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New Cisco Firepower 2100 Series Prevents Bottlenecks

Cisco takes on security bottlenecks, with the introduction of the Cisco Firepower 2100 Series Next-Generation Firewall (NGFW).

The 2100 series is designed for businesses that perform high volumes of sensitive transactions, such as banking and retail, and supports their need to maintain uptime and protect critical business functions and data. The series aims to end the industry tug of war between performance and protection – with incorporation of a new scalable architecture and improvements of up to 200 percent greater throughput to eliminate bottlenecks – from the Internet edge to the data cent

The new Cisco Firepower 2100 Series provides businesses with the confidence to pursue new digitization opportunities, knowing they have a security architecture designed to protect against the greatest threats, without affecting the performance of critical business functions.

As an architecture with dual multicore CPU complexes that accelerate key cryptographic, firewall, and threat defense functions, the 2100s are purpose-built to meet customers’ ongoing protection and performance needs without compromise. The Cisco Firepower 2100 Series delivers up to 200 percent greater throughput than similarly priced offerings, even when threat inspection is turned on.

The new Cisco Firepower 2100 Series NGFW is a family of four threat-focused NGFW security platforms (2110, 2120, 2130, and 2140) that deliver throughput ranges from 1.9-8.5 Gbps, for enterprise use cases from the Internet edge to the data center. Each delivers Cisco’s renowned reliability for network uptime, and twice the port density with 10 GbE connectivity in a compact 1RU design.

Cisco has enhanced local, centralized, and cloud-based management tools that allow customers to streamline operations and more cost-efficiently address unique enterprise user requirements.

- Firepower Device Manager: Features an on-box web-based interface to deploy Cisco Firepower NGFW devices in minutes, with the use of a guided set-up wizard.

- Firepower Management Center (FMC): Enables simple and comprehensive security administration of multiple appliances. New FMC appliances offer a 50 percent increase in management scalability over previous models. Further simplifying and improving protection, the FMC enables users to automate security tasks, including assessment, tuning, correlation, containment and remediation. With the Cisco Threat Intelligence Director (TID), using industry standards FMC can now also automatically take in and correlate third-party and customer-specific threat intelligence providing additional defense via security sensors on your network.

- Cloud Defense Orchestrator: Delivers simple, cloud-based policy management. This tool allows teams to streamline and scale security policy management, designing and deploying policy uniformly across an organization. CDO now offers support for Web Security Appliance v.11 and is now available via a European cloud.

David Ulevitch, VP and GM, Security Business Group, Cisco said: “The Cisco Next-Generation Firewalls have been proven to be the most effective on the market, but we also know that businesses everywhere are struggling with a number of factors, including lack of talent and expanding attack surfaces, which can impact the effectiveness of even the best solutions. The New Cisco Firepower 2100 Series addresses these challenges, making it easier for enterprises to manage their architecture and ensure that they have the best performance at all times.”

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 ...

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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.

New Cisco Firepower 2100 Series Prevents Bottlenecks

Cisco takes on security bottlenecks, with the introduction of the Cisco Firepower 2100 Series Next-Generation Firewall (NGFW).

The 2100 series is designed for businesses that perform high volumes of sensitive transactions, such as banking and retail, and supports their need to maintain uptime and protect critical business functions and data. The series aims to end the industry tug of war between performance and protection – with incorporation of a new scalable architecture and improvements of up to 200 percent greater throughput to eliminate bottlenecks – from the Internet edge to the data cent

The new Cisco Firepower 2100 Series provides businesses with the confidence to pursue new digitization opportunities, knowing they have a security architecture designed to protect against the greatest threats, without affecting the performance of critical business functions.

As an architecture with dual multicore CPU complexes that accelerate key cryptographic, firewall, and threat defense functions, the 2100s are purpose-built to meet customers’ ongoing protection and performance needs without compromise. The Cisco Firepower 2100 Series delivers up to 200 percent greater throughput than similarly priced offerings, even when threat inspection is turned on.

The new Cisco Firepower 2100 Series NGFW is a family of four threat-focused NGFW security platforms (2110, 2120, 2130, and 2140) that deliver throughput ranges from 1.9-8.5 Gbps, for enterprise use cases from the Internet edge to the data center. Each delivers Cisco’s renowned reliability for network uptime, and twice the port density with 10 GbE connectivity in a compact 1RU design.

Cisco has enhanced local, centralized, and cloud-based management tools that allow customers to streamline operations and more cost-efficiently address unique enterprise user requirements.

- Firepower Device Manager: Features an on-box web-based interface to deploy Cisco Firepower NGFW devices in minutes, with the use of a guided set-up wizard.

- Firepower Management Center (FMC): Enables simple and comprehensive security administration of multiple appliances. New FMC appliances offer a 50 percent increase in management scalability over previous models. Further simplifying and improving protection, the FMC enables users to automate security tasks, including assessment, tuning, correlation, containment and remediation. With the Cisco Threat Intelligence Director (TID), using industry standards FMC can now also automatically take in and correlate third-party and customer-specific threat intelligence providing additional defense via security sensors on your network.

- Cloud Defense Orchestrator: Delivers simple, cloud-based policy management. This tool allows teams to streamline and scale security policy management, designing and deploying policy uniformly across an organization. CDO now offers support for Web Security Appliance v.11 and is now available via a European cloud.

David Ulevitch, VP and GM, Security Business Group, Cisco said: “The Cisco Next-Generation Firewalls have been proven to be the most effective on the market, but we also know that businesses everywhere are struggling with a number of factors, including lack of talent and expanding attack surfaces, which can impact the effectiveness of even the best solutions. The New Cisco Firepower 2100 Series addresses these challenges, making it easier for enterprises to manage their architecture and ensure that they have the best performance at all times.”

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.