#cloud computing consulting

[pritivora26]

The future of cloud computing in 2024 holds a lot of exciting possibilities. With the rapid advancement of technology and the increasing demand for digital transformation, cloud computing is expected to continue its growth and evolution. This ranking gathers 10 top cloud consultants worldwide. Companies are ranked according to which one can produce software in the most agile way and have the quickest impact on the project because this is the most crucial consideration when picking a business. Read more.

[techygrowth]

Cloud computing consulting companies offer a variety of services like, Cloud migration, cloud strategy, cloud security, IT consulting and cloud management. Before selecting the best company look for, experience, testimonials of clients, Offering multiple services and ensure they provide support.

[tekskills-blog]

Cloud consulting company | Cloud computing Services | cloud migration services

Cloud transformation, migration, and storage services are among the cloud computing services provided by Tek Skills, a cloud consulting business. Services Based in the Cloud

[coffeebeansconsulting]

What is Serverless Computing?

Serverless computing is a cloud computing model where the cloud provider manages the infrastructure and automatically provisions resources as needed to execute code. This means that developers don’t have to worry about managing servers, scaling, or infrastructure maintenance. Instead, they can focus on writing code and building applications. Serverless computing is often used for building event-driven applications or microservices, where functions are triggered by events and execute specific tasks.

How Serverless Computing Works

In serverless computing, applications are broken down into small, independent functions that are triggered by specific events. These functions are stateless, meaning they don’t retain information between executions. When an event occurs, the cloud provider automatically provisions the necessary resources and executes the function. Once the function is complete, the resources are de-provisioned, making serverless computing highly scalable and cost-efficient.

Serverless Computing Architecture

The architecture of serverless computing typically involves four components: the client, the API Gateway, the compute service, and the data store. The client sends requests to the API Gateway, which acts as a front-end to the compute service. The compute service executes the functions in response to events and may interact with the data store to retrieve or store data. The API Gateway then returns the results to the client.

Benefits of Serverless Computing

Serverless computing offers several benefits over traditional server-based computing, including:

Reduced costs: Serverless computing allows organizations to pay only for the resources they use, rather than paying for dedicated servers or infrastructure.

Improved scalability: Serverless computing can automatically scale up or down depending on demand, making it highly scalable and efficient.

Reduced maintenance: Since the cloud provider manages the infrastructure, organizations don’t need to worry about maintaining servers or infrastructure.

Faster time to market: Serverless computing allows developers to focus on writing code and building applications, reducing the time to market new products and services.

Drawbacks of Serverless Computing

While serverless computing has several benefits, it also has some drawbacks, including:

Limited control: Since the cloud provider manages the infrastructure, developers have limited control over the environment and resources.

Cold start times: When a function is executed for the first time, it may take longer to start up, leading to slower response times.

Vendor lock-in: Organizations may be tied to a specific cloud provider, making it difficult to switch providers or migrate to a different environment.

Some facts about serverless computing

Serverless computing is often referred to as Functions-as-a-Service (FaaS) because it allows developers to write and deploy individual functions rather than entire applications.

Serverless computing is often used in microservices architectures, where applications are broken down into smaller, independent components that can be developed, deployed, and scaled independently.

Serverless computing can result in significant cost savings for organizations because they only pay for the resources they use. This can be especially beneficial for applications with unpredictable traffic patterns or occasional bursts of computing power.

One of the biggest drawbacks of serverless computing is the “cold start” problem, where a function may take several seconds to start up if it hasn’t been used recently. However, this problem can be mitigated through various optimization techniques.

Serverless computing is often used in event-driven architectures, where functions are triggered by specific events such as user interactions, changes to a database, or changes to a file system. This can make it easier to build highly scalable and efficient applications.

Now, let’s explore some other serverless computing frameworks that can be used in addition to Google Cloud Functions.

AWS Lambda: AWS Lambda is a serverless compute service from Amazon Web Services (AWS). It allows developers to run code in response to events without worrying about managing servers or infrastructure.

Microsoft Azure Functions: Microsoft Azure Functions is a serverless compute service from Microsoft Azure. It allows developers to run code in response to events and supports a wide range of programming languages.

IBM Cloud Functions: IBM Cloud Functions is a serverless compute service from IBM Cloud. It allows developers to run code in response to events and supports a wide range of programming languages.

OpenFaaS: OpenFaaS is an open-source serverless framework that allows developers to run functions on any cloud or on-premises infrastructure.

Apache OpenWhisk: Apache OpenWhisk is an open-source serverless platform that allows developers to run functions in response to events. It supports a wide range of programming languages and can be deployed on any cloud or on-premises infrastructure.

Kubeless: Kubeless is a Kubernetes-native serverless framework that allows developers to run functions on Kubernetes clusters. It supports a wide range of programming languages and can be deployed on any Kubernetes cluster.

IronFunctions: IronFunctions is an open-source serverless platform that allows developers to run functions on any cloud or on-premises infrastructure. It supports a wide range of programming languages and can be deployed on any container orchestrator.

These serverless computing frameworks offer developers a range of options for building and deploying serverless applications. Each framework has its own strengths and weaknesses, so developers should choose the one that best fits their needs.

Real-time examples

Coca-Cola: Coca-Cola uses serverless computing to power its Freestyle soda machines, which allow customers to mix and match different soda flavors. The machines use AWS Lambda functions to process customer requests and make recommendations based on their preferences.

iRobot: iRobot uses serverless computing to power its Roomba robot vacuums, which use computer vision and machine learning to navigate homes and clean floors. The Roomba vacuums use AWS Lambda functions to process data from their sensors and decide where to go next.

Capital One: Capital One uses serverless computing to power its mobile banking app, which allows customers to manage their accounts, transfer money, and pay bills. The app uses AWS Lambda functions to process requests and deliver real-time information to users.

Fender: Fender uses serverless computing to power its Fender Play platform, which provides online guitar lessons to users around the world. The platform uses AWS Lambda functions to process user data and generate personalized lesson plans.

Netflix: Netflix uses serverless computing to power its video encoding and transcoding workflows, which are used to prepare video content for streaming on various devices. The workflows use AWS Lambda functions to process video files and convert them into the appropriate format for each device.

Conclusion

Serverless computing is a powerful and efficient solution for building and deploying applications. It offers several benefits, including reduced costs, improved scalability, reduced maintenance, and faster time to market. However, it also has some drawbacks, including limited control, cold start times, and vendor lock-in. Despite these drawbacks, serverless computing will likely become an increasingly popular solution for building event-driven applications and microservices.

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[cloudatlasinc]

Accelerating transformation with SAP on Azure

Microsoft continues to expand its presence in the cloud by building more data centers globally, with over 61 Azure regions in 140 countries. They are expanding their reach and capabilities to meet all the customer needs. The transition from a cloudless domain like DRDC to the entire cloud platform is possible within no time, and a serverless future awaits. Microsoft gives the platform to build and innovate at a rapid speed. Microsoft is enhancing new capabilities to meet cloud services' demands and needs, from IaaS to PaaS Data, AI, ML, and IoT. There are over 600 services available on Azure with a cloud adoption framework and enterprise-scale landing zone. Many companies look at Microsoft Azure security compliance as a significant migration driver. Microsoft Azure has an extensive list of compliance certifications across the globe. The Microsoft services have several beneficial characteristics; capabilities are broad, deep, and suited to any industry, along with a global network of skilled professionals and partners. Expertise in the Microsoft portfolio includes both technology integration and digital transformation. Accountability for the long term, addressing complex challenges while mitigating risk. Flexibility to engage in the way that works for you with the global reach to satisfy the target business audience.

SAP and Microsoft Azure

SAP and Microsoft bring together the power of industry-specific best practices, reference architectures, and professional services and support to simplify and safeguard your migration to SAP in the cloud and help manage the ongoing business operations now and in the future. SAP and Microsoft have collaborated to design and deliver a seamless, optimized experience to help manage migration and business operations as you move from on-premises editions of SAP solutions to SAP S/4 HANA on Microsoft Azure. It reduces complexity, minimizes costs, and supports end-to-end SAP migration and operations strategy, platform, and services. As a result, one can safeguard the cloud migration with out-of-box functionality and industry-specific best practices while immaculately handling the risk and optimizing the IT environment. Furthermore, the migration assimilates best-in-class technologies from SAP and Microsoft, packed with a unified business cloud platform. 

SAP Deployment Options on Azure

SAP system is deployed on-premises or in Azure. One can deploy different systems into different landscapes either on Azure or on-premises. SAP HANA on Azure large instances intend to host the SAP application layer of SAP systems in Virtual Machines and the related SAP HANA instance on the unit in the 'SAP HANA Azure Large Instance Stamp.' 'A Large Instance Stamp' is a hardware infrastructure stack that is SAP HANA TDI certified and dedicated to running SAP HANA instances within Azure. 'SAP HANA Large Instances' is the official name for the solution in Azure to run HANA instances on SAP HANA TDI certified hardware that gets deployed in ‘Large Instance Stamps’ in different Azure regions. SAP or HANA Large Instances or HLI are physical servers meaning bare metal servers. HLI does not reside in the same data center as Azure services but is in close proximity and connected through high throughput links to satisfy SAP HANA network latency requirements. HLI comes in two flavors- Type 1 and 2. IaaS can install SAP HANA on a virtual machine running on Azure. Running SAP HANA on IaaS supports more Linux versions than HLI. For example, you can install SAP Netweaver on Windows and Linux IaaS Virtual Machines on Azure. SAP HANA can only run on RedHat and SUSE, while NetWeaver can run on windows SQL and Linux.

Azure Virtual Network

Azure Virtual Network or VNET is a core foundation of the infrastructure implementation on Azure. The VNET can be a communication boundary for those resources that need to communicate. You can have multiple VNETs in your subscription. If they weren't connected, we could call them Pierre in Azure wall; there will be no traffic flow in between. They can also share the same IP range. Understanding the requirements and proper setup is essential as changing them later, especially with the running production workloads, could cause downtime. When you provision a VNET, The private blocks must allocate address space. If you plan to connect multiple VNETs, you cannot have an overlapping address space. The IP range should not clash or overlap with the IP addressing in Azure while connecting on-premise to Azure via express route or site-site VPN. Configuring VNET to the IP address space becomes a DHP service. You can configure VNET with the DNS server's IP addresses to resolve services on-premise.VNETS can be split into different subnets and communicate freely with each other. Network security groups or NSGs are the control planes we use to filter traffic. NSGs are stateful but simple firewall rules based on the source and destination IP and ports.

 Azure Virtual Gateway

 For extensive connectivity, you must create a virtual gateway subnet. When you create a virtual gateway, you will get prompted for two options: VPN or Express Route Gateway; with VPN, you cannot connect to the Express Route Circuit. If you choose the Express Route Virtual Gateway, you can combine both.

 There are two types of VPN;

1) The point-to-site VPN is used for testing and gives the lowest throughput.

2) The site-site VPN connection can offer better benefits by bridging networks.

This VPN offers zero support for SLA and uses this connection as a backup for the recommended connection on Azure, called the express route. Express route is a dedicated circuit using hardware installed on your data center, with a constant link to ‘Microsoft Azure Edge’ devices. Express route is inevitable for maintaining the communication between application VNET running in Azure and on-premise systems to HLI servers. The express route is safer and more resilient than VPN as it provides a connection through a single circuit and facilitates second redundancy; this helps route traffic between SAP application servers inside Azure and enables low latency. Furthermore, the fast path allows routine traffic between SAP application servers inside Azure VNET and HLI through an optimized route that bypasses the virtual network gateway and directly hops through edge routers to HLA servers. Therefore, an ultra-performance express route gateway must have a Fast Path feature.

SAP HANA Architecture (VM)

This design gets centered on the SAP HANA backend on the Linux Suse or RedHat distributions. Even though the Linux OS implementation is the same, the vendor licensing differs. It incorporates always-on replication and utilizes synchronous and asynchronous replication to meet the HANA DB requirements. We have also introduced NetApp file share for DFS volumes used by each SAP component using Azure site recovery and building a DR plan for App ASCs and the web dispatches servers. Azure Active directory is used in synchronization with on-premises active directory, as SAP application user authenticates from on-premises to SAP landscape on Azure with Single Sign-On credentials. Azure high-speed express route gateway securely connects on-premises networks to Azure virtual machines and other resources. The request flows into highly available SAP central, SAP ABAP services ASCS and through SAP application servers running on Azure virtual machines. The on-demand request moves from the SAP App server to the SAP HANA server running on a high-performance Azure VM. Primary active and secondary standby servers run on SAP-certified virtual machines with a cluster availability of 99.95 at the OS level. Data replication is handled through HSR in synchronous mode from primary to secondary enabling zero recovery point objective. SAP HANA data is replicated through a disaster recovery VM in another Azure region through the Azure high-speed backbone network and using HSR in asynchronous mode. The disaster recovery VM can be smaller than the production VM to save costs.

SAP systems are network sensitive, so the network system must factor the design decisions into segmenting the VNETs and NSGs. To ensure network reliability, we must use low latency cross-connections with sufficient bandwidth and no packet loss. SAP is very sensitive to these metrics, and you could experience significant issues if traffic suffers latency or packet loss between the application and the SAP system. We can use proximity placement groups called PGS to force the grouping of different VM types into a single Azure data center to optimize the network latency between the different VM types to the best possible.

 Security Considerations

 Security is another core pillar of any design. Role-based Access control (RBAC) gets accessed through the Azure management bay. RBAC is backed up through AD using cloud-only synchronized identities. Azure AD can back up the RBAC through cloud-only or synchronized identities. RBAC will tie in those cloud or sync identities to Azure tenants, where you can give personal access to Azure for operational purposes. Network security groups are vital for securing the network traffic both within and outside the network environment. The NSGs are stateful firewalls that preserve session information. You can have a single NSG per subnet, and multiple subnets can share the same energy. Application security group or ASG handles functions such as web servers, application servers, or backend database servers combined to perform a meaningful service. Resource encryption brings the best of security with encryption in transit. SAP recommends using encryption at rest, so for the Azure storage account, we can use storage service encryption, which would use either Microsoft or customer-managed keys to manage encryption. Azure storage also adds encryption in transit, with SSL using HTTPS traffic. You can use Azure Disk Encryption (ADE) for OS and DBA encryption for SQL.

Migration of SAP Workloads to Azure

The most critical part of the migration is understanding what you are planning to migrate and accounting for dependencies, limitations, or even blockers that might stop your migration. Following an appropriate inventory process will ensure that your migration completes successfully. You can use in-hand tools to understand the current SAP landscape in the migration scope. For example, looking at your service now or CMDB catalog might reveal some of the data that expresses your SAP system. Then take that information to start drawing out your sizing in Azure. It is essential to ensure that we have a record of the current environment configuration, such as the number of servers and their names, server roles, and data about CPU and memory. It is essential to pick up the disk sizes, configuration, and throughput to ensure that your design delivers a better experience in Azure. It is also necessary to understand database replication and throughput requirements around replicas. When performing a migration, the sizing for large HANA instances is no different from sizing for HANA in general. For existing and deployment systems you want to move from other RDBMS to HANA, SAP provides several reports that run on your existing SAP systems. If migrating the database to HANA, these reports need to check the data and calculate memory requirements for the HANA instances.

When evaluating high availability and disaster recovery requirements, it is essential to consider the implications of choosing between two-tier and three-tier architectures. To avoid network contention in a two-tier arrangement, install database and Netweaver components on the same Azure VM. The database and application components get installed in three-tier configurations on separate Azure Virtual Machines. This choice has other implications regarding sizing since two-tier, and three-tier SAP ratings for a given VM differs. The high availability option is not mandatory for the SAP application servers.

You can achieve high availability by employing redundancy. To implement it, you can install individual application servers on separate Azure VMs. For example, you can achieve high availability for ASCS and SCS servers running on windows using windows failover clustering with SIOS data keeper. We can also achieve high availability with Linux clustering using Azure NetApp files. For DBMS servers, you should use DB replication technology using redundant nodes. Azure offers high availability through redundancy of its infrastructure and capabilities, such as Azure VM restarts, which play an essential role in a single VM deployment. In addition, Azure offers different SLAs depending on your configuration. For example, SAP landscapes organize SABC servers into different tiers; there are three diverse landscapes: deployment, quality assurance, and production.

Migration Strategies:- SAP landscapes to Azure

 Enterprises have SAP systems for business functions like Enterprise Resource Planning(ERP), global trade, business intelligence(BI), and others. Within those systems, there are different environments like sandbox developments, tests, and production. Each horizontal row is an environment, and each vertical dimension is the SAP system for a business function. The layers at the bottom are lower-risk environments and are less critical. Those towards the top are in high-risk environments and are more critical. As you move up the stack, there is more risk in the migration process. Production is the more critical environment. The use of test environments for business continuity is of concern. The systems at the bottom are smaller and have fewer computing resources, lower availability, size requirements, and less throughput. They have the same amount of storage as the production database with a horizontal migration strategy. To gain experience with production systems on Azure, you can use a vertical approach with low-risk factors in parallel to the horizontal design.

 Horizontal Migration Strategy

 To limit risk, start with low-impact sandboxes or training systems. Then, if something goes wrong, there is little danger associated with users or mission-critical business functions. After gaining experience in hosting, running, and administering SAP systems in Azure, apply to the next layer of systems up the stack. Then, estimate costs, limiting expenditures, performance, and optimization potential for each layer and adjust if needed.

Vertical Migration Strategy

The cost must be on guard along with legal requirements. Move systems from the sandbox to production with the lowest risk. First, the governance, risk, compliance system, and the object Event Repository gets driven towards production. Then the higher risk elements like BI and DRP. When you have a new system, it's better to start in Azure default mode rather than putting it on-premises and moving it later. The last system you move is the highest risk, mission-critical system, usually the ERP production system. Having the most performance virtual machines, SQL, and extensive storage would be best. Consider the earliest migration of standalone systems. If you have different SAP systems, always look for upstream and downstream dependencies from one SAP system to another.

Journey to SAP on Azure

Consider two main factors for the migration of SAP HANA to the cloud. The first is the end-of-life first-generation HANA appliance, causing customers to reevaluate their platform. The second is the desire to take advantage of the early value proposition of SAP business warehouse BW on HANA in a flexible DDA model over traditional databases and later BW for HANA. As a result, numerous initial migrations of SAP HANA to Microsoft Azure have focused on SAP BW to take advantage of SAP HANA's in-memory capability for the BW workloads. In addition, using the SAP database migration option DMO with the System Migration option of SUM facilitates single-step migration from the source system on-premises to the target system residing in Azure. As a result, it minimizes the overall downtime. In general, when initiating a project to deploy SAP workloads to Azure, you should divide it into the following phases. Project preparation and planning, pilot, non-production, production preparation, go-live, and post-production.

Use Cases for SAP Implementation in Microsoft Azure

 Use  cases

How  does Microsoft Azure help?

How  do organizations benefit?

Deliver  automated disaster recovery with low RPO and RTO

Azure  recovery services replicate on-premises virtual machines to Azure and  orchestrate failover and failback

RPO  and RTO get reduced, and the cost of ownership of disaster recovery (DR)  infrastructure diminishes. While the DR systems replicate, the only cost  incurred is storage

Make  timely changes to SAP workloads by development teams

200-300  times faster infrastructure provisioning and rollout compared to on-premises,  more rapid changes by SAP application teams

Increased  agility and the ability to provision instances within 20 minutes

Fund  intermittently used development and test infrastructure for SAP workloads

Supports  the potential to stop development and test systems at the end of business day

Savings  as much as 40-75 percent in hosting costs by exercising the ability to control  instances when not in use

Increase  data center capacity to serve updated SAP project requests

Frees  on-premises data center capacity by moving development and test for SAP  workloads to Microsoft Azure without upfront investments

Flexibility  to shift from capital to operational expenditures

Provide  consistent training environments based on templates

Ability  to store and use pre-defined images of the training environment for updated  virtual machines

Cost  savings by provisioning only the instances needed for training and then  deleting them when the event is complete

Archive  historical systems for auditing and governance

Supports  migration of physical machines to virtual machines that get activated when  needed

Savings  of as much as 60 percent due to cheaper storage and the ability to quickly  spin up systems based on need.

  References

n.d. Microsoft Azure: Cloud Computing Services. Accessed June 13, 2022. http://azure.microsoft.com.

n.d. All Blog Posts. Accessed June 13, 2022. https://blogs.sap.com.

n.d. Cloud4C: Managed Cloud Services for Enterprises. Accessed June 13, 2022. https://www.cloud4c.com.

n.d. NetApp Cloud Solutions | Optimized Storage In Any Cloud. Accessed June 13, 2022. http://cloud.netapp.com.

[riya2510]

5G System Integration Market Report: Insights, Trends, and Forecast 2022–2030

5G System Integration Market Report – Straits Research

Market Overview

The global 5G System Integration Market was valued at USD 7.76 Billion in 2021 and is projected to grow from USD XX Billion in 2022 to USD 67.16 Billion by 2030, growing at a robust CAGR of 27.1% during the forecast period (2022–2030). The market encompasses the integration of advanced technologies, including 5G networks, IoT devices, cloud computing, and edge computing, into existing infrastructures to enable high-speed communication and seamless connectivity. 5G system integration is essential for businesses across various industries to unlock the full potential of 5G technology, providing faster speeds, lower latency, and more reliable connections. With the growing demand for high-speed, ultra-reliable, and low-latency communications, the 5G system integration market is expected to experience significant growth.

Request a Free Sample (Free Executive Summary at Full Report Starting from USD 1850): https://straitsresearch.com/report/5g-system-integration-market/request-sample

5G System Integration Market Categorization

The 5G System Integration market is segmented in multiple ways, each targeting specific services, industries, and applications that benefit from 5G technology.

1. Services Outlook:

The services provided in 5G system integration can be divided into three main categories:

Consulting: Consulting services are crucial for businesses looking to adopt and integrate 5G technology into their operations. Consultants offer strategic advice on deployment strategies, cost management, and technology selection.

Infrastructure Integration: This involves the integration of 5G infrastructure, such as base stations, towers, and small cells, with existing network systems. This integration ensures the seamless functioning of 5G networks alongside legacy systems.

Application Integration: This service focuses on integrating 5G technology with applications across different sectors, ensuring that businesses can optimize their operations and communication systems by leveraging high-speed data transmission and low latency.

2. Vertical Outlook:

The market for 5G system integration is further segmented by industry verticals, as different sectors adopt 5G technology to enhance their operations:

Manufacturing: The adoption of 5G in manufacturing enables smart factories with automation, robotics, and real-time analytics, improving productivity and efficiency.

Energy & Utility: 5G technology enables real-time monitoring of energy grids, smart meters, and power distribution systems, improving operational efficiency and minimizing downtime.

Media & Entertainment: 5G enables high-quality streaming, virtual reality (VR), and augmented reality (AR) experiences, transforming the entertainment industry and providing new opportunities for content creators.

IT & Telecom: Telecom companies are leveraging 5G technology to upgrade their networks and provide high-speed internet services to customers, while the IT sector uses 5G to support large-scale cloud computing and data processing.

Transportation & Logistics: 5G supports the growth of autonomous vehicles, smart logistics, and real-time tracking, improving operational efficiency and reducing costs in the transportation and logistics industry.

BFSI (Banking, Financial Services, and Insurance): In the BFSI sector, 5G integration allows for secure, real-time transactions, mobile banking services, and enhanced customer experiences.

Healthcare: 5G’s low latency enables telemedicine, remote surgeries, and patient monitoring systems, helping healthcare providers improve patient care and operational efficiency.

Retail: Retailers use 5G technology to enhance customer experiences through augmented reality, personalized shopping experiences, and real-time inventory management.

Others: This category includes sectors such as education, government, and agriculture that are also adopting 5G technology for improved communication, data analysis, and operational efficiency.

3. Application Outlook:

The diverse applications of 5G technology span several fields, each providing unique benefits for different industries:

Smart City: 5G enables the development of smart city applications such as intelligent traffic systems, smart meters, and public safety systems, improving urban living.

Collaborative Robots / Cloud Robots: The integration of 5G with robotics allows for the deployment of collaborative robots in manufacturing and other industries, improving automation and efficiency.

Industrial Sensors: 5G facilitates the use of industrial sensors for real-time monitoring and data collection, enabling predictive maintenance and improving operations in industries like manufacturing and energy.

Logistics & Inventory Monitoring: With 5G, companies can track inventory in real-time, improve logistics efficiency, and enable faster delivery times, reducing operational costs.

Wireless Industry Camera: 5G enables high-definition video streaming from cameras used in industries like surveillance, security, and media, ensuring smooth, high-quality streaming.

Drone: Drones equipped with 5G can transmit high-definition video and data in real time, enabling uses in agriculture, delivery, and infrastructure inspection.

Home and Office Broadband: 5G enables high-speed internet access for both residential and commercial properties, enhancing broadband services for customers.

Vehicle-to-everything (V2X): V2X technology powered by 5G allows for communication between vehicles, infrastructure, and pedestrians, enabling safer, more efficient transportation systems.

Gaming and Mobile Media: 5G enhances the gaming experience by providing low-latency, high-speed connections for mobile games and media streaming.

Remote Patient & Diagnosis Management: 5G enables remote healthcare services, allowing for faster diagnosis, patient monitoring, and telemedicine applications.

Intelligent Power Distribution Systems: 5G enhances the management of power grids by providing real-time data, improving grid stability and reducing energy losses.

P2P Transfers / mCommerce: 5G facilitates faster peer-to-peer (P2P) payments and mobile commerce, enhancing the customer experience in the financial services industry.

4. Geographic Overview:

The 5G System Integration Market is witnessing dynamic growth across the globe. Key regions and their dominant countries are:

North America: The U.S. leads the North American market with the largest adoption of 5G technology, driven by the presence of major telecom players, technological advancements, and high investments in 5G infrastructure.

Europe: The European market is expanding, with the U.K., Germany, and France playing a significant role in adopting 5G systems, especially in manufacturing, healthcare, and transportation.

Asia Pacific: Asia Pacific is expected to witness the highest growth during the forecast period, with countries like China, Japan, and South Korea leading the 5G adoption race. The region’s strong focus on technological innovation and infrastructure development fuels market growth.

Latin America: Latin America is catching up with other regions in adopting 5G technology, particularly in countries like Brazil and Mexico. These countries are focusing on 5G infrastructure deployment and increasing connectivity in urban and rural areas.Market Segmentation with Insights-Driven Strategy Guide: https://straitsresearch.com/report/5g-system-integration-market/segmentation

Top Players in the 5G System Integration Market

The 5G System Integration Market features several industry leaders who are pivotal in the growth and innovation of 5G technology:

Accenture Inc.

Cisco Systems, Inc.

Huawei Technologies Co., Ltd.

Infosys Limited

Tata Consultancy Services Limited

Wipro Limited

Radisys Corporation

IBM Corporation

HPE (Hewlett Packard Enterprise)

Oracle Corporation

HCL Technologies Limited

ALTRAN

AMDOCS

CA Technologies

Hansen Technologies

Samsung Electronics Co., Ltd.

Ericsson

Keysight Technologies

ECI Telecom

These companies provide integrated solutions and services for the successful implementation and deployment of 5G systems, contributing to the rapid growth of the 5G ecosystem.

Key Unit Economics for Businesses and Startups

For businesses and startups, understanding the unit economics of 5G system integration is essential. Key metrics include:

Cost of Integration: The total investment required for adopting 5G infrastructure, including hardware, software, and consulting services.

Return on Investment (ROI): The anticipated financial returns from deploying 5G technology, which could include cost savings, enhanced operational efficiency, and new revenue streams.

Customer Acquisition and Retention: 5G enhances customer experiences, leading to higher retention rates and attracting new customers through innovative services.

Startups looking to integrate 5G technology should focus on scalable solutions and consider cloud-based integration services to reduce upfront costs.

Buy Full Report (Exclusive Insights with In-Depth Data Supplement): https://straitsresearch.com/buy-now/5g-system-integration-market

5G System Integration Market Operational Factors

Several operational factors influence the 5G system integration market, including:

Technology Advancements: Continuous developments in 5G, IoT, and edge computing technologies are driving the market forward.

Regulatory Challenges: Countries are implementing policies and regulations related to spectrum allocation, network sharing, and data security, affecting 5G adoption.

Deployment Costs: The high cost of infrastructure and integration services remains a barrier for some businesses, especially startups and small enterprises.Table of Contents for the 5G System Integration Market Report: https://straitsresearch.com/report/5g-system-integration-market/toc

About Straits Research

Straits Research is a leading provider of market research and intelligence services. With a focus on high-quality research, analytics, and advisory, our team offers actionable insights tailored to clients’ strategic needs.

Contact Us Email: sales@straitsresearch.com Address: 825 3rd Avenue, New York, NY, USA, 10022 Tel: UK: +44 203 695 0070, USA: +1 646 905 0080

[cherannetworks]

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[jcmarchi]

AI’s Growing Appetite for Power: Are Data Centers Ready to Keep Up?

New Post has been published on https://thedigitalinsider.com/ais-growing-appetite-for-power-are-data-centers-ready-to-keep-up/

AI’s Growing Appetite for Power: Are Data Centers Ready to Keep Up?

As artificial intelligence (AI) races forward, its energy demands are straining data centers to the breaking point. Next-gen AI technologies like generative AI (genAI) aren’t just transforming industries—their energy consumption is affecting nearly every data server component—from CPUs and memory to accelerators and networking.

GenAI applications, including Microsoft’s Copilot and OpenAI’s ChatGPT, demand more energy than ever before. By 2027, training and maintaining these AI systems alone could consume enough electricity to power a small country for an entire year. And the trend isn’t slowing down: over the last decade, power demands for components such as CPUs, memory, and networking are estimated to grow 160% by 2030, according to a Goldman Sachs report.

The usage of large language models also consumes energy. For instance, a ChatGPT query consumes about ten times a traditional Google search. Given AI’s massive power requirements, can the industry’s rapid advancements be managed sustainably, or will they contribute further to global energy consumption? McKinsey’s recent research shows that around 70% of the surging demand in the data center market is geared toward facilities equipped to handle advanced AI workloads. This shift is fundamentally changing how data centers are built and run, as they adapt to the unique requirements of these high-powered genAI tasks.

“Traditional data centers often operate with aging, energy-intensive equipment and fixed capacities that struggle to adapt to fluctuating workloads, leading to significant energy waste,” Mark Rydon, Chief Strategy Officer and co-founder of distributed cloud compute platform Aethir, told me. “Centralized operations often create an imbalance between resource availability and consumption needs, leading the industry to a critical juncture where advancements could risk undermining environmental goals as AI-driven demands grow.”

Industry leaders are now addressing the challenge head-on, investing in greener designs and energy-efficient architectures for data centers. Efforts range from adopting renewable energy sources to creating more efficient cooling systems that can offset the vast amounts of heat generated by genAI workloads.

Revolutionizing Data Centers for a Greener Future

Lenovo recently introduced the ThinkSystem N1380 Neptune, a leap forward in liquid cooling technology for data centers. The company asserts that the innovation is already enabling organizations to deploy high-powered computing for genAI workloads with significantly lower energy use — up to 40% less power in data centers. N1380 Neptune, harnesses NVIDIA’s latest hardware, including the Blackwell and GB200 GPUs, allowing for the handling of trillion-parameter AI models in a compact setup. Lenovo said that it aims to pave the way for data centers that can operate 100KW+ server racks without the need for dedicated air conditioning.

“We identified a significant requirement from our current consumers: data centers are consuming more power when handling AI workloads due to outdated cooling architectures and traditional structural frameworks,” Robert Daigle, Global Director of AI at Lenovo, told me. “To understand this better, we collaborated with a high-performance computing (HPC) customer to analyze their power consumption, which led us to the conclusion that we could reduce energy usage by 40%.” He added that the company took into account factors such as fan power and the power consumption of cooling units, comparing these with standard systems available through Lenovo’s data center assessment service, to develop the new data center architecture in partnership with Nvidia.

UK-based information technology consulting company AVEVA, said it is utilizing predictive analytics to identify issues with data center compressors, motors, HVAC equipment, air handlers, and more.

“We found that it’s the pre-training of generative AI that consumes massive power,” Jim Chappell, AVEVA’s Head of AI & Advanced Analytics, told me. “Through our predictive AI-driven systems, we aim to find problems well before any SCADA or control system, allowing data center operators to fix equipment problems before they become major issues. In addition, we have a Vision AI Assistant that natively integrates with our control systems to help find other types of anomalies, including temperature hot spots when used with a heat imaging camera.”

Meanwhile, decentralized computing for AI training and development through GPUs over the cloud is emerging as an alternative. Aethir’s Rydon explained that by distributing computational tasks across a broader, more adaptable network, energy use can be optimized, by aligning resource demand with availability—leading to substantial reductions in waste from the outset.

“Instead of relying on large, centralized data centers, our ‘Edge’ infrastructure disperses computational tasks to nodes closer to the data source, which drastically reduces the energy load for data transfer and lowers latency,” said Rydon. “The Aethir Edge network minimizes the need for constant high-power cooling, as workloads are distributed across various environments rather than concentrated in a single location, helping to avoid energy-intensive cooling systems typical of central data centers.”

Likewise, companies including Amazon and Google are experimenting with renewable energy sources to manage rising power needs in their data centers. Microsoft, for instance, is investing heavily in renewable energy sources and efficiency-boosting technologies to reduce its data center’s energy consumption. Google has also taken steps to shift to carbon-free energy and explore cooling systems that minimize power use in data centers. “Nuclear power is likely the fastest path to carbon-free data centers. Major data center providers such as Microsoft, Amazon, and Google are now heavily investing in this type of power generation for the future. With small modular reactors (SMRs), the flexibility and time to production make this an even more viable option to achieve Net Zero,” added AVEVA’s Chappell.

Can AI and Data Center Sustainability Coexist?

Ugur Tigli, CTO at AI infrastructure platform MinIO, says that while we hope for a future where AI can advance without a huge spike in energy consumption, that’s just not realistic in the short term. “Long-term impacts are trickier to predict,” he told me, “but we’ll see a shift in the workforce, and AI will help improve energy consumption across the board.” Tigli believes that as energy efficiency becomes a market priority, we’ll see growth in computing alongside declines in energy use in other sectors, especially as they become more efficient.

He also pointed out that there’s a growing interest among consumers for greener AI solutions. “Imagine an AI application that performs at 90% efficiency but uses only half the power—that’s the kind of innovation that could really take off,” he added. It’s clear that the future of AI isn’t just about innovation—it’s also about data center sustainability. Whether it’s through developing more efficient hardware or smarter ways to use resources, how we manage AI’s energy consumption will greatly influence the design and operation of data centers.

Rydon emphasized the importance of industry-wide initiatives that focus on sustainable data center designs, energy-efficient AI workloads, and open resource sharing. “These are crucial steps towards greener operations,” he said. “Businesses using AI should partner with tech companies to create solutions that reduce environmental impact. By working together, we can steer AI toward a more sustainable future.”

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Top 5 Cloud Computing Companies In India: A Comprehensive Guide

Cloud computing, a rapidly growing trend in the business world, is revolutionizing operations by offering solutions for software applications and data storage computing power. The increasing demand for such services in India is a clear indicator of the industry's rapid growth. As the IT sector expands, more and more cloud computing service providers are entering the market, with many now leading the industry in India.

As cloud consulting services have been rapidly gaining popularity in recent years and are helping businesses extensively, cloud computing is growing very fast, and companies are providing services to IT infrastructure on a large scale. Many service providers in India are at the top of cloud computing, such as AWS (Amazon Web Services), Digital Ocean, Google Cloud, Netgleam, and Microsoft Azure.

Overall, these 5 Top Cloud Computing Service Providers in India provide secure and reliable infrastructure and data analytics capabilities across various industries.

Netgleam Consulting:

Netgleam is India's leading Cloud Consulting Company, which prepares businesses to thrive in the digital age. We provide businesses with reliable services related to cloud computing and help solve challenges. We offer cloud services such as networking, storage, software, and databases through the Internet. Businesses & organizations can avail of some of our services for their cloud project, which includes:

Cloud Support and Maintenance

2. Cloud Migration

3. Cloud Computing Architecture

4. Cloud Integration

Netgleam can help you transition to the future of corporate management and businesses and provide the necessary resources. Organizations can adopt our cloud services to save on costs and run operations as outsourced without in-house resources.

AWS (Amazon Web Services):

AWS is one of the cloud consulting companies in India known for providing various services on a large scale. It provides business services like machine learning, computing, analytics, artificial intelligence, and databases. Many platforms are looking at AWS as a cloud service provider due to its scalability and are using its services. Some providers are taking advantage of AWS services to handle their data. AWS's cloud consulting services offer flexible solutions for small to large enterprises.

Digital Ocean:

Digital Ocean has gained popularity quickly in India for providing services to startups and developers. It is an ideal and reliable choice for innovating companies as it focuses more on extensive documentation and community support. Developer-friendly features, simplicity, and affordability are why this provider is leading. Digital Ocean lets businesses manage cloud infrastructure with its robust APIs and user-friendly interface.

Google Cloud:

The Google Cloud service provider offers services like Kubernetes Engine, Compute Engine, and App Engine to Indian organizations to modernize applications and IT infrastructure. This platform provides some essential tools for businesses and organizations to build and scale applications in the cloud. GC's pricing model is transparent and best among sub-providers in terms of prices. With Google Cloud, you can avail of security features like transit, identity access management, and data encryption.

Microsoft Azure:

Microsoft Azure has emerged as a trusted provider in cloud computing with its vast experience. It designs its services to meet the cloud-related needs of organizations and businesses. It provides an environment for sensitive data compliant with compliance regulations and data privacy. The Microsoft platform offers a range of solutions and products catering to the Indian market. Azure integrates with applications such as SAP and Salesforce, making it easier for businesses to adopt cloud technologies.

Choosing the Best Cloud Computing Service Providers in India for Your Business When it comes to choosing the best cloud computing service provider for your organization, several factors should be considered. Understanding your company's budget and which cloud technology is suitable within that budget is crucial. Assessing the technical support provided by the provider and ensuring their reliability are also key considerations. This guidance can help you make an informed decision that best suits your business needs.

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