#cloud computing data center

[cbreindia]

How CBRE is Shaping the Data Center solution Landscape in India

A data center is a building or a dedicated space within a building that incorporates  computer systems to provide shared access to applications and data using a complex network and storage infrastructure. The rapid growth of technology and the digital revolution have led to an exponential increase in the demand for data centers worldwide. As India emerges as a major player in the global technology sector, the need for robust and efficient data center solutions has become paramount. The increasing demand for digital services, cloud computing, and the rapid expansion of the internet and mobile networks gave birth to the Data Center as a leading alternative real estate segment.

CBRE India shaping Data center

CBRE India, a commercial real estate services and investment agency is shaping the Data Center solution landscape in India by providing end to end solutions in terms of  building, developing, buying, selling or managing a data center. It also serves the entire real estate and IT processes of a Data Center, including advisory, transaction, project management and facilities management disciplines. Through their project management services, CBRE India ensures the timely and efficient execution of data center construction projects, adhering to international standards and best practices. 

DC growth in Mumbai

Mumbai is the  biggest DC market in India with 40% of the total capacity. Mumbai has a robust infrastructure in terms of power supply and  telecommunications network and is also home to numerous financial institutions and MNCs. Due to these factors and the growth of internet users and government propelled initiatives like "Digital India" and "Smart Cities Mission", the Data Center in Mumbai is a thriving segment. 

DC crossing threshold

Data Center companies in India will soar high in the market with the size of $4.5 billion by 2025, becoming a significant contributor in the global economy. Investment in this sector is expected to grow to USD 20 million by 2025. Around 250 MW of additional data center capacity is expected to come online, thus taking the total co-location capacity in India to 1.15 GW.

DC Services by CBRE India

CBRE India is revolutionising the data center industry by providing impeccable services in market analysis and insights, expertise and consultancy on infrastructure development, adoption of energy efficient practices for sustainability and implementing cutting-edge solutions like edge computing, AI-driven automation, and advanced cooling techniques for future readiness and innovation. CBRE India assists investors and operators in identifying potential locations, gauging demand-supply dynamics and understanding customer requirements. 

Out and out, the Data Center solution is going through the phase of territory expansion with the traction in demand as well as investment for data center companies in India, all thanks to digitization. Given the data center market is evolving at an unprecedented pace, Data Center companies in India are looking forward to a state of the art infrastructure which makes CBRE a pioneer in the business.

[nixcraft]

[betagrove]

That tweet about each ai prompt wasting a full 16oz of water isn't true like at all

[peterbordes]

(via AI inference chip startup Groq closes $640M at $2.8B valuation to meet next-gen LPUs demand)

Groq, a leader in fast AI inference, has secured a $640M Series D round at a valuation of $2.8B. The round was led by funds and accounts managed by BlackRock Private Equity Partners with participation from both existing and new investors including Neuberger Berman, Type One Ventures, and strategic investors including Cisco Investments, Global Brain’s KDDI Open Innovation Fund III, and Samsung Catalyst Fund. The unique, vertically integrated Groq AI inference platform has generated skyrocketing demand from developers seeking exceptional speed.

[radiantinfosolutions]

The Growing Demand for Data Center Architects in India’s IT Sector

Learn how Radiant Info Solutions is shaping India’s IT sector with cutting-edge data center architecture services, offering scalable, secure, and energy-efficient solutions.

[jcmarchi]

Shaktiman Mall, Principal Product Manager, Aviatrix – Interview Series

New Post has been published on https://thedigitalinsider.com/shaktiman-mall-principal-product-manager-aviatrix-interview-series/

Shaktiman Mall, Principal Product Manager, Aviatrix – Interview Series

Shaktiman Mall is Principal Product Manager at Aviatrix. With more than a decade of experience designing and implementing network solutions, Mall prides himself on ingenuity, creativity, adaptability and precision. Prior to joining Aviatrix, Mall served as Senior Technical Marketing Manager at Palo Alto Networks and Principal Infrastructure Engineer at MphasiS.

Aviatrix is a company focused on simplifying cloud networking to help businesses remain agile. Their cloud networking platform is used by over 500 enterprises and is designed to provide visibility, security, and control for adapting to changing needs. The Aviatrix Certified Engineer (ACE) Program offers certification in multicloud networking and security, aimed at supporting professionals in staying current with digital transformation trends.

What initially attracted you to computer engineering and cybersecurity?

As a student, I was initially more interested in studying medicine and wanted to pursue a degree in biotechnology. However, I decided to switch to computer science after having conversations with my classmates about technological advancements over the preceding decade and emerging technologies on the horizon.

Could you describe your current role at Aviatrix and share with us what your responsibilities are and what an average day looks like?

I’ve been with Aviatrix for two years and currently serve as a principal product manager in the product organization. As a product manager, my responsibilities include building product vision, conducting market research, and consulting with the sales, marketing and support teams. These inputs combined with direct customer engagement help me define and prioritize features and bug fixes.

I also ensure that our products align with customers’ requirements. New product features should be easy to use and not overly or unnecessarily complex. In my role, I also need to be mindful of the timing for these features – can we put engineering resources toward it today, or can it wait six months? To that end, should the rollout be staggered or phased into different versions? Most importantly, what is the projected return on investment?

An average day includes meetings with engineering, project planning, customer calls, and meetings with sales and support. Those discussions allow me to get an update on upcoming features and use cases while understanding current issues and feedback to troubleshoot before a release.

What are the primary challenges IT teams face when integrating AI tools into their existing cloud infrastructure?

Based on real-world experience of integrating AI into our IT technology, I believe there are four challenges companies will encounter:

Harnessing data & integration: Data enriches AI, but when data is across different places and resources in an organization, it can be difficult to harness it properly.

Scaling: AI operations can be CPU intensive, making scaling challenging.

Training and raising awareness: A company could have the most powerful AI solution, but if employees don’t know how to use it or don’t understand it, then it will be underutilized.

Cost: For IT especially, a quality AI integration will not be cheap, and businesses must budget accordingly.

Security: Make sure that the cloud infrastructure meets security standards and regulatory requirements relevant to AI applications

How can businesses ensure their cloud infrastructure is robust enough to support the heavy computing needs of AI applications?

There are multiple factors to running AI applications. For starters, it’s critical to find the right type and instance for scale and performance.

Also, there needs to be adequate data storage, as these applications will draw from static data available within the company and build their own database of information. Data storage can be costly, forcing businesses to assess different types of storage optimization.

Another consideration is network bandwidth. If every employee in the company uses the same AI application at once, the network bandwidth needs to scale – otherwise, the application will be so slow as to be unusable. Likewise, companies need to decide if they will use a centralized AI model where computing happens in a single place or a distributed AI model where computing happens closer to the data sources.

With the increasing adoption of AI, how can IT teams protect their systems from the heightened risk of cyberattacks?

There are two main aspects to security every IT team must consider. First, how do we protect against external risks? Second, how do we ensure data, whether it is the personally identifiable information (PII) of customers or proprietary information, remains within the company and is not exposed? Businesses must determine who can and cannot access certain data. As a product manager, I need sensitive information others are not authorized to access or code.

At Aviatrix, we help our customers protect against attacks, allowing them to continue adopting technologies like AI that are essential for being competitive today. Recall network bandwidth optimization: because Aviatrix acts as the data plane for our customers, we can manage the data going through their network, providing visibility and enhancing security enforcement.

Likewise, our distributed cloud firewall (DCF) solves the challenges of a distributed AI model where data gets queried in multiple places, spanning geographical boundaries with different laws and compliances. Specifically, a DCF supports a single set of security compliance enforced across the globe, ensuring the same set of security and networking architecture is supported. Our Aviatrix Networks Architecture also allows us to identify choke points, where we can dynamically update the routing table or help customers create new connections to optimize AI requirements.

How can businesses optimize their cloud spending while implementing AI technologies, and what role does the Aviatrix platform play in this?

One of the main practices that will help businesses optimize their cloud spending when implementing AI is minimizing egress spend.

Cloud network data processing and egress fees are a material component of cloud costs. They are both difficult to understand and inflexible. These cost structures not only hinder scalability and data portability for enterprises, but also provide decreasing returns to scale as cloud data volume increases which can impact organizations’ bandwidth.

Aviatrix designed our egress solution to give the customer visibility and control. Not only do we perform enforcement on gateways through DCF, but we also do native orchestration, enforcing control at the network interface card level for significant cost savings. In fact, after crunching the numbers on egress spend, we had customers report savings between 20% and 40%.

We’re also building auto-rightsizing capabilities to automatically detect high resource utilization and automatically schedule upgrades as needed.

Lastly, we ensure optimal network performance with advanced networking capabilities like intelligent routing, traffic engineering and secure connectivity across multi-cloud environments.

How does Aviatrix CoPilot enhance operational efficiency and provide better visibility and control over AI deployments in multicloud environments?

Aviatrix CoPilot’s topology view provides real-time network latency and throughput, allowing customers to see the number of VPC/VNets. It also displays different cloud resources, accelerating problem identification. For example, if the customer sees a latency issue in a network, they will know which assets are getting affected. Also, Aviatrix CoPilot helps customers identify bottlenecks, configuration issues, and improper connections or network mapping. Furthermore, if a customer needs to scale up one of its gateways into the node to accommodate more AI capabilities, Aviatrix CoPilot can automatically detect, scale, and upgrade as necessary.

Can you explain how dynamic topology mapping and embedded security visibility in Aviatrix CoPilot assist in real-time troubleshooting of AI applications?

Aviatrix CoPilot’s dynamic topology mapping also facilitates robust troubleshooting capabilities. If a customer must troubleshoot an issue between different clouds (requiring them to understand where traffic was getting blocked), CoPilot can find it, streamlining resolution. Not only does Aviatrix CoPilot visualize network aspects, but it also provides security visualization components in the form of our own threat IQ, which performs security and vulnerability protection. We help our customers map the networking and security into one comprehensive visualization solution.

We also help with capacity planning for both cost with costIQ, and performance with auto right sizing and network optimization.

How does Aviatrix ensure data security and compliance across various cloud providers when integrating AI tools?

AWS and its AI engine, Amazon Bedrock, have different security requirements from Azure and Microsoft Copilot. Uniquely, Aviatrix can help our customers create an orchestration layer where we can automatically align security and network requirements to the CSP in question. For example, Aviatrix can automatically compartmentalize data for all CSPs irrespective of APIs or underlying architecture.

It is important to note that all of these AI engines are inside a public subnet, which means they have access to the internet, creating additional vulnerabilities because they consume proprietary data. Thankfully, our DCF can sit on a public and private subnet, ensuring security. Beyond public subnets, it can also sit across different regions and CSPs, between data centers and CSPs or VPC/VNets and even between a random site and the cloud. We establish end-to-end encryption across VPC/VNets and regions for secure transfer of data. We also have extensive auditing and logging for tasks performed on the system, as well as integrated network and policy with threat detection and deep packet inspection.

What future trends do you foresee in the intersection of AI and cloud computing, and how is Aviatrix preparing to address these trends?

I see the interaction of AI and cloud computing birthing incredible automation capabilities in key areas such as networking, security, visibility, and troubleshooting for significant cost savings and efficiency.

It could also analyze the different types of data entering the network and recommend the most suitable policies or security compliances. Similarly, if a customer needed to enforce HIPAA, this solution could scan through the customer’s networks and then recommend a corresponding strategy.

Troubleshooting is a major investment because it requires a call center to assist customers. However, most of these issues don’t necessitate human intervention.

Generative AI (GenAI) will also be a game changer for cloud computing. Today, a topology is a day-zero decision – once an architecture or networking topology gets built, it is difficult to make changes. One potential use case I believe is on the horizon is a solution that could recommend an optimal topology based on certain requirements. Another problem that GenAI could solve is related to security policies, which quickly become outdated after a few years. AGenAI solution could help users routinely create new security stacks per new laws and regulations.

Aviatrix can implement the same security architecture for a datacenter with our edge solution, given that more AI will sit close to the data sources. We can help connect branches and sites to the cloud and edge with AI computes running.

We also help in B2B integration with different customers or entities in the same company with separate operating models.

AI is driving new and exciting computing trends that will impact how infrastructure is built. At Aviatrix, we’re looking forward to seizing the moment with our secure and seamless cloud networking solution.

Thank you for the great interview, readers who wish to learn more should visit Aviatrix. 

[rosielindy]

One of the joys of working in technology are all the wonderful acronyms. I’m starting on a new technical project and hearing the term GNAS, so rather than asking somebody I decided to google it and found this page. I eventually found the correct acronym meaning but not here. I already know what a NAS is and discovered the G is Gateway.

What a relief! I really like my coworkers but not enough to do the last one on the list. 😜 😂

[ifitechsolu1pg2]

Data Center Transformation for L&T Hydrocarbon | Digital Transformation

Digital Transformation in LTHC needed to stable and secured connectivity with redundancy to avoid business downtime. IFI Suggested to do lift and shift via Azure migrate tool, which helps to replicate VM on block level to Azure, and during off business hours, final cutover is performed.

[poojalate]

How Leading Companies Are Leveraging Infrastructure as a Service (IaaS)

As businesses increasingly turn to digital solutions, Infrastructure as a Service (IaaS) has emerged as a vital component for modern enterprises. By utilizing cloud platforms, companies can enhance their agility, scalability, and cost-efficiency. This article explores infrastructure as a service examples and how leading companies are leveraging IaaS providers to drive innovation and growth.

What is Infrastructure as a Service (IaaS)?

IaaS is a cloud computing service model that delivers virtualized computing resources over the internet. It enables businesses to rent infrastructure components like servers, storage, and networking, rather than investing in physical hardware. This flexibility allows companies to scale resources according to their needs and focus on core activities without the burden of managing IT infrastructure.

1. Netflix: Enhancing Scalability and Performance

Cloud Infrastructure Examples

Netflix, the global streaming giant, leverages IaaS to manage its vast content library and ensure seamless streaming experiences for millions of users worldwide. By using IaaS providers like Amazon Web Services (AWS), Netflix can quickly scale its infrastructure to handle peak loads, such as new releases or seasonal spikes in viewership. This scalability ensures high performance and availability, crucial for maintaining customer satisfaction.

2. Airbnb: Optimizing Resource Management

IaaS Use Cases

Airbnb, the popular online marketplace for lodging, utilizes IaaS to manage its global operations. The company employs cloud services examples like dynamic scaling to match infrastructure resources with fluctuating demand. During peak travel seasons or significant events, Airbnb can scale up its infrastructure to accommodate increased traffic, ensuring reliable service and user experience.

3. Slack: Ensuring Data Security and Compliance

Cloud Platforms

Slack, a leading collaboration platform, relies on IaaS for data security and regulatory compliance. By partnering with IaaS providers like Google Cloud Platform (GCP), Slack benefits from advanced security features, including encryption and compliance with industry standards such as GDPR and HIPAA. This ensures that sensitive business communications remain secure and compliant with regulations.

4. Pinterest: Enhancing Development and Innovation

IaaS Providers

Pinterest, a visual discovery and bookmarking platform, leverages IaaS to accelerate development cycles and foster innovation. Using cloud platforms like Microsoft Azure, Pinterest provides its developers with the tools and resources needed to build, test, and deploy new features rapidly. This agile development environment supports continuous improvement and innovation.

5. Spotify: Delivering Seamless Music Streaming

Cloud Infrastructure Examples

Spotify, the music streaming service, utilizes IaaS to manage its extensive music catalog and deliver high-quality streaming experiences. By using cloud platforms like Google Cloud, Spotify ensures that users can access their favorite music anytime, anywhere. The scalable infrastructure allows Spotify to handle millions of concurrent users without compromising performance.

6. Coca-Cola: Supporting Global Operations

IaaS Use Cases

Coca-Cola, a global beverage leader, uses IaaS to support its worldwide operations. By partnering with IaaS providers like IBM Cloud, Coca-Cola manages its supply chain, customer data, and digital marketing initiatives across different regions. This integrated approach enables Coca-Cola to maintain consistency and efficiency in its global operations.

7. Twitter: Managing Real-Time Data

Cloud Services Examples

Twitter, the social media platform, leverages IaaS to manage and process vast amounts of real-time data. Using cloud platforms like AWS, Twitter can handle high volumes of tweets, mentions, and user interactions with minimal latency. This capability is crucial for delivering real-time updates and maintaining user engagement.

8. General Electric: Facilitating Industrial IoT

IaaS Providers

General Electric (GE) uses IaaS to power its Industrial Internet of Things (IIoT) initiatives. By utilizing cloud platforms like Microsoft Azure, GE connects industrial equipment and collects data to optimize performance and predict maintenance needs. This data-driven approach enhances operational efficiency and reduces downtime.

9. eBay: Ensuring High Availability

Cloud Infrastructure Examples

eBay, the e-commerce giant, employs IaaS to ensure high availability and reliability for its global marketplace. By using IaaS providers like AWS, eBay can quickly scale its infrastructure to handle large volumes of transactions and user interactions. This reliability is essential for maintaining trust and satisfaction among buyers and sellers.

10. Zoom: Supporting Remote Communication

IaaS Use Cases

Zoom, the video conferencing service, relies on IaaS to support its global user base. By leveraging cloud platforms like Oracle Cloud, Zoom ensures high-quality video and audio communication, even during peak usage times. This scalability and reliability are critical for supporting remote work and virtual events.

Conclusion

Leading companies across various industries are leveraging Infrastructure as a Service (IaaS) to enhance scalability, performance, security, and innovation. By partnering with top IaaS providers and utilizing cloud infrastructure services, these businesses can stay agile, competitive, and responsive to market demands. Whether it's optimizing resource management, ensuring data security, or supporting global operations, IaaS provides the flexibility and power needed to drive business success in the digital age.

[madmantechnologies]

The Essential Role of Data Centre Solutions for IT Services Industries

Introduction:-

The need for reliable and effective data centre solutions in the quickly changing digital landscape cannot be emphasized. With companies depending more and more on cloud computing and digital platforms, data centres are now the mainstay of contemporary IT infrastructure. Offering complete data centre solutions is a must for IT service providers to guarantee the smooth running, security, and scalability of their clients' digital ecosystems.

The Pillars of Data Centre Solutions:-

A vast range of technologies and services are included in data centre solutions, which are intended to handle, store, and process data. The essential elements consist of:

Infrastructure Management:-

This refers to the hardware and software infrastructure needed for processing and storing data. The reliability of IT services is increased overall, peak performance is guaranteed, and downtime is minimized with effective infrastructure management.

2. Cloud integration:-

Integrating cloud services with traditional data centres becomes crucial as businesses shift to cloud-based models. By providing flexibility, scalability, and cost efficiency, this hybrid strategy enables businesses to make use of the greatest features from both worlds.

3. Data Security:

Sensitive information must be protected. To protect data from cyber threats, data centre solutions must incorporate strong security features including intrusion detection systems, firewalls, and encryption.

4. Disaster Recovery and Backup:

One essential component of data centre solutions is guaranteeing business continuity in the event of system failure or data loss. To reduce risks and guarantee a prompt restoration of services, regular backups and disaster recovery strategies are crucial.

5. Scalability:

Businesses need more data as they expand. Scalable data centre solutions guarantee that IT infrastructure can keep up with business demands by enabling organizations to grow their capacity and capabilities without requiring major overhauls.

Why Data Centre Solutions Matter for IT Services Companies

Enhanced Performance and Reliability: Data centres provide the foundation for reliable and high-performance IT services. By managing and optimizing data flow, IT services companies can ensure that their clients experience minimal downtime and maximum efficiency.

Cost Efficiency: Efficient data centre solutions can significantly reduce operational costs. By leveraging economies of scale, IT services companies can offer their clients cost-effective solutions while maintaining high service standards.

Compliance and Regulatory Adherence: Different industries have varying regulatory requirements for data management and security. Data centre solutions ensure that businesses comply with these regulations, avoiding legal pitfalls and enhancing their reputation.

Innovation and Competitive Advantage: Advanced data centre technologies such as artificial intelligence, machine learning, and big data analytics enable businesses to innovate and stay ahead of the competition. IT services companies that provide cutting-edge data centre solutions empower their clients to harness the power of these technologies.

Sustainability: Modern data centres are increasingly focused on energy efficiency and sustainability. By adopting green technologies and practices, IT services companies can help their clients reduce their carbon footprint and contribute to environmental conservation.

CONCLUSION -

In conclusion, a variety of criteria, such as the organization's budget, performance requirements, scalability needs, and compliance duties, influence the decision between traditional data centres and cloud alternatives. Scalability, flexibility, and cost-effectiveness are offered by cloud solutions, while control and security are provided by traditional data centres. Many businesses use a hybrid strategy, combining cloud and on-premises resources to strike the best possible balance between cost, scalability, and control. In the end, choosing the best IT infrastructure plan to support corporate growth and innovation in the digital age depends on knowing the particular requirements of the company.

Additionally, numerous people can view the data simultaneously thanks to this technology. This expedites and simplifies work. You may handle your data in real-time from any remote part of the world with the help of Madman Technologies, they are the best Cloud Computing and DC migration services in India.

You can google our website and contact us over the phone —

madmantechnologies.ai@gmail.com

Contact details — 9625468776

[onpassivereseller]

Automaattinen Tienaaminen - ONPASSIVE Digital Blueprint

ONPASSIVE Digital Blueprint. The research paper discusses the recent developments and future prospects of ONPASSIVE, a marketing business. It emphasizes the importance of understanding the business model and marketing platform within ONPASSIVE. The paper highlights the introduction of OConnect, traffic allocation, new products, and upcoming announcements by CEO Mr. Ash Mufareh. It underscores the…

[scloudsg]

Entering Europe: Data Center Colocation in Post-Brexit UK

In a groundbreaking move, Google has announced a staggering $1 billion investment in a new data center just outside of London, underscoring the UK’s position as a key player in the ever-expanding cloud computing landscape. This development comes at a time when hyperscale cloud providers (HCPs) are reevaluating their infrastructure models, paving the way for a surge in colocation opportunities. As the UK officially exits the European Union post-Brexit, the landscape of colocation services presents both challenges and golden prospects for businesses seeking to establish a strategic presence.

Advantages of Colocation Services

The UK’s strategic location, despite Brexit-related uncertainties, emerges as a focal point for business expansion to Europe. Google’s massive investment signifies not only the growing demand for internet services within the UK but also positions the country as an ideal hub for colocation services serving the broader European market. The colocation model offers advantages such as faster time-to-market and a shift away from substantial capital expenditures, aligning with the evolving strategies of HCPs.

Strategic Considerations for Colocation Providers

As HCPs seek external partnerships and colocation services, providers in the UK, especially in Tier 2 cities like London, find themselves at the center of a strategic opportunity. The demand for hyperscale colocation services in these regions is driving the need for efficient colocation facilities, reshaping infrastructure business models. However, the challenges arising from Brexit-related uncertainties and intricate regulatory landscapes necessitate diligent navigation for businesses operating in the data center sector.

Regulations, Compliance, and Data Sovereignty

The UK’s departure from the EU introduces uncertainties related to regulatory changes, impacting how businesses conduct cross-border services and transactions. Compliance with data protection standards, including the General Data Protection Regulation (GDPR) and its UK counterpart, remains crucial for colocation providers to build trust with clients and adhere to legal requirements governing sensitive data handling. In this complex landscape, the consideration of data sovereignty becomes paramount. Businesses must navigate not only the evolving regulatory frameworks but also ensure that their data storage and processing practices align with data sovereignty requirements. Addressing data sovereignty concerns is integral to strategic decision-making, ensuring that businesses meet the diverse and stringent regulatory expectations when offering colocation services in the UK or broader Europe.

Golden Opportunities for Data Center Providers

Amidst the shifting dynamics of the data center landscape, data center providers find themselves presented with golden opportunities in Europe and the UK. The expanding market and the strategic shift of HCPs towards colocation models create favorable conditions for providers to establish themselves as key players. The demand for colocation services is at an all-time high, offering providers a chance to capitalize on the growing need for reliable and efficient data storage and processing capabilities.

Expanding to Europe: Colocation in UK or Europe?

The UK boasts a mature and sophisticated market with a strong technology infrastructure, making it an ideal choice for businesses seeking a reliable and well-established environment. Furthermore, proximity to major financial and technological hubs, particularly in London, provides strategic advantages for companies aiming to connect with global markets. The UK’s recognized excellence in technology and adherence to robust regulatory standards also make it an appealing choice for businesses valuing regulatory stability. Despite the uncertainties introduced by Brexit, the UK’s business-friendly policies and long-standing reputation as a technology hub position it as a strong contender for companies prioritizing stability and a mature market presence.

🏢 OUR DC CO-LOCATION

Conclusion

The UK’s appeal for business expansion in the post-Brexit era is evident, highlighted by Google’s substantial investment. Colocation providers navigating Brexit complexities, regulatory changes, and market dynamics must prioritize compliance and strategic alignment with hyperscale cloud providers’ evolving needs. This juncture presents golden opportunities for business expansion to Europe and the UK, emphasizing the crucial moment to establish a robust foothold in the dynamic realm of data storage and processing.

Source:

https://thesun.my/business/google-to-invest-us-1-billion-in-uk-data-centre-MD12004448

https://www.adlittle.com/en/insights/viewpoints/cloud-expansion-europe-substantial-opportunity-low-risk-data-centers

https://press.aboutamazon.com/2023/10/amazon-web-services-to-launch-aws-european-sovereign-cloud

Related Articles:

Navigating EU Data Protection Regulations in Cloud Computing

How Cloud Migration Excellence and Modernization Drive Business Growth

Cloud Providers Set to Transform Government Solutions with Sovereignty-Focused Offerings

This article is re-published from: https://www.scloud.sg/resource/entering-europe-data-center-colocation-in-post-brexit-uk/

[515engine]

https://iueds.com/technology/cloud-or-data-center/

[govindhtech]

Tech Breakdown: What Is a SuperNIC? Get the Inside Scoop!

The most recent development in the rapidly evolving digital realm is generative AI. A relatively new phrase, SuperNIC, is one of the revolutionary inventions that makes it feasible.

Describe a SuperNIC

On order to accelerate hyperscale AI workloads on Ethernet-based clouds, a new family of network accelerators called SuperNIC was created. With remote direct memory access (RDMA) over converged Ethernet (RoCE) technology, it offers extremely rapid network connectivity for GPU-to-GPU communication, with throughputs of up to 400Gb/s.

SuperNICs incorporate the following special qualities:

Ensuring that data packets are received and processed in the same sequence as they were originally delivered through high-speed packet reordering. This keeps the data flow’s sequential integrity intact.

In order to regulate and prevent congestion in AI networks, advanced congestion management uses network-aware algorithms and real-time telemetry data.

In AI cloud data centers, programmable computation on the input/output (I/O) channel facilitates network architecture adaptation and extension.

Low-profile, power-efficient architecture that effectively handles AI workloads under power-constrained budgets.

Optimization for full-stack AI, encompassing system software, communication libraries, application frameworks, networking, computing, and storage.

Recently, NVIDIA revealed the first SuperNIC in the world designed specifically for AI computing, built on the BlueField-3 networking architecture. It is a component of the NVIDIA Spectrum-X platform, which allows for smooth integration with the Ethernet switch system Spectrum-4.

The NVIDIA Spectrum-4 switch system and BlueField-3 SuperNIC work together to provide an accelerated computing fabric that is optimized for AI applications. Spectrum-X outperforms conventional Ethernet settings by continuously delivering high levels of network efficiency.

Yael Shenhav, vice president of DPU and NIC products at NVIDIA, stated, “In a world where AI is driving the next wave of technological innovation, the BlueField-3 SuperNIC is a vital cog in the machinery.” “SuperNICs are essential components for enabling the future of AI computing because they guarantee that your AI workloads are executed with efficiency and speed.”

The Changing Environment of Networking and AI

Large language models and generative AI are causing a seismic change in the area of artificial intelligence. These potent technologies have opened up new avenues and made it possible for computers to perform new functions.

GPU-accelerated computing plays a critical role in the development of AI by processing massive amounts of data, training huge AI models, and enabling real-time inference. While this increased computing capacity has created opportunities, Ethernet cloud networks have also been put to the test.

The internet’s foundational technology, traditional Ethernet, was designed to link loosely connected applications and provide wide compatibility. The complex computational requirements of contemporary AI workloads, which include quickly transferring large amounts of data, closely linked parallel processing, and unusual communication patterns all of which call for optimal network connectivity were not intended for it.

Basic network interface cards (NICs) were created with interoperability, universal data transfer, and general-purpose computing in mind. They were never intended to handle the special difficulties brought on by the high processing demands of AI applications.

The necessary characteristics and capabilities for effective data transmission, low latency, and the predictable performance required for AI activities are absent from standard NICs. In contrast, SuperNICs are designed specifically for contemporary AI workloads.

Benefits of SuperNICs in AI Computing Environments

Data processing units (DPUs) are capable of high throughput, low latency network connectivity, and many other sophisticated characteristics. DPUs have become more and more common in the field of cloud computing since its launch in 2020, mostly because of their ability to separate, speed up, and offload computation from data center hardware.

SuperNICs and DPUs both have many characteristics and functions in common, however SuperNICs are specially designed to speed up networks for artificial intelligence.

The performance of distributed AI training and inference communication flows is highly dependent on the availability of network capacity. Known for their elegant designs, SuperNICs scale better than DPUs and may provide an astounding 400Gb/s of network bandwidth per GPU.

When GPUs and SuperNICs are matched 1:1 in a system, AI workload efficiency may be greatly increased, resulting in higher productivity and better business outcomes.

SuperNICs are only intended to speed up networking for cloud computing with artificial intelligence. As a result, it uses less processing power than a DPU, which needs a lot of processing power to offload programs from a host CPU.

Less power usage results from the decreased computation needs, which is especially important in systems with up to eight SuperNICs.

One of the SuperNIC’s other unique selling points is its specialized AI networking capabilities. It provides optimal congestion control, adaptive routing, and out-of-order packet handling when tightly connected with an AI-optimized NVIDIA Spectrum-4 switch. Ethernet AI cloud settings are accelerated by these cutting-edge technologies.

Transforming cloud computing with AI

The NVIDIA BlueField-3 SuperNIC is essential for AI-ready infrastructure because of its many advantages.

Maximum efficiency for AI workloads: The BlueField-3 SuperNIC is perfect for AI workloads since it was designed specifically for network-intensive, massively parallel computing. It guarantees bottleneck-free, efficient operation of AI activities.

Performance that is consistent and predictable: The BlueField-3 SuperNIC makes sure that each job and tenant in multi-tenant data centers, where many jobs are executed concurrently, is isolated, predictable, and unaffected by other network operations.

Secure multi-tenant cloud infrastructure: Data centers that handle sensitive data place a high premium on security. High security levels are maintained by the BlueField-3 SuperNIC, allowing different tenants to cohabit with separate data and processing.

Broad network infrastructure: The BlueField-3 SuperNIC is very versatile and can be easily adjusted to meet a wide range of different network infrastructure requirements.

Wide compatibility with server manufacturers: The BlueField-3 SuperNIC integrates easily with the majority of enterprise-class servers without using an excessive amount of power in data centers.

[peterbordes]

Aramco Digital, the digital and technology subsidiary of @aramco and @GroqInc a leader in #AI inference and creator of the Language Processing Unit (LPU), announced their partnership to establish the world’s largest inferencing data center in Saudi Arabia.

[harshitasoni]

Connecting the Dots: Cloud Service Providers in the US

Unlock the Future with the US Data Center Market! Delve into the dynamic US Data Center Industry, where innovation meets infrastructure. Discover the leading players shaping the market, emerging companies ready to disrupt, and top Cloud Computing Companies providing cutting-edge solutions. Explore the insatiable demand for new data centers, despite the challenges. Uncover the secrets of Cloud Service Providers in the US as they power the digital revolution. In this sector, opportunities abound, and the landscape is ever-evolving. Stay ahead of the game and be part of the data-driven transformation in the US Data Center Sector.