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SolarWinds Integrates with Amazon Bedrock

SolarWinds announced expanded collaboration with Amazon Web Services (AWS) through new integrations with Amazon Bedrock, a fully managed service that offers access to high-performing foundation models from leading AI companies through a single API.

This relationship enhances AI innovation at SolarWinds on two fronts: first, using Amazon Bedrock powers generative AI capabilities within the SolarWinds® Platform and SolarWinds Service Desk, and second, enabling SolarWinds Observability to monitor Amazon Bedrock services directly, providing visibility into one of the world’s most advanced AI infrastructures.

SolarWinds leverages the Anthropic family of Claude models through Amazon Bedrock, delivering conversational, context-aware capabilities across its platform, including automated ticket summarization, incident correlation, and intelligent recommendations within SolarWinds Service Desk.

These new experiences are orchestrated through the SolarWinds LLM Gateway, a unified platform service built on AI by Design principles, which provides secure model abstraction across various models.

“Amazon Bedrock gives us a secure, scalable foundation to extend SolarWinds AI across our entire portfolio,” said Krishna Sai, CTO, SolarWinds. “It enables our teams to innovate faster and deliver real-time intelligence and downstream value to customers, while ensuring their data remains private, protected, and under their control.”

In parallel, SolarWinds Observability SaaS now monitors customer workloads on Amazon Bedrock as first-class monitored resources. IT teams can visualize Amazon Bedrock performance—including invocation rates, latency, token throughput, throttling, and overall health—through customizable dashboards and automated alerts powered by the SolarWinds Platform. This capability demonstrates how SolarWinds Observability SaaS can deliver end-to-end insight into even the most sophisticated AI workloads.

“With unified observability, organizations have confidence their AI systems perform reliably, securely, and at scale, accelerating their journey toward autonomous operational resilience,” said Cullen Childress, CPO, SolarWinds.

The SolarWinds AI Agent, announced earlier this fall, is built on Amazon Bedrock and serves as a digital teammate, summarizing incidents, identifying probable root causes, recommending fixes, and automating multi-step workflows through natural language interaction. These capabilities are complemented by recently announced features, such as Root Cause Assist and enhanced dynamic threshold capabilities, which together help IT professionals reduce noise, resolve issues more quickly, and focus on innovation rather than reactive issue management.

By embedding Anthropic Claude 4 and Claude 4.5 models through Amazon Bedrock, SolarWinds is extending AI Agent’s intelligence and automation across its observability, database, and IT service management products. The result is a unified, scalable foundation built on the company’s AI by Design and Secure by Design frameworks, ensuring every innovation is built with transparency, safety, and customer trust at its core.

Many SolarWinds AI features, powered by Amazon Bedrock, are already available in SolarWinds Service Desk. Additional features, such as the SolarWinds AI Agent, improved Root Cause Assist, and Database Query Assist, will soon be rolled out across other products, including SolarWinds Observability SaaS. 

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

SolarWinds Integrates with Amazon Bedrock

SolarWinds announced expanded collaboration with Amazon Web Services (AWS) through new integrations with Amazon Bedrock, a fully managed service that offers access to high-performing foundation models from leading AI companies through a single API.

This relationship enhances AI innovation at SolarWinds on two fronts: first, using Amazon Bedrock powers generative AI capabilities within the SolarWinds® Platform and SolarWinds Service Desk, and second, enabling SolarWinds Observability to monitor Amazon Bedrock services directly, providing visibility into one of the world’s most advanced AI infrastructures.

SolarWinds leverages the Anthropic family of Claude models through Amazon Bedrock, delivering conversational, context-aware capabilities across its platform, including automated ticket summarization, incident correlation, and intelligent recommendations within SolarWinds Service Desk.

These new experiences are orchestrated through the SolarWinds LLM Gateway, a unified platform service built on AI by Design principles, which provides secure model abstraction across various models.

“Amazon Bedrock gives us a secure, scalable foundation to extend SolarWinds AI across our entire portfolio,” said Krishna Sai, CTO, SolarWinds. “It enables our teams to innovate faster and deliver real-time intelligence and downstream value to customers, while ensuring their data remains private, protected, and under their control.”

In parallel, SolarWinds Observability SaaS now monitors customer workloads on Amazon Bedrock as first-class monitored resources. IT teams can visualize Amazon Bedrock performance—including invocation rates, latency, token throughput, throttling, and overall health—through customizable dashboards and automated alerts powered by the SolarWinds Platform. This capability demonstrates how SolarWinds Observability SaaS can deliver end-to-end insight into even the most sophisticated AI workloads.

“With unified observability, organizations have confidence their AI systems perform reliably, securely, and at scale, accelerating their journey toward autonomous operational resilience,” said Cullen Childress, CPO, SolarWinds.

The SolarWinds AI Agent, announced earlier this fall, is built on Amazon Bedrock and serves as a digital teammate, summarizing incidents, identifying probable root causes, recommending fixes, and automating multi-step workflows through natural language interaction. These capabilities are complemented by recently announced features, such as Root Cause Assist and enhanced dynamic threshold capabilities, which together help IT professionals reduce noise, resolve issues more quickly, and focus on innovation rather than reactive issue management.

By embedding Anthropic Claude 4 and Claude 4.5 models through Amazon Bedrock, SolarWinds is extending AI Agent’s intelligence and automation across its observability, database, and IT service management products. The result is a unified, scalable foundation built on the company’s AI by Design and Secure by Design frameworks, ensuring every innovation is built with transparency, safety, and customer trust at its core.

Many SolarWinds AI features, powered by Amazon Bedrock, are already available in SolarWinds Service Desk. Additional features, such as the SolarWinds AI Agent, improved Root Cause Assist, and Database Query Assist, will soon be rolled out across other products, including SolarWinds Observability SaaS. 

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...