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ScienceLogic Skyler Offerings Available on AWS Marketplace

ScienceLogic announced that its newly reimagined Skylar™ offerings, anchored in the ScienceLogic AI Platform, including Skylar™ One and Skylar™ Automation  alongside Skylar™ AI and Skylar™ Compliance, are now available to purchase on the AWS Marketplace. 

This milestone enables organizations to easily and rapidly onboard ScienceLogic capabilities for intelligent automation, unified observability, compliance, and accelerated IT operations, delivering outcomes far beyond incident response and positioning customers for greater resilience and agility.

Through the AWS Marketplace, ScienceLogic can now provide a simplified procurement experience while also reducing vendor sprawl, accelerating AI adoption, and helping customers advance toward more resilient, automated operations with enhanced compliance. Customers can choose to deploy ScienceLogic offerings flexibly within their own AWS Virtual Private Cloud (VPC) for maximum control and compliance, or leverage ScienceLogic’s Regional Services Architecture (RSA) for a fully managed SaaS experience – delivering choice without compromise. By leveraging the AWS procurement process, organizations gain expert guidance, unified vendor management, and simplified budgeting with transparent, predictable pricing models—eliminating the uncertainty and cost overruns often associated with purely consumption-based pricing.

“Making the Skylar offerings available in the AWS Marketplace removes friction for customers and speeds adoption of intelligent IT operations,” said Michael Nappi, chief product officer at ScienceLogic. “Instead of piecemeal tools or point agents, ScienceLogic unifies observability, automation, compliance, and AI-driven remediation in one platform. The result is less downtime, reduced complexity, and faster progress toward self-healing, proactive operations at scale.”

The ScienceLogic AI Platform offerings and services available on the AWS Marketplace include:

  • Skylar One: (formerly SL1®) is the foundation of the ScienceLogic AI Platform, delivering unified, service-centric observability across hybrid and multi-vendor environments. It connects and synthesizes fragmented data silos, accelerates root cause analysis, and optimizes operations at scale. It Includes Skylar One Studio (formerly SL1 Studio) for out-of-the-box monitoring integrations via ScienceLogic PowerPacks and flexible, customizable observability.
  • Skylar Automation: (formally PowerFlow™) is the low-code orchestration engine that connects insights IT ecosystems – from ITSM, CMDBs to collaboration and cloud platforms – automating processes from detection to resolution and eliminating manual toil.
  • Skylar AI: (name retained) is the intelligence layer of the ScienceLogic AI Platform, powering correlation, prediction, and proactive remediation through Agentic AI. It includes Skylar Analytics for unsupervised prediction and detection, and Skylar Advisor for plain-language guidance and safe, executable actions to reduce MTTR.
  • Skylar Compliance: (formerly Restorepoint™) delivers centralized backup, recovery, and policy enforcement across multi-vendor infrastructures, ensuring resilience and minimizing downtime.

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ScienceLogic Skyler Offerings Available on AWS Marketplace

ScienceLogic announced that its newly reimagined Skylar™ offerings, anchored in the ScienceLogic AI Platform, including Skylar™ One and Skylar™ Automation  alongside Skylar™ AI and Skylar™ Compliance, are now available to purchase on the AWS Marketplace. 

This milestone enables organizations to easily and rapidly onboard ScienceLogic capabilities for intelligent automation, unified observability, compliance, and accelerated IT operations, delivering outcomes far beyond incident response and positioning customers for greater resilience and agility.

Through the AWS Marketplace, ScienceLogic can now provide a simplified procurement experience while also reducing vendor sprawl, accelerating AI adoption, and helping customers advance toward more resilient, automated operations with enhanced compliance. Customers can choose to deploy ScienceLogic offerings flexibly within their own AWS Virtual Private Cloud (VPC) for maximum control and compliance, or leverage ScienceLogic’s Regional Services Architecture (RSA) for a fully managed SaaS experience – delivering choice without compromise. By leveraging the AWS procurement process, organizations gain expert guidance, unified vendor management, and simplified budgeting with transparent, predictable pricing models—eliminating the uncertainty and cost overruns often associated with purely consumption-based pricing.

“Making the Skylar offerings available in the AWS Marketplace removes friction for customers and speeds adoption of intelligent IT operations,” said Michael Nappi, chief product officer at ScienceLogic. “Instead of piecemeal tools or point agents, ScienceLogic unifies observability, automation, compliance, and AI-driven remediation in one platform. The result is less downtime, reduced complexity, and faster progress toward self-healing, proactive operations at scale.”

The ScienceLogic AI Platform offerings and services available on the AWS Marketplace include:

  • Skylar One: (formerly SL1®) is the foundation of the ScienceLogic AI Platform, delivering unified, service-centric observability across hybrid and multi-vendor environments. It connects and synthesizes fragmented data silos, accelerates root cause analysis, and optimizes operations at scale. It Includes Skylar One Studio (formerly SL1 Studio) for out-of-the-box monitoring integrations via ScienceLogic PowerPacks and flexible, customizable observability.
  • Skylar Automation: (formally PowerFlow™) is the low-code orchestration engine that connects insights IT ecosystems – from ITSM, CMDBs to collaboration and cloud platforms – automating processes from detection to resolution and eliminating manual toil.
  • Skylar AI: (name retained) is the intelligence layer of the ScienceLogic AI Platform, powering correlation, prediction, and proactive remediation through Agentic AI. It includes Skylar Analytics for unsupervised prediction and detection, and Skylar Advisor for plain-language guidance and safe, executable actions to reduce MTTR.
  • Skylar Compliance: (formerly Restorepoint™) delivers centralized backup, recovery, and policy enforcement across multi-vendor infrastructures, ensuring resilience and minimizing downtime.

The Latest

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 ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...