INFRAM24: Measuring your IT strategy and capabilities to drive adoption and improve outcomes

Measuring your IT strategy and capabilities to drive adoption and improve outcomes

The world of healthcare is constantly shifting, and technology is at the spearhead of this continuous transformation. As organizations grapple with the complexities of digital adoption, cybersecurity, and sustainable operations, HIMSS’ Infrastructure Adoption Model (INFRAM) has been updated to meet the need, and lead with data-driven insights and strategic guidance. Cisco enables healthcare leaders to use INFRAM not just as an evaluation tool, but to drive change, mitigate risks, and ensure that technology investments translate into improved care delivery and clinical outcomes.

What’s New with INFRAM

Recently, HIMSS has revised INFRAM to not just look at infrastructure capabilities but to also look at IT strategy, assess technology adoption by internal stakeholders, and measure the direct impacts of infrastructure investments on clinical outcomes and operations. It now allows organizations to understand if their infrastructure capabilities are in line with their overall goals.  This update provides a closer look at the effectiveness of technology investments and identifies opportunities for improvements.

New INFRAM Domains

The updated version of INFRAM addresses 5 crucial aspect of healthcare infrastructure:

1. Cybersecurity: Data breaches are occurring more frequently and can have a larger effect on patient care and hospital operations than ever before, INFRAM emphasizes establishing robust cybersecurity practices, leveraging AI (Artificial Intelligence) for quick recovery, and aligning organizational efforts to minimize future risks. This domain allows organizations to understand their current capabilities in everything from network identity all the way to endpoint security.
2. IT Management & Performance: Systematic performance support and change management are critical for adhering to service-level agreements. INFRAM assists in leveraging technology to mitigate incidents and maintain high service standards. This helps the hospital understand their current IT capabilities across transport, wireless, collaboration, and data center for everything from location services all the way to their cloud usage strategy.
3. Adoption: Ensuring that innovative technologies are not just installed but integrated and optimized for maximum efficiency is vital. INFRAM ensures that patients, clinicians, staff, IT, and leadership reap the full benefits of technological advancements.
4. Outcomes: Perhaps most importantly, INFRAM provides a framework that aligns IT investments with clinical, financial, and operational objectives, ensuring measurable contributions to organizational goals.
5. Sustainability: Healthcare organizations are not exempt from the global call for environmental responsibility. INFRAM aids in developing strategies to reduce greenhouse gas emissions and carbon footprints, aligning healthcare with green initiatives.

Benefits to Healthcare Leaders

Using INFRAM, healthcare leaders can:

• Measure Value: Adopt an evidence-based approach for investments, gain critical buy-in, and achieve recognition for outcomes.
• Analyze Gaps: Pinpoint and address friction points in infrastructure development for tailored, strategic investments.
• Cybersecurity Risk Planning & Mitigation: Implement a proactive, best-practice approach to cybersecurity and establish a clear plan of action in the event of breaches.
• Build Governance and Drive Adoption: Ensure technology governance that maximizes value and supports care teams in delivering optimal outcomes.
• Drive Alignment- INFRAM provides a structured approach to evaluate a hospital’s infrastructure and Cisco can help ensure it aligns with the organization’s goals. This allows for cohesion between the Executive, Clinical, Operation and IT teams.

INFRAM24

INFRAM is more than an assessment tool; it is a strategic ally for healthcare organizations aiming to harness the power of technology to improve patient care and operational efficiency. As healthcare continues to evolve, INFRAM offers a structured path to navigate the complexities of digital transformation with confidence and clarity.

Source: cisco.com

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Empowering Cybersecurity with AI: The Future of Cisco XDR

In 2007, there was a study from the University of Maryland proving that internet-connected systems were attacked every 39 seconds on average. Today, that number has grown more than 60%. Cisco sees 64 attempts to connect to ransomware infrastructure every second. The world is becoming digitized, and hybrid, which creates an environment that criminals target with increasing sophistication. It’s too much for human-scale, and so a hybrid world requires a hybrid approach that sits between humans and machines.

Envision an AI Assistant that serves as a reliable partner for incident responders, offering precise, real-time guidance on the subsequent steps to take, tailored to the specific state of the incident at hand and allowing SOC (Security Operations Center) teams to respond faster and do more with less. I am pleased to announce the launch of the AI Assistant in XDR as a part of our Breach Protection Suite.

In our RSAC 2023 announcement, we introduced a vision of our Cisco SOC Assistant, designed to expedite threat detection and response. Today, this vision is realized and available in private preview. It enhances our Breach Protection Suite which is powered by Cisco XDR’s capabilities. It significantly speeds up investigations and responses, enabling security teams to safeguard their environments more efficiently and cost-effectively.

Assist with Information Discovery

In 2024, the global shortfall of 3.5 million security professionals, as reported by ISC2, underscores the importance of retaining and recruiting skilled personnel to counter increasingly sophisticated cyber threats and safeguard enterprises. Moreover, the lack of appropriate tools often leads to ineffective cyber risk management and professional burnout, adversely affecting staff retention and the SOC’s capacity to thwart attacks.

The AI Assistant in XDR acts as a potent enhancer, empowering SOC teams to maximize their efficiency and effectively close the personnel and skill gap. When an incident occurs, the assistant will contextualize events across email, the web, endpoints, and the network to tell the SOC analyst exactly what happened and its impact on their environment. It presents a short description of the incident that quickly answers what, when and how an incident happened. It also provides a long description of the incident which explains the timeline of events that have happened in this active incident.

Figure 1: Short Description of Incident Details generated by the AI Assistant

Figure 2: Long Description of Incident Details and Events Timeline

Moreover, our AI Assistant utilizes XDR’s patented ability to prioritize critical incidents, reducing alert fatigue for the SOC team and enhancing their efficiency in handling active incidents.

Figure 3: Targeted Prioritization of Incidents by AI Assistant that Need Immediate Attention

Augment and Elevate SOC Teams with Best Practice Recommendations

Today’s SOCs often struggle with a fragmented technology stack, making it difficult to respond effectively to cyber threats. Alert fatigue is a major hurdle for modern SOC teams, hindering proactive threat hunting and leading to overlooked alerts and burnout. The Cisco AI Assistant comes to the rescue and jumpstarts the incident response process for a modern SOC team.

Our AI Assistant, powered by Cisco XDR the platform for Cisco’s Breach Protection Suite, synthesizes data from email, web, processes, endpoints, cloud, and network domains, offering precise action recommendations to effectively contain ongoing cyber-attacks. It works at machine scale to identify patterns and potential attacks that humans might miss because of alert fatigue, if a defender is only looking at one domain in isolation, or while trying to manually correlate data. The AI Assistant is context aware, meaning it tracks the state of the incident in real-time and generates tailored recommendations specific to that incident.

Figure 4: Tailored Recommendations for an Incident by the AI Assistant

Mean Time to Detection (MTTD) and Mean Time to Respond (MTTR) are two primary metrics that SOC teams want to optimize for. Cisco XDR with our AI Assistant enables security teams to reduce these metrics by jumpstarting investigations and incident response by providing tailored recommendations for that specific incident.

Enable Seamless Collaboration Across Security Teams

The Cisco AI Assistant, embedded within XDR, facilitates team collaboration using Webex, Teams, or Slack. This empowers security teams to swiftly assemble the right experts for an active incident, thereby speeding up the MTTR. The AI Assistant unifies the team by setting up WAR rooms, summarizing messages, and logging them in XDR for instant audit-readiness.

Figure 5: AI Assistant creates a Webex WAR Room and brings the right experts together for Incident Response

Automate Workflows to Neutralize Threats Across the Enterprise

Today’s SOCs often lack a cohesive technology stack to respond to cyber threats efficiently and consistently. As the IT environment grows beyond the on-premises data center to cloud, hybrid-cloud and multi-cloud country specific data centers, organizations accumulate point solutions to monitor and protect pieces of the environment. As a result, SOC analysts must do a lot of the heavy lifting required to detect and respond to an attack. This includes logging into different tools to execute workflows that contain an attack.

Our AI Assistant taps into advanced workflows and atomics with Cisco XDR’s 90+ integrations. Our AI assistant enables the execution of workflows at a single click, guided by the AI Assistant’s personalized recommendations that consider the incident’s playbook and current state in real-time.

Figure 6: Execution of Automated Workflows by the AI Assistant to Contain an Incident

Gone are the days when security teams had to juggle multiple isolated products and execute workflows in each to mitigate an attack. With Cisco Breach Protection Suite, billions of security events can be correlated and recommended actions can be generated and executed all in one place. This is the transformative power of the Cisco XDR combined with Cisco’s AI Assistant revolutionizing enterprise security.

Source: cisco.com

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Synergizing Advanced Identity Threat Detection & Response Solutions

In an ever-evolving digital landscape, cybersecurity has become the cornerstone of organizational success. With the proliferation of sophisticated cyber threats, businesses must adopt a multi-layered approach to ensure the integrity of their digital assets and safeguard their sensitive information. Two leading players in this space, Cisco’s Duo Security and Cisco Identity Intelligence, have emerged as champions in Identity Threat Detection & Response. In this blog post, we will explore how Cisco Identity Intelligence seamlessly complements Cisco’s Duo Security to provide a comprehensive and robust cybersecurity strategy.

The Power of Identity Threat Detection & Response

Identity Threat Detection & Response (ITDR) has become a vital aspect of modern cybersecurity. It focuses on identifying anomalies in user behavior, detecting potential unauthorized access, and responding to security incidents promptly. Cisco’s Duo Security has established itself as a prominent solution in this domain, offering a range of features such as multi-factor authentication (MFA) and access controls that protect against unauthorized access.

Cisco Identity Intelligence: Elevating Cybersecurity Preparedness

Cisco Identity Intelligence brings an additional layer of protection to the table with its advanced capabilities in anomaly detection and behavioral analytics. This innovative technology analyzes user behavior patterns, device interactions, and network activities to identify even the subtlest deviations from normal behavior. This is particularly crucial in today’s threat landscape, where attackers are becoming increasingly adept at mimicking legitimate user actions.

How Cisco Identity Intelligence Complements Cisco’s Duo Security

1. Enhanced Anomaly Detection: While Cisco’s Duo Security provides robust MFA and access controls, Cisco Identity Intelligence takes it a step further by analyzing user activities in real time. By establishing a baseline of normal behavior, Cisco Identity Intelligence can swiftly identify any unusual actions, potentially preventing unauthorized access even after initial authentication.

2. Behavioral Analytics: Cisco Identity Intelligence’s AI-driven behavioral analytics can identify complex attack patterns that may go unnoticed by traditional security measures. By correlating data across multiple dimensions, Cisco Identity Intelligence helps security teams detect identity-related threats that could lead to data breaches or system compromise.

3. Holistic Threat Response: When integrated with Cisco’s Duo Security, Cisco Identity Intelligence enables a comprehensive threat response strategy. The combined capabilities of these two solutions allow organizations to not only prevent unauthorized access but also respond proactively to emerging threats, minimizing potential damage.

4. Adaptive Security: Cisco Identity Intelligence’s adaptive security approach means that it continuously learns from new data and adjusts its understanding of what constitutes normal behavior. This adaptability ensures that evolving attack techniques are promptly recognized and mitigated.

5. Reduced False Positives: Cisco Identity Intelligence’s sophisticated engine minimizes false positives by understanding context and user intent. This helps security teams focus their efforts on genuine threats, reducing alert fatigue and streamlining incident response.

Conclusion

As the cyber threat landscape continues to evolve, the collaboration between leading cybersecurity solutions becomes imperative. Cisco’s Duo Security and Cisco Identity Intelligence collectively fortify an organization’s defense by combining multi-factor authentication, access controls, AI-driven anomaly detection, and behavioral analytics. This synergy creates a robust shield against identity-related threats and provides a holistic approach to cybersecurity.

Remember, in today’s digital age, a comprehensive cybersecurity strategy is not a luxury but a necessity. By embracing the combined power of Cisco’s Duo Security and Cisco Identity Intelligence, organizations can confidently navigate the complex realm of cyber threats and safeguard their digital assets with unwavering resolve.

Source: cisco.com

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Computing that’s purpose-built for a more energy-efficient, AI-driven future

Just as humans use patterns as mental shortcuts for solving complex problems, AI is about recognizing patterns to distill actionable insights. Now think about how this applies to the data center, where patterns have developed over decades. You have cycles where we use software to solve problems, then hardware innovations enable new software to focus on the next problem. The pendulum swings back and forth repeatedly, with each swing representing a disruptive technology that changes and redefines how we get work done with our developers and with data center infrastructure and operations teams.

AI is clearly the latest pendulum swing and disruptive technology that requires advancements in both hardware and software. GPUs are all the rage today due to the public debut of ChatGPT – but GPUs have been around for a long time. I was a GPU user back in the 1990s because these powerful chips enabled me to play 3D games that required fast processing to calculate things like where all those polygons should be in space, updating visuals fast with each frame.

In technical terms, GPUs can process many parallel floating-point operations faster than standard CPUs and in large part that is their superpower. It’s worth noting that many AI workloads can be optimized to run on a high-performance CPU.  But unlike the CPU, GPUs are free from the responsibility of making all the other subsystems within compute work with each other. Software developers and data scientists can leverage software like CUDA and its development tools to harness the power of GPUs and use all that parallel processing capability to solve some of the world’s most complex problems.

A new way to look at your AI needs

Unlike single, heterogenous infrastructure use cases like virtualization, there are multiple patterns within AI that come with different infrastructure needs in the data center. Organizations can think about AI use cases in terms of three main buckets:

1. Build the model, for large foundational training.

2. Optimize the model, for fine-tuning a pre-trained model with specific data sets.

3. Use the model, for inferencing insights from new data.

The least demanding workloads are optimize and use the model because most of the work can be done in a single box with multiple GPUs. The most intensive, disruptive, and expensive workload is build the model. In general, if you’re looking to train these models at scale you need an environment that can support many GPUs across many servers, networking together for individual GPUs that behave as a single processing unit to solve highly complex problems, faster.

This makes the network critical for training use cases and introduces all kinds of challenges to data center infrastructure and operations, especially if the underlying facility was not built for AI from inception. And most organizations today are not looking to build new data centers.

Therefore, organizations building out their AI data center strategies will have to answer important questions like:

• What AI use cases do you need to support, and based on the business outcomes you need to deliver, where do they fall into the build the model, optimize the model, and use the model buckets?
• Where is the data you need, and where is the best location to enable these use cases to optimize outcomes and minimize the costs?
• Do you need to deliver more power? Are your facilities able to cool these types of workloads with existing methods or do you require new methods like water cooling?
• Finally, what is the impact on your organization’s sustainability goals?

The power of Cisco Compute solutions for AI

As the general manager and senior vice president for Cisco’s compute business, I’m happy to say that Cisco UCS servers are designed for demanding use cases like AI fine-tuning and inferencing, VDI, and many others. With its future-ready, highly modular architecture, Cisco UCS empowers our customers with a blend of high-performance CPUs, optional GPU acceleration, and software-defined automation. This translates to efficient resource allocation for diverse workloads and streamlined management through Cisco Intersight. You can say that with UCS, you get the muscle to power your creativity and the brains to optimize its use for groundbreaking AI use cases.

But Cisco is one player in a wide ecosystem. Technology and solution partners have long been a key to our success, and this is certainly no different in our strategy for AI. This strategy revolves around driving maximum customer value to harness the full long-term potential behind each partnership, which enables us to combine the best of compute and networking with the best tools in AI.

This is the case in our strategic partnerships with NVIDIA, Intel, AMD, Red Hat, and others. One key deliverable has been the steady stream of Cisco Validated Designs (CVDs) that provide pre-configured solution blueprints that simplify integrating AI workloads into existing IT infrastructure. CVDs eliminate the need for our customers to build their AI infrastructure from scratch. This translates to faster deployment times and reduced risks associated with complex infrastructure configurations and deployments.

Another key pillar of our AI computing strategy is offering customers a diversity of solution options that include standalone blade and rack-based servers, converged infrastructure, and hyperconverged infrastructure (HCI). These options enable customers to address a variety of use cases and deployment domains throughout their hybrid multicloud environments – from centralized data centers to edge end points. Here are just a couple of examples:

• Converged infrastructures with partners like NetApp and Pure Storage offer a strong foundation for the full lifecycle of AI development from training AI models to day-to-day operations of AI workloads in production environments. For highly demanding AI use cases like scientific research or complex financial simulations, our converged infrastructures can be customized and upgraded to provide the scalability and flexibility needed to handle these computationally intensive workloads efficiently.
• We also offer an HCI option through our strategic partnership with Nutanix that is well-suited for hybrid and multi-cloud environments through the cloud-native designs of Nutanix solutions. This allows our customers to seamlessly extend their AI workloads across on-premises infrastructure and public cloud resources, for optimal performance and cost efficiency. This solution is also ideal for edge deployments, where real-time data processing is crucial.

AI Infrastructure with sustainability in mind 

Cisco’s engineering teams are focused on embedding energy management, software and hardware sustainability, and business model transformation into everything we do. Together with energy optimization, these new innovations will have the potential to help more customers accelerate their sustainability goals.

Working in tandem with engineering teams across Cisco, Denise Lee leads Cisco’s Engineering Sustainability Office with a mission to deliver more sustainable products and solutions to our customers and partners. With electricity usage from data centers, AI, and the cryptocurrency sector potentially doubling by 2026, according to a recent International Energy Agency report, we are at a pivotal moment where AI, data centers, and energy efficiency must come together. AI data center ecosystems must be designed with sustainability in mind. Denise outlined the systems design thinking that highlights the opportunities for data center energy efficiency across performance, cooling, and power in her recent blog, Reimagine Your Data Center for Responsible AI Deployments.

Recognition for Cisco’s efforts have already begun. Cisco’s UCS X-series has received the Sustainable Product of the Year by SEAL Awards and an Energy Star rating from the U.S. Environmental Protection Agency. And Cisco continues to focus on critical features in our portfolio through agreement on product sustainability requirements to address the demands on data centers in the years ahead.

Look ahead to Cisco Live

We are just a couple of months away from Cisco Live US, our premier customer event and showcase for the many different and exciting innovations from Cisco and our technology and solution partners. We will be sharing many exciting Cisco Compute solutions for AI and other uses cases. Our Sustainability Zone will feature a virtual tour through a modernized Cisco data center where you can learn about Cisco compute technologies and their sustainability benefits. I’ll share more details in my next blog closer to the event.

Source: cisco.com

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Bridging the Digital Divide with Subscriber Edge

Bridging the digital divide has been a longstanding top priority for countries globally. According to Broadband Research, in 2023 approximately five billion people (64% of the world’s population) were connected to the internet. That means roughly three billion people do not have the basic digital necessities such as access to data, sharing information, or communicating. In addition, they do not have the same access to educational, employment, and economic opportunities that could improve the quality of their lives through digital connections.

The World Bank has estimated that increasing the percentage of people with internet access to 75% would “boost the developing world’s collective GDP by $2 trillion and create 140 million new jobs.”

The good news is that the public and private sectors have been partnering to help close the digital divide, but as Broadband Research states: “Factors like increased affordability of devices, improved infrastructure and innovative services drive this growth.”

Role of subscriber edge

Accessing the internet requires a subscription to a broadband service from communications service providers (CSPs), using either cable, fiber, DSL, fixed wireless access (FWA), satellite or 4G/5G infrastructure and devices. Subscriber edge is the access point function for subscribers in a service provider network through which they connect to the broadband network for high-speed connectivity, such as accessing the internet.

Subscriber edge can be deployed with other services on the same platform by converging residential and enterprise services using multiservice nodes. Subscriber edge solutions involve managing subscriber sessions, and include functions like IP address management, policy and quality of service (QoS) enforcement, and secure access to the network through authentication and billing.

Shifting application and traffic demands

Traditional approaches for offering broadband services can be revenue-impacting and could affect the quality of experience (QoE) for a broadband user (see Figure 1). For example, with the advancement of applications and evolving transport protocols—such as Quick UDP Internet Connections (QUIC) and Transmission Control Protocol/ Transport Layer Security (TCPLS)—traffic patterns within broadband networks are experiencing a shift away from traditional transport protocols. These new protocols offer greater control to end-user applications, which reduces the dependency on the underlying broadband network and requires relatively simpler QoS models.

This shift is a pivotal opportunity for CSPs to simplify and modernize their complex traditional broadband networks to address higher bandwidth demands, growing user base, increasing video traffic and rising costs. As a result, there is a need to relook at subscriber edge with the overall subscriber services network design, and address important areas such as:

• Subscriber anchor point in the network
• Selection of subscriber edge devices and architecture
• Improve end-user experience and offer new services
• Address rising network costs

Figure 1. Traditional broadband centralized architecture

Source: cisco.com

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Experience Eco-Friendly Data Center Efficiency with Cisco’s Unified Computing System (UCS)

In the highly dynamic and ever-evolving world of enterprise computing, data centers serve as the backbones of operations, driving the need for powerful, scalable, and energy-efficient server solutions. As businesses continuously strive to refine their IT ecosystems, recognizing and capitalizing on data center energy-saving attributes and design innovations is essential for fostering sustainable development and maximizing operational efficiency and effectiveness.

Cisco’s Unified Computing System (UCS) stands at the forefront of this technological landscape, offering a comprehensive portfolio of server options tailored to meet the most diverse of requirements. Each component of the UCS family, including the B-Series, C-Series, HyperFlex, and X-Series, is designed with energy efficiency in mind, delivering performance while mitigating energy use. Energy efficiency is a major consideration, starting from the beginning of the planning and design phases of these technologies and products all the way through into each update.

The UCS Blade Servers and Chassis (B-Series) provide a harmonious blend of integration and dense computing power, while the UCS Rack-Mount Servers (C-Series) offer versatility and incremental scalability. These offerings are complemented by Cisco’s UCS HyperFlex Systems, the next-generation of hyper-converged infrastructure that brings compute, storage, and networking into a cohesive, highly efficient platform. Furthermore, the UCS X-Series takes flexibility and efficiency to new heights with its modular, future-proof architecture.

Cisco UCS B-Series Blade Chassis and Servers

The Cisco UCS B-Series Blade Chassis and Servers offer several features and design elements that contribute to greater energy efficiency compared to traditional blade server chassis. The following components and functions of UCS contribute to this efficiency:

1. Unified Design: Cisco UCS incorporates a unified system that integrates computing, networking, storage access, and virtualization resources into a single, cohesive architecture. This integration reduces the number of physical components needed, leading to lower power consumption compared to traditional setups where these elements are usually separate and require additional power.

2. Power Management: UCS includes sophisticated power management capabilities at both the hardware and software levels. This enables dynamic power allocation based on workload demands, allowing unused resources to be powered down or put into a low-power state. By adjusting power usage according to actual requirements, the wasting of energy is minimized.

3. Efficient Cooling: The blade servers and chassis are designed to optimize airflow and cooling efficiency. This reduces the need for excessive cooling, which can be a significant contributor to energy consumption in data centers. By efficiently managing airflow and cooling, Cisco UCS helps minimize the overall energy required for server operation.

4. Higher Density: UCS Blade Series Chassis typically support higher server densities compared to traditional blade server chassis. By consolidating more computing power into a smaller physical footprint, organizations can achieve greater efficiency in terms of space utilization, power consumption, and cooling requirements.

5. Virtualization Support: Cisco UCS is designed to work seamlessly with virtualization technologies such as VMware, Microsoft Hyper-V, and others. Virtualization allows for better utilization of server resources by running multiple virtual machines (VMs) on a single physical server. This consolidation reduces the total number of servers needed, thereby lowering energy consumption across the data center.

6. Power capping and monitoring: UCS provides features for power capping and monitoring, allowing administrators to set maximum power limits for individual servers or groups of servers. This helps prevent power spikes and ensures that power usage remains within predefined thresholds, thus optimizing energy efficiency.

7. Efficient Hardware Components: UCS incorporates energy-efficient hardware components such as processors, memory modules, and power supplies. These components are designed to deliver high performance while minimizing power consumption, contributing to overall energy efficiency.

Cisco UCS Blade Series Chassis and Servers facilitate greater energy efficiency through a combination of unified design, power management capabilities, efficient cooling, higher physical density, support for virtualization, and the use of energy-efficient hardware components. By leveraging these features, organizations can reduce their overall energy consumption and operational costs in the data center.

Cisco UCS C-Series Rack Servers

Cisco UCS C-Series Rack Servers are standalone servers that tend to be more flexible in terms of deployment and may be easier to cool individually. They are often more efficient in environments where fewer servers are required or when full utilization of a blade chassis is not possible. In such cases, deploying a few rack servers can be more energy-efficient than powering a partially empty blade chassis.

The Cisco UCS Rack Servers, like the Blade Series, have been designed with energy efficiency in mind. The following aspects contribute to the energy efficiency of UCS Rack Servers:

1. Modular Design: UCS Rack Servers are built with a modular design that allows for easy expansion and servicing. This means that components can be added or replaced as needed without unnecessary wasting resources.

2. Component Efficiency: Like the Blade Series, UCS Rack Servers use high-efficiency power supplies, voltage regulators, and cooling fans. These components are chosen for their ability to deliver performance while minimizing energy consumption.

3. Thermal Design: The physical design of the UCS Rack Servers helps to optimize airflow, which can reduce the need for excessive cooling. Proper thermal management ensures that the servers maintain an optimal operating temperature, which contributes to energy savings.

4. Advanced CPUs: UCS Rack Servers are equipped with the latest processors that offer a balance between performance and power usage. These CPUs often include features that reduce power consumption when full performance is not required.

5. Energy Star Certification: Many UCS Rack Servers are Energy Star certified, meaning they meet strict energy efficiency guidelines set by the U.S. Environmental Protection Agency.

6. Management Software: Cisco’s management software allows for detailed monitoring and control of power usage across UCS Rack Servers. This software can help identify underutilized resources and optimize power settings based on the workload.

Cisco UCS Rack Servers are designed with energy efficiency as a core principle. They feature a modular design that enables easy expansion and servicing, high-efficiency components such as power supplies and cooling fans, and processors that balance performance with power consumption. The thermal design of these rack servers optimizes airflow, contributing to reduced cooling needs.

Additionally, many UCS Rack Servers have earned Energy Star certification, indicating compliance with stringent energy efficiency guidelines. Management software further enhances energy savings by allowing detailed monitoring and control over power usage, ensuring that resources are optimized according to workload demands. These factors make UCS Rack Servers a suitable choice for data centers focused on minimizing energy consumption while maintaining high performance.

Cisco UCS S-Series Storage Servers

The Cisco UCS S-Series servers are engineered to offer high-density storage solutions with scalability, which leads to considerable energy efficiency benefits when compared to the UCS B-Series blade servers and C-Series rack servers. The B-Series focuses on optimizing compute density and network integration in a blade server form factor, while the C-Series provides versatile rack-mount server solutions. In contrast, the S-Series emphasizes storage density and capacity.

Each series has its unique design optimizations; however, the S-Series can often consolidate storage and compute resources more effectively, potentially reducing the overall energy footprint by minimizing the need for additional servers and standalone storage units. This consolidation is a key factor in achieving greater energy efficiency within data centers.

The UCS S-Series servers incorporate the following features that contribute to energy efficiency:

1. Efficient Hardware Components: Similar to other Cisco UCS servers, the UCS S-Series servers utilize energy-efficient hardware components such as processors, memory modules, and power supplies. These components are designed to provide high performance while minimizing power consumption, thereby improving energy efficiency.
2. Scalability and Flexibility: S-Series servers are highly scalable and offer flexible configurations to meet diverse workload requirements. This scalability allows engineers to right-size their infrastructure and avoid over-provisioning, which often leads to wasteful energy consumption.
3. Storage Optimization: UCS S-Series servers are optimized for storage-intensive workloads by offering high-density storage options within a compact form factor. With consolidated storage resources via fewer physical devices, organizations can reduce power consumption associated with managing and powering multiple storage systems.
4. Power Management Features: S-Series servers incorporate power management features similar to other UCS servers, allowing administrators to monitor and control power usage at both the server and chassis levels. These features enable organizations to optimize power consumption based on workload demands, reducing energy waste.
5. Unified Management: UCS S-Series servers are part of the Cisco Unified Computing System, which provides unified management capabilities for the entire infrastructure, including compute, storage, and networking components. This centralized management approach helps administrators efficiently monitor and optimize energy usage across the data center.

Cisco UCS HyperFlex HX-Series Servers

The Cisco HyperFlex HX-Series represents a fully integrated and hyperconverged infrastructure system that combines computing, storage, and networking into a simplified, scalable, and high-performance architecture designed to handle a wide array of workloads and applications.

When it comes to energy efficiency, the HyperFlex HX-Series stands out by further consolidating data center functions and streamlining resource management compared to the traditional UCS B-Series, C-Series, and S-Series. Unlike the B-Series blade servers which prioritize compute density, the C-Series rack servers which offer flexibility, or the S-Series storage servers which focus on high-density storage, the HX-Series incorporates all of these aspects into a cohesive unit. By doing so, it reduces the need for separate storage and compute layers, leading to potentially lower power and cooling requirements.

The integration inherent in hyperconverged infrastructure, such as the HX-Series, often results in higher efficiency and a smaller energy footprint as it reduces the number of physical components required, maximizes resource utilization, and optimizes workload distribution; all of this contributes to a more energy-conscious data center environment.

The HyperFlex can contribute to energy efficiency in the following ways:

1. Consolidation of Resources: HyperFlex integrates compute, storage, and networking resources into a single platform, eliminating the need for separate hardware components such as standalone servers, storage arrays, and networking switches. By consolidating these resources, organizations can reduce overall power consumption when compared to traditional infrastructure setups that require separate instances of these components.
2. Efficient Hardware Components: HyperFlex HX-Series Servers are designed to incorporate energy-efficient hardware components such as processors, memory modules, and power supplies. These components are optimized for performance, per watt, helping to minimize power consumption while delivering the necessary robust compute and storage capabilities.
3. Dynamic Resource Allocation: HyperFlex platforms often include features for dynamic resource allocation and optimization. This may include technologies such as VMware Distributed Resource Scheduler (DRS) or Cisco Intersight Workload Optimizer, which intelligently distribute workloads across the infrastructure to maximize resource utilization and minimize energy waste.
4. Software-Defined Storage Efficiency: HyperFlex utilizes software-defined storage (SDS) technology, which allows for more efficient use of storage resources compared to traditional storage solutions. Features such as deduplication, compression, and thin provisioning help to reduce the overall storage footprint, resulting in lower power consumption associated with storage devices.
5. Integrated Management and Automation: HyperFlex platforms typically include centralized management and automation capabilities that enable administrators to efficiently monitor and control the entire infrastructure from a single interface. This combined integration management approach can streamline operations, optimize resource usage, and identify opportunities for energy saving.
6. Scalability and Right-Sizing: HyperFlex allows organizations to scale resources incrementally by adding additional server nodes to the cluster as needed. This scalability enables organizations to custom fit their infrastructure and avoid over-provisioning, which can lead to unnecessary energy consumption.
7. Efficient Cooling Design: HyperFlex systems are designed with extreme consideration for efficient cooling to maintain optimal operating temperatures for the hardware components. By optimizing airflow and cooling mechanisms within the infrastructure, HyperFlex helps minimize energy consumption associated with cooling systems.

Cisco UCS X-Series Modular System

The Cisco UCS X-Series is a versatile and innovative computing platform that elevates the concept of a modular system to new heights, offering a flexible, future-ready solution for the modern data center. It stands apart from the traditional UCS B-Series blade servers, C-Series rack servers, S-Series storage servers, and even the integrated HyperFlex HX-Series hyperconverged systems, in that it provides a unique blend of adaptability and scalability. The X-Series is designed with a composable infrastructure that allows dynamic reconfiguration of computing, storage, and I/O resources to match specific workload requirements.

In terms of energy efficiency, the UCS X-Series is engineered to streamline power usage by dynamically adapting to the demands of various applications. It achieves this through a technology that allows components to be powered on and off independently, which can lead to significant energy savings compared to the always-on nature of B-Series and C-Series servers. While the S-Series servers are optimized for high-density storage, the X-Series can reduce the need for separate high-capacity storage systems by incorporating storage elements directly into its composable framework. Furthermore, compared to the HyperFlex HX-Series, the UCS X-Series may offer even more granular control over resource allocation, potentially leading to even better energy management and waste reduction.

The UCS X-Series platform aims to set a new standard for sustainability by optimizing power consumption across diverse workloads, minimizing the environmental impact, and lowering the total cost of ownership (TCO) through improved energy efficiency. By intelligently consolidating and optimizing resources, the X-Series promises, and has proven to be, a forward-looking solution that responds to the growing need for eco-friendly and cost-effective data center operations.

The Cisco UCS X-Series can contribute to energy efficiency in the following ways:

1. Integrated Architecture: Cisco UCS X-Series combines compute, storage, and networking into a unified system, reducing the need for seperate components. This consolidation leads to lower overall energy consumption compared to traditional data center architectures.
2. Energy-Efficient Components: The UCS X-Series is built with the latest energy-efficient technologies; CPUs, memory modules, and power supplies in the X-Series are selected for their performance-to-power consumption ratio, ensuring that energy use is optimized without sacrificing performance.
3. Intelligent Workload Placement: Cisco UCS X-Series can utilize Cisco Intersight and other intelligent resource management tools to distribute workloads intelligently and efficiently across available resources, optimizing power usage and reducing unnecessary energy expenditure.
4. Software-Defined Storage Benefits: The X-Series can leverage software-defined storage which often includes features like deduplication, compression, and thin provisioning to make storage operations more efficient and reduce the energy needed for data storage.
5. Automated Management: With Cisco Intersight, the X-Series provides automated management and orchestration across the infrastructure, helping to streamline operations, reduce manual intervention, and cut down on energy usage through improved allocation of resources.
6. Scalable Infrastructure: The modular design of the UCS X-Series allows for easy scalability, thus allowing organizations to add resources only as needed. This helps prevent over-provisioning and the energy costs associated with idle equipment.
7. Optimized Cooling: The X-Series chassis is designed with cooling efficiency in mind, using advanced airflow management and heat sinks to keep components at optimal temperatures. This reduces the amount of energy needed for cooling infrastructure.

Mindful energy consumption without compromise

Cisco’s UCS offers a robust and diverse suite of server solutions, each engineered to address the specific demands of modern-day data centers with a sharp focus on energy efficiency. The UCS B-Series and C-Series each bring distinct advantages in terms of integration, computing density, and flexible scalability, while the S-Series specializes in high-density storage capabilities. The HyperFlex HX-Series advances the convergence of compute, storage, and networking, streamlining data center operations and energy consumption. Finally, the UCS X-Series represents the pinnacle of modularity and future-proof design, delivering unparalleled flexibility to dynamically meet the shifting demands of enterprise workloads.

Across this entire portfolio, from the B-Series to the X-Series, Cisco has infused an ethos of sustainability, incorporating energy-efficient hardware, advanced power management, and intelligent cooling designs. By optimizing the use of resources, embracing virtualization, and enabling scalable, granular infrastructure deployments, Cisco’s UCS platforms are not just powerful computing solutions but are also catalysts for energy-conscious, cost-effective, and environmentally responsible data center operations.

For organizations navigating the complexities of digital transformation while balancing operational efficiency with the goal of sustainability, the Cisco UCS lineup stands ready to deliver performance that powers growth without compromising on our commitment to a greener future.

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Understanding the Differences between SD-WAN and MPLS

In the realm of networking, SD-WAN and MPLS are two terms that frequently arise, each offering distinct advantages and functionalities. In this comprehensive guide, we delve into the nuances of these technologies, providing clarity on their disparities and assisting you in making informed decisions for your network infrastructure.

What is SD-WAN?

SD-WAN, or Software-Defined Wide Area Network, is a modern approach to networking that utilizes software-defined networking (SDN) concepts to intelligently manage and optimize Wide Area Network (WAN) connections. Unlike traditional WAN setups that rely heavily on hardware, SD-WAN leverages software to dynamically route traffic across the network based on predefined policies and conditions.

Key Features of SD-WAN:

1. Centralized Management: SD-WAN solutions offer centralized management interfaces that provide administrators with granular control over network configurations and traffic flow.
2. Dynamic Path Selection: With SD-WAN, traffic is intelligently routed across multiple network paths, including broadband, MPLS, and LTE, based on real-time conditions such as link quality and latency.
3. Application Awareness: SD-WAN platforms often incorporate deep packet inspection and application recognition capabilities, allowing for the prioritization of critical applications and traffic shaping based on application requirements.
4. Cost Efficiency: By leveraging lower-cost internet connections alongside more expensive MPLS links, SD-WAN can significantly reduce WAN expenses without compromising performance or reliability.

Understanding MPLS

MPLS, or Multiprotocol Label Switching, is a legacy networking technology commonly used for building private, high-performance WANs. MPLS operates by assigning labels to network packets, enabling routers to make forwarding decisions based on these labels rather than IP addresses.

Key Features of MPLS:

1. Traffic Engineering: MPLS networks support traffic engineering capabilities, allowing administrators to optimize network paths and allocate bandwidth efficiently.
2. Quality of Service (QoS): MPLS offers robust QoS mechanisms, ensuring that critical applications receive the necessary bandwidth and latency guarantees to maintain optimal performance.
3. Security: MPLS inherently provides a higher level of security compared to public internet connections, as traffic remains within the confines of the private MPLS network, reducing exposure to external threats.
4. Reliability: MPLS networks are known for their reliability and predictability, making them ideal for applications that require consistent performance and uptime.

Contrasting SD-WAN and MPLS

While both SD-WAN and MPLS serve the purpose of connecting geographically dispersed locations within an organization, they differ significantly in terms of architecture, cost, and flexibility.

Architecture:

• SD-WAN: SD-WAN architectures are decentralized and software-driven, offering flexibility and scalability to adapt to changing network requirements rapidly.
• MPLS: MPLS networks are centralized and hardware-dependent, typically requiring substantial upfront investments in infrastructure and equipment.

Cost:

• SD-WAN: SD-WAN solutions often provide cost savings compared to MPLS, particularly for organizations with diverse connectivity requirements or those seeking to augment MPLS with lower-cost internet links.
• MPLS: MPLS services can be costly, primarily due to the need for dedicated circuits and long-term contracts with service providers.

Flexibility:

• SD-WAN: SD-WAN architectures offer unparalleled flexibility, allowing organizations to seamlessly integrate various transport technologies and cloud services into their network environments.
• MPLS: MPLS networks are less flexible, with limited support for cloud connectivity and scalability compared to SD-WAN solutions.

Conclusion

In summary, both SD-WAN and MPLS have their merits and are suited to different network environments and business requirements. SD-WAN excels in providing agility, cost efficiency, and flexibility, making it an attractive option for organizations seeking to modernize their network infrastructure. On the other hand, MPLS offers reliability, security, and quality of service, making it well-suited for mission-critical applications and industries with stringent compliance requirements.

Ultimately, the choice between SD-WAN and MPLS depends on factors such as budget, performance needs, and organizational priorities. By understanding the nuances of each technology, organizations can make informed decisions that align with their strategic objectives and drive business success.

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