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FireScope Introduces FireScope Stratis

FireScope introduced FireScope Stratis, an elastic cloud-enabled enterprise management solution designed to support truly massive and highly dynamic environments.

FireScope Stratis is designed from the ground up to leverage cloud-era technologies such as Big Data, elastic scalability, multi-layered redundancy, multi-tenancy and more.

FireScope's approach delivers capabilities such as:

* Complete visibility, from user experiences to power and air and encompassing all of your virtual and non-virtual assets, from across the globe in a single interface with a Top-Down service-aligned approach.

* Elastic management platform, leveraging Infrastructure As A Service (‘IAAS”) and Big Data technology to scale on-demand automatically to support dynamic infrastructure growth and capable of supporting truly massive environments with hundreds of thousands of assets.

* Layered elastic redundancy and secure multi-tenancy out of the box.

* Insight into the business implications of events and performance in terms of lost revenue, productivity and regulatory risk and enabling you to analyze capacity in terms of forecasted business growth.

FireScope Stratis is comprised of three elastically scalable components; the Elastic Web Component, Elastic Application Component and Elastic Storage Component.

In addition to enabling customers to start using their first dashboards on day-one, this simplified architecture features a cloud management interface that continually evaluates the load and performance of each layer to automatically self-adjust resources to deliver optimal performance without over utilization.

A universal Edge device, configured from the cloud-based FireScope Stratis interface, performs localized discovery and data collection, and makes expansion of coverage for new business locations or growth as easy as starting the edge device and executing discovery and auto-configuration.

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FireScope Introduces FireScope Stratis

FireScope introduced FireScope Stratis, an elastic cloud-enabled enterprise management solution designed to support truly massive and highly dynamic environments.

FireScope Stratis is designed from the ground up to leverage cloud-era technologies such as Big Data, elastic scalability, multi-layered redundancy, multi-tenancy and more.

FireScope's approach delivers capabilities such as:

* Complete visibility, from user experiences to power and air and encompassing all of your virtual and non-virtual assets, from across the globe in a single interface with a Top-Down service-aligned approach.

* Elastic management platform, leveraging Infrastructure As A Service (‘IAAS”) and Big Data technology to scale on-demand automatically to support dynamic infrastructure growth and capable of supporting truly massive environments with hundreds of thousands of assets.

* Layered elastic redundancy and secure multi-tenancy out of the box.

* Insight into the business implications of events and performance in terms of lost revenue, productivity and regulatory risk and enabling you to analyze capacity in terms of forecasted business growth.

FireScope Stratis is comprised of three elastically scalable components; the Elastic Web Component, Elastic Application Component and Elastic Storage Component.

In addition to enabling customers to start using their first dashboards on day-one, this simplified architecture features a cloud management interface that continually evaluates the load and performance of each layer to automatically self-adjust resources to deliver optimal performance without over utilization.

A universal Edge device, configured from the cloud-based FireScope Stratis interface, performs localized discovery and data collection, and makes expansion of coverage for new business locations or growth as easy as starting the edge device and executing discovery and auto-configuration.

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In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...