Skip to main content

Sysdig Advisor Released

Sysdig announced the availability of Sysdig Advisor, a Kubernetes troubleshooting feature that consolidates and prioritizes relevant performance details in Sysdig Monitor.

By providing a single view of performance and event information, Sysdig Advisor enables operations, developers, and site reliability engineering (SRE) teams to troubleshoot issues faster while decreasing the number of tools needed.

With a click of a button, Sysdig Advisor presents all relevant capacity, event, alerts, and troubleshooting information. Since this information is presented in the context of Kubernetes objects, users can quickly drill down when looking for the source of a performance problem. Sysdig Advisor displays a prioritized list of issues and related live logs to surface the biggest problem areas and accelerate time to resolution.

Key Benefits of Sysdig Advisor:

- Accelerates troubleshooting by up to 10x: Sysdig Advisor produces a prioritized list of issues, giving administrators visibility into what problems to address first. When compared to traditional methodologies, teams can resolve Kubernetes issues by up to 10x faster with Sysdig Advisor by reducing the time it takes to find critical information, including capacity, utilization, event, and alert data for clusters, namespaces, workloads, and pods.

- Reduces troubleshooting resource count: Sysdig Advisor reduces the dependence on a side-by-side comparison of blogs, dashboards, logs, and command line output needed to troubleshoot Kubernetes environments. The simple user interface surfaces all the important details in a single unified tool with a curated, actionable set of steps for remediation.

- Increases troubleshooting access without increasing security risk: Security teams are often concerned about providing broad access to command-line tools, such as kubectl. Sysdig Advisor provides quick access to the same level of information to users across the organization, without being overly permissive.

“Kubernetes is complex, with countless components and variables that make it difficult to understand how, why, and when something goes wrong. Any SRE knows the pain of wading through multiple tools and getting multiple teams involved when troubleshooting an alert,” said Loris Degioanni, founder and CTO at Sysdig. “Now with Sysdig Advisor, they can efficiently debug issues and get back to work on deploying new releases.”

Sysdig is driving the standard for unified cloud and container security so DevOps and security teams can confidently secure containers, Kubernetes, and cloud services. Sysdig offers two products, Sysdig Secure and Sysdig Monitor, and the Sysdig platform architecture underpins both products. Sysdig Monitor provides cloud and Kubernetes monitoring that is fully open source Prometheus compatible. With Sysdig Secure, teams find and prioritize software vulnerabilities, detect and respond to threats, and manage cloud configurations, permissions, and compliance. Sysdig provides a single view of risk from source to run, with no blind spots, no guesswork, no black boxes.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

Sysdig Advisor Released

Sysdig announced the availability of Sysdig Advisor, a Kubernetes troubleshooting feature that consolidates and prioritizes relevant performance details in Sysdig Monitor.

By providing a single view of performance and event information, Sysdig Advisor enables operations, developers, and site reliability engineering (SRE) teams to troubleshoot issues faster while decreasing the number of tools needed.

With a click of a button, Sysdig Advisor presents all relevant capacity, event, alerts, and troubleshooting information. Since this information is presented in the context of Kubernetes objects, users can quickly drill down when looking for the source of a performance problem. Sysdig Advisor displays a prioritized list of issues and related live logs to surface the biggest problem areas and accelerate time to resolution.

Key Benefits of Sysdig Advisor:

- Accelerates troubleshooting by up to 10x: Sysdig Advisor produces a prioritized list of issues, giving administrators visibility into what problems to address first. When compared to traditional methodologies, teams can resolve Kubernetes issues by up to 10x faster with Sysdig Advisor by reducing the time it takes to find critical information, including capacity, utilization, event, and alert data for clusters, namespaces, workloads, and pods.

- Reduces troubleshooting resource count: Sysdig Advisor reduces the dependence on a side-by-side comparison of blogs, dashboards, logs, and command line output needed to troubleshoot Kubernetes environments. The simple user interface surfaces all the important details in a single unified tool with a curated, actionable set of steps for remediation.

- Increases troubleshooting access without increasing security risk: Security teams are often concerned about providing broad access to command-line tools, such as kubectl. Sysdig Advisor provides quick access to the same level of information to users across the organization, without being overly permissive.

“Kubernetes is complex, with countless components and variables that make it difficult to understand how, why, and when something goes wrong. Any SRE knows the pain of wading through multiple tools and getting multiple teams involved when troubleshooting an alert,” said Loris Degioanni, founder and CTO at Sysdig. “Now with Sysdig Advisor, they can efficiently debug issues and get back to work on deploying new releases.”

Sysdig is driving the standard for unified cloud and container security so DevOps and security teams can confidently secure containers, Kubernetes, and cloud services. Sysdig offers two products, Sysdig Secure and Sysdig Monitor, and the Sysdig platform architecture underpins both products. Sysdig Monitor provides cloud and Kubernetes monitoring that is fully open source Prometheus compatible. With Sysdig Secure, teams find and prioritize software vulnerabilities, detect and respond to threats, and manage cloud configurations, permissions, and compliance. Sysdig provides a single view of risk from source to run, with no blind spots, no guesswork, no black boxes.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.