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ScienceLogic Raises the Bar for Hybrid Cloud Monitoring and Management

ScienceLogic announced enhanced and extended support for hybrid cloud monitoring and management in the latest release of its award-winning ScienceLogic Smart IT platform.

Highlighted in this release are significant updates to the ScienceLogic Power-Packs that provide smart monitoring policies that are highly automated for Amazon Web Services (AWS) and VMware vCloud Director.

To support today’s dynamic infrastructure with “compute anywhere” requirements, ScienceLogic service management views seamlessly show service levels, health, availability, and risk regardless of where individual service delivery resources (e.g., storage, database, web servers, etc.) reside – in the data center or in the cloud.

Designed to support multi-tenant operations for service providers or enterprises, ScienceLogic Smart IT software provides an ultra-flexible and unified monitoring and management platform for hybrid cloud and converged compute environments.

Hundreds of ScienceLogic Power-Packs work out-of-the-box to collect data from any computing source and present actionable information in context that drive Smart IT policies.

New in ScienceLogic v7.3

- Advanced Monitoring of AWS provides the most comprehensive set of performance, availability, and billing information in easy-to-analyze dashboard views, across multiple Amazon accounts, services, and regions.

- Advanced Monitoring of VMware vCloud Director automatically applies service level monitoring for VMware cloud assets across public, private, and hybrid cloud environments, making ScienceLogic the only product on the market to support fully multi-tenant operations for VMware cloud assets.

- Dynamic Component Mapping provides automated relational mapping and continuous, intelligent updates to status of individual systems that make up highly dynamic, complex infrastructures, such as Cisco UCS, VCE Vblock, and virtual environments using vMotion.

- ScienceLogic’s single RESTful API provides access to all performance, fault, configuration and analytics data.

“We believe that every IT organization will run hybrid operations – whether that means multiple vendors and service providers or a mix of data center, public, private, and hybrid cloud assets,” said Jeremy Sherwood, ScienceLogic Cloud Strategist. “To support this vision, ScienceLogic software has always been vendor-agnostic, and we continue to follow our mission to simplify what is becoming an increasingly complex and dynamic operational environment, with centralized, automated policy-based management. The new release takes this commitment to the next level to ensure seamless management in hybrid and converged compute environments, enabling IT to move at the speed of business today.”

Related Links:

www.sciencelogic.com

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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 ...

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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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

ScienceLogic Raises the Bar for Hybrid Cloud Monitoring and Management

ScienceLogic announced enhanced and extended support for hybrid cloud monitoring and management in the latest release of its award-winning ScienceLogic Smart IT platform.

Highlighted in this release are significant updates to the ScienceLogic Power-Packs that provide smart monitoring policies that are highly automated for Amazon Web Services (AWS) and VMware vCloud Director.

To support today’s dynamic infrastructure with “compute anywhere” requirements, ScienceLogic service management views seamlessly show service levels, health, availability, and risk regardless of where individual service delivery resources (e.g., storage, database, web servers, etc.) reside – in the data center or in the cloud.

Designed to support multi-tenant operations for service providers or enterprises, ScienceLogic Smart IT software provides an ultra-flexible and unified monitoring and management platform for hybrid cloud and converged compute environments.

Hundreds of ScienceLogic Power-Packs work out-of-the-box to collect data from any computing source and present actionable information in context that drive Smart IT policies.

New in ScienceLogic v7.3

- Advanced Monitoring of AWS provides the most comprehensive set of performance, availability, and billing information in easy-to-analyze dashboard views, across multiple Amazon accounts, services, and regions.

- Advanced Monitoring of VMware vCloud Director automatically applies service level monitoring for VMware cloud assets across public, private, and hybrid cloud environments, making ScienceLogic the only product on the market to support fully multi-tenant operations for VMware cloud assets.

- Dynamic Component Mapping provides automated relational mapping and continuous, intelligent updates to status of individual systems that make up highly dynamic, complex infrastructures, such as Cisco UCS, VCE Vblock, and virtual environments using vMotion.

- ScienceLogic’s single RESTful API provides access to all performance, fault, configuration and analytics data.

“We believe that every IT organization will run hybrid operations – whether that means multiple vendors and service providers or a mix of data center, public, private, and hybrid cloud assets,” said Jeremy Sherwood, ScienceLogic Cloud Strategist. “To support this vision, ScienceLogic software has always been vendor-agnostic, and we continue to follow our mission to simplify what is becoming an increasingly complex and dynamic operational environment, with centralized, automated policy-based management. The new release takes this commitment to the next level to ensure seamless management in hybrid and converged compute environments, enabling IT to move at the speed of business today.”

Related Links:

www.sciencelogic.com

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...