection provide insights into correlated alerts and events to accelerate root cause analysis, allowing IT teams to be more productive as the organization scales.

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SolarWinds Adds New AI-Powered Observability Capabilities

SolarWinds announced enhancements to its SaaS-based and self-hosted, on-premises observability solutions built to monitor and observe complex, distributed environments from anywhere.

The AI-powered enhancements enable teams to manage on-prem, hybrid, or cloud-native ecosystems with full-stack visibility across networks, infrastructure, databases, applications, user experiences, and security through a unified, integrated solution available either on-premises or in the cloud.

These transformative updates to the SolarWinds solutions come as organizations face increased monitoring and issue resolution challenges associated with their digital transformation efforts—from cloud migration to SD-WAN networks, modern application frameworks, and persistently hybrid workforces. Recent Gartner® research has suggested that through 2027, 50% of critical applications will reside outside of centralized public clouds. With proven SolarWinds AI-powered observability solutions, organizations can gain full, unified visibility into the entire technology stack through both a self-hosted solution and a born-in-the-cloud SaaS offering.

SolarWinds enables enterprises to integrate on-prem and cloud ecosystems into one holistic view—so they can improve the user experience and increase performance through proactive issue detection and accelerated problem-solving.

“The rapidly evolving technology landscape and organizations’ ongoing modernization journeys drive the digital complexity they face. When operating in a hybrid, multi-cloud, containerized microservices world, there’s one thing we know for sure: this complexity isn’t magically going away,” said Cullen Childress, SolarWinds SVP, Product. “At the same time, uptime and service level requirements continue to become more stringent while budgets remain stagnant. For nearly 25 years, we’ve given IT pros the tools they need to do their jobs more easily and with greater satisfaction. That’s why our message today is clear: with SolarWinds, you can see everything from anywhere.”

The new capabilities in SolarWinds observability solutions include further enhancements to its proven broad and deep network and infrastructure Observability, offering complete hybrid visibility across on-premises and cloud networks. This includes on-premises and cloud network devices, virtual machines, hypervisors, containers, Kubernetes, and infrastructure-as-a-service resources. SolarWinds further extends its world-class database observability capabilities by adding query explorer and visual explain plans. Additionally, AIOps-enabled pattern recognition and anomaly detection provide insights into correlated alerts and events to accelerate root cause analysis, allowing IT teams to be more productive as the organization scales.

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In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...