Category Archives: Cloud Computing

While Amazon's AWS cloud computing unit is investing in an AI-infused future, the tech titan is still under pressure to rake in money from online retail and ads  Islander News.com

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While Amazon's AWS cloud computing unit is investing in an AI-infused future, the tech titan is still under pressure to rake in money from online...

We continue our coverage this week of the International Solid State Circuits Conference (ISSCC), held in San Francisco, CA. At this event, groups from both academia and industry have gathered to present their latest and greatest research and developments.

As the conference program shows, many new solid-state circuits, architectures, and processors have been revealed as well as more comprehensive performance assessments.

Among the presented papers lies AMDs Zen 4c core, which may sound familiar as it has been included in recent years such as 9004 series processors or the Bergamo cloud-focused processor. This article dives into AMDs ISSCC paper to give designers more context on what the Zen 4c core offers and how AMD engineers were able to achieve it.

As more focus is shifted toward cloud computing, traditional approaches to processor design begin to become obsolete as number of cores can outweigh individual core performance. Conversely, edge-based devices can benefit from a small but powerful processor core.

These markets are where AMD hopes that the Zen 4c core can flourish. Compared to the older Zen 4 architecture, the Zen 4c is fully ISA and feature compatible, allowing for easier transitions to and from Zen 4 and Zen 4c software. In addition, the same TSMC 5 nm process is used, with more focus placed on area and power efficiency.

In terms of features, the Zen 4c core is highly similar to the normal Zen 4, with the primary deviation appearing in the L3 cache. Compared to Zen 4, the Zen 4c core only has 2 MB L3 cache compared to Zen 4s 4 MB. This tradeoff is compensated for, however, due to the increased number of cores allowed with the Zen 4c core architecture.

In order to support high-core-count dies, Zen 4c required aggressive optimization. In each SRAM cell, two transistors were shaved off by using a double-pumped architecture to perform reads and writes in one clock cycle. This allowed for a 40% macro area reduction while only reducing the clock speed by 20%.

While a lower clock frequency isnt necessarily a good thing, the lower clock ultimately means more area and power reduction per core due to 50% decreased leakage and 25% less switching capacitance. Ultimately, the Zen 4c core reported a 35% smaller core area in the same process node.

The increased area efficiency ultimately allowed AMD engineers to double the core count on a Zen 4c chiplet while maintaining the same amount of L3 cache and with only a 10% total area increase.

The resulting Zen 4c chiplet touted a 9% performance improvement over Zen 4 chiplets, showing the cores effectiveness in compute applications. Normalized to area and power, the Zen 4c shows a 25% and 9% improvement over Zen 4 architectures, paving the way for better and more efficient high-core-count processors in cloud computing applications.

Designers curious about the performance of Zen 4c cores can look to AMD EPYC 9004 series processors or 7000 series of mobile processors to evaluate the performance of the new cores. From what we know now, we can see that the Zen 4c cores excel in applications where efficient computing is required.

All images used courtesy of ISSCC and AMD

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ISSCC 2024: Inside AMD's Zen 4cThe Area-Optimized Cloud Computing Core - News - All About Circuits

Huawei Cloud: Infrastructure of Choice for AI with 10 Systematic Innovations Unveiled in MWC Barcelona 2024

PR Newswire

BARCELONA, Spain, Feb. 25, 2024

BARCELONA, Spain, Feb. 25, 2024 /PRNewswire/ -- This year's Huawei Cloud Summit demonstrates how Huawei Cloud is the infrastructure of choice for AI applications. With the theme of "Accelerate Intelligence with Everything as a Service", the 500-strong event brought together executives and experts from diverse industries, such as carrier, finance, and Internet. Huawei Cloud presented 10 AI-oriented innovations and extensive industry expertise of Pangu models. The objective is an AI-ready infrastructure tailored to each industry for a faster journey towards intelligence.

Jacqueline Shi, President of Huawei Cloud Global Marketing and Sales Service, said in her speech: "Huawei Cloud is one of the fastest growing cloud service providers in the world. At Huawei Cloud, we're all about pushing boundaries and bringing cutting-edge tech to customers around the world. We have launched a series of local cloud Regions in recent years, such as in Ireland, Trkiye, Indonesia, Saudi Arabia, giving customers easy access to the best-performing cloud. With over 120 security certifications worldwide, you can be sure your business and data are safe and sound. But it is not just about the tech. We believe in helping our partners grow alongside us, and this goal is now backed by our GoCloud and GrowCloud programs. And let's not forget AI it is reshaping everything, and we're at the forefront. We're building a solid cloud foundation for everyone, for every industry, to accelerate intelligence."

Today's foundation models redefine production, interaction, service paradigms, and business models for traditional applications. They make AI a new engine for the growth of cloud computing. While the potential is vast, implementing AI in line with business objectives requires systematic innovation. Huawei Cloud CTO Bruno Zhang said that "Huawei Cloud will help you with two strategies. AI for Cloud uses AI and foundation models to elevate your experience. They revolutionize software development, digital content production, and more. Cloud for AI makes AI adoption seamless and efficient. Architectural innovation, AI-native storage, and data-AI convergence empower you to train and use AI like never before."

At the Summit, Huawei Cloud unveiled ten AI-oriented innovations that make it the cloud infrastructure of choice for AI.

KooVerse: Huawei Cloud has 85 AZs in 30 Regions across over 170 countries and regions. This global cloud infrastructure covering compute, storage, networking, and security pushes latency down to 50 ms.

Distributed QingTian architecture: Foundation models require a 10-fold growth in demand for compute resources every 18 months, far surpassing Moore's Law.To address this challenge, this architecture evolved from the conventional primary/secondary one. Built on a high-speed interconnect bus (Unified Bus), QingTian surpasses the limitations in compute, storage, and networking for a top-class AI compute backbone with heterogeneous, peer-to-peer, full-mesh computing.

AI compute: Hyperscale and stable, AI Cloud Service supports trillion-parameter model training, and training jobs can run uninterrupted on a cluster over thousands of cards for 30 days, 90% of the time. Service downtime stays within 10 minutes. It provides over 100 Pangu model capability sets and 100 adapted open source large models out of the box.

AI-Native storage: Training models needs mountains of data, and Huawei Cloud handles this demand with a three-pronged approach: EMS memory service stores petabytes of parameters with 220 TB ultra-large bandwidth and ultra-low latency down to the microsecond; SFS Turbo cache service for high throughput and concurrency of tens of millions IOPS enables warm-up of 1 billion data records in just 5 hours, not 100; Object Storage Service (OBS) knowledge lake reduces 30% costs in storing training and inference data.

E2E security: The full lifecycle covers model runtime environments, training data, the models themselves, generated content, and applications. This ensures robust, secure, and compliant models and applications.

GaussDB: This next-generation database features high availability, security, performance, flexibility, and intelligence, as well as simple and smart deployment and migration. Specifically, its enterprise-class distributed architecture ensures high availability thanks to zero intra-city dual-cluster RPO, complete isolation of software and hardware faults, and zero service downtime. For security, it is certified CC EAL4+, the highest level in the industry. For automation, GaussDB enhances database migration, deployment, and migration as the world's first AI-native database.

Data-AI convergence: The explosion of foundation models means "Data+AI" is now "Data4AI and AI4Data". Huawei Cloud LakeFormation unifies data lake from multiple lakes or warehouses so one copy of data is shared among multiple data analytics engines and AI engines without data migration. Three collaborative pipelines DataArts, ModelArts, and CodeArts then orchestrate and schedule data and AI workflows. They drive online model training and inference with real-time data. The AI4Data engine makes data governance more intelligent, from data integration, development, to quality and asset management.

Media infrastructure: In this AIGC and 3D Internet era, Huawei Cloud has built a media infrastructure of efficiency, experience, and evolution. For efficiency, Huawei Cloud MetaStudio, the content production pipeline that include Workspace and AIGC-based virtual humans, generates content more quickly and better. For experience, Huawei Cloud Live, Low Latency Live, and SparkRTC empower more seamless interactions. For evolution, Huawei Cloud provides AIGC and 3D space services with real-time user interaction. All these combine to boost the business and user experience to the next level.

Landing Zone: Enterprises use and manage resources better on Huawei Cloud thanks to unified account, identity, permissions, network, compliance, and cost management. Now multi-tenancy and collaboration are seamless among personnel, finance, resources, permissions, and security compliance.

Flexible deployment: All mentioned Pangu model capabilities and services can work in public cloud, dedicated cloud, or hybrid cloud. For example, customers can build and run dedicated AI platform and foundation models in their existing data centers using Huawei Cloud Stack, a hybrid cloud solution.

The Mobile World Congress (MWC) 2024 is taking place in Barcelona from February 26 to 29. Huawei Cloud is set to collaborate with customers and partners to present a wide range of engaging topics. Additionally, innovative products and real-world cases covering Pangu models, GaussDB, data-AI convergence, virtual human, and software development will be showcased during the event.

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Huawei Cloud: Infrastructure of Choice for AI with 10 Systematic Innovations Unveiled in MWC Barcelona 2024 - Morningstar

42% of organizations surveyed in the US are considering or already have moved at least half of their cloud-based workloads back to on-premises infrastructures, a phenomenon known as cloud repatriation, according to Citrix.

The survey showed that 94% of respondents had been involved with a cloud repatriation project in the last three years.

Unexpected security issues (41%) and high project expectations (29%) were reported as the top drivers for moving some cloud-based workloads back to on-premises infrastructures. Another major driver was the failure to meet or properly set internal expectations, accounting for 23%.

After reflecting on their experience, IT leaders found that the most common reasons for cloud repatriation projects were security concerns, unexpected costs, performance issues, compatibility problems, and service downtime.

Over 29% of IT leaders found that moving projects from on-premises to the cloud was more expensive than expected, while 65% said it was financially predictable. The cost-benefit analysis of cloud versus on-premises infrastructure varies greatly depending on the organization.

Despite previously unsuccessful cloud projects, 70% of respondents are still encouraged to start new projects in the future. Instead of a complete cloud approach, IT leaders would recommend a mix of mostly cloud and some on-premises to the CIO.

Hybrid cloud infrastructures offer the best of both worlds across both public and private models. Organizations can optimize costs, seamlessly integrate systems, and experiment with innovation projects without compromising on agility or flexibility, said Calvin Hsu, VP of Product Management at Citrix.

As IT leaders consider utilizing a hybrid strategy, a key consideration is whether cloud or on-premises is the most secure for safeguarding sensitive information. In Citrixs study, 31% of respondents stated that they had fallen victim to the same number of cyberattacks regardless of whether data and applications were hosted on-premises or in a hybrid environment.

The experience of security vulnerabilities varied among different organizations, with some reporting fewer incidents on-premises while others experienced more.

Security is a top priority, and 93% of IT leaders agreed that cloud technologies can help prevent cybersecurity incidents. Moving workloads and cloud repatriation projects can pose a risk, and IT leaders are worried that these projects could make them vulnerable to a cyberattack. With benefits to both cloud and on-premises infrastructures, 50% of these IT leaders currently have projects in both cloud and on-premises.

Its clear that IT leaders are still trying to find the right balance between cloud and on-premises, Hsu added. With evolving demands and unexpected changes to priorities, enterprises need a model that allows them to scale resources up or down as required while maintaining security, compliance, and business performance.

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Cybersecurity fears drive a return to on-premise infrastructure from cloud computing - Help Net Security

BARCELONA, Spain, Feb. 25, 2024 /PRNewswire/ -- This year's Huawei Cloud Summit demonstrates how Huawei Cloud is the infrastructure of choice for AI applications. With the theme of "Accelerate Intelligence with Everything as a Service", the 500-strong event brought together executives and experts from diverse industries, such as carrier, finance, and Internet. Huawei Cloud presented 10 AI-oriented innovations and extensive industry expertise of Pangu models. The objective is an AI-ready infrastructure tailored to each industry for a faster journey towards intelligence.

Jacqueline Shi, President of Huawei Cloud Global Marketing and Sales Service, said in her speech: "Huawei Cloud is one of the fastest growing cloud service providers in the world. At Huawei Cloud, we're all about pushing boundaries and bringing cutting-edge tech to customers around the world. We have launched a series of local cloud Regions in recent years, such as in Ireland, Trkiye, Indonesia, Saudi Arabia, giving customers easy access to the best-performing cloud. With over 120 security certifications worldwide, you can be sure your business and data are safe and sound. But it is not just about the tech. We believe in helping our partners grow alongside us, and this goal is now backed by our GoCloud and GrowCloud programs. And let's not forget AI it is reshaping everything, and we're at the forefront. We're building a solid cloud foundation for everyone, for every industry, to accelerate intelligence."

Today's foundation models redefine production, interaction, service paradigms, and business models for traditional applications. They make AI a new engine for the growth of cloud computing. While the potential is vast, implementing AI in line with business objectives requires systematic innovation. Huawei Cloud CTO Bruno Zhang said that "Huawei Cloud will help you with two strategies. AI for Cloud uses AI and foundation models to elevate your experience. They revolutionize software development, digital content production, and more. Cloud for AI makes AI adoption seamless and efficient. Architectural innovation, AI-native storage, and data-AI convergence empower you to train and use AI like never before."

At the Summit, Huawei Cloud unveiled ten AI-oriented innovations that make it the cloud infrastructure of choice for AI.

KooVerse: Huawei Cloud has 85 AZs in 30 Regions across over 170 countries and regions. This global cloud infrastructure covering compute, storage, networking, and security pushes latency down to 50 ms.

Distributed QingTian architecture: Foundation models require a 10-fold growth in demand for compute resources every 18 months, far surpassing Moore's Law.To address this challenge, this architecture evolved from the conventional primary/secondary one. Built on a high-speed interconnect bus (Unified Bus), QingTian surpasses the limitations in compute, storage, and networking for a top-class AI compute backbone with heterogeneous, peer-to-peer, full-mesh computing.

AI compute: Hyperscale and stable, AI Cloud Service supports trillion-parameter model training, and training jobs can run uninterrupted on a cluster over thousands of cards for 30 days, 90% of the time. Service downtime stays within 10 minutes. It provides over 100 Pangu model capability sets and 100 adapted open source large models out of the box.

AI-Native storage: Training models needs mountains of data, and Huawei Cloud handles this demand with a three-pronged approach: EMS memory service stores petabytes of parameters with 220 TB ultra-large bandwidth and ultra-low latency down to the microsecond; SFS Turbo cache service for high throughput and concurrency of tens of millions IOPS enables warm-up of 1 billion data records in just 5 hours, not 100; Object Storage Service (OBS) knowledge lake reduces 30% costs in storing training and inference data.

E2E security: The full lifecycle covers model runtime environments, training data, the models themselves, generated content, and applications. This ensures robust, secure, and compliant models and applications.

GaussDB: This next-generation database features high availability, security, performance, flexibility, and intelligence, as well as simple and smart deployment and migration. Specifically, its enterprise-class distributed architecture ensures high availability thanks to zero intra-city dual-cluster RPO, complete isolation of software and hardware faults, and zero service downtime. For security, it is certified CC EAL4+, the highest level in the industry. For automation, GaussDB enhances database migration, deployment, and migration as the world's first AI-native database.

Data-AI convergence: The explosion of foundation models means "Data+AI" is now "Data4AI and AI4Data". Huawei Cloud LakeFormation unifies data lake from multiple lakes or warehouses so one copy of data is shared among multiple data analytics engines and AI engines without data migration. Three collaborative pipelines DataArts, ModelArts, and CodeArts then orchestrate and schedule data and AI workflows. They drive online model training and inference with real-time data. The AI4Data engine makes data governance more intelligent, from data integration, development, to quality and asset management.

Media infrastructure: In this AIGC and 3D Internet era, Huawei Cloud has built a media infrastructure of efficiency, experience, and evolution. For efficiency, Huawei Cloud MetaStudio, the content production pipeline that include Workspace and AIGC-based virtual humans, generates content more quickly and better. For experience, Huawei Cloud Live, Low Latency Live, and SparkRTC empower more seamless interactions. For evolution, Huawei Cloud provides AIGC and 3D space services with real-time user interaction. All these combine to boost the business and user experience to the next level.

Landing Zone: Enterprises use and manage resources better on Huawei Cloud thanks to unified account, identity, permissions, network, compliance, and cost management. Now multi-tenancy and collaboration are seamless among personnel, finance, resources, permissions, and security compliance.

Flexible deployment: All mentioned Pangu model capabilities and services can work in public cloud, dedicated cloud, or hybrid cloud. For example, customers can build and run dedicated AI platform and foundation models in their existing data centers using Huawei Cloud Stack, a hybrid cloud solution.

The Mobile World Congress (MWC) 2024 is taking place in Barcelona from February 26 to 29. Huawei Cloud is set to collaborate with customers and partners to present a wide range of engaging topics. Additionally, innovative products and real-world cases covering Pangu models, GaussDB, data-AI convergence, virtual human, and software development will be showcased during the event.

SOURCE HUAWEI CLOUD

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Huawei Cloud: Infrastructure of Choice for AI with 10 Systematic Innovations Unveiled in MWC Barcelona 2024 - PR Newswire

SEOUL, Feb. 26 (Yonhap) -- The science ministry said Monday it will invest 121.9 billion won (US$91.5 million) to bolster the local cloud computing industry this year.

The budget marked a 17.2 billion won increase from the previous year's allocation, according to the Ministry of Science and ICT.

The ministry said cloud technology plays a key role in advancing artificial intelligence (AI) as it provides high performance computing capacity and massive data storage capabilities.

In detail, the ministry plans to inject 24 billion won into the development and commercialization of innovative cloud services, 7 billion won into cloud-based software as a service (SaaS), and 8 billion won into the transformation of software to SaaS.

Around 20 billion won is set aside to create an innovation fund for SaaS.

"We will foster cloud technology across industries and society and support the innovative growth of local cloud companies, including SaaS, in the era of AI sparked by Chat GPT," a science ministry official said.

An image illustrating cloud computing technology (Yonhap)

nyway@yna.co.kr (END)

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Science ministry to invest 121.9 bln won in cloud computing industry - Yonhap News Agency

Microsoft has announced plans to quadruple its spending on cloud computing and AI infrastructure in Spain, part of a wave of investments the tech giant has been making across Europe in recent months.

The software giant said it is going to invest $2.1bn in AI and cloud infrastructure in Spain by 2025. Its Microsoft's largest investment in Spain in its 37 years of operating there.

As part of the move, Microsoft will open a data center cloud region located in Madrid, and plans to open another data center in Aragon that will serve European companies and public bodies. Across both these two sites, Microsoft said it will provide its entire range of AI offerings to Spanish and European companies.

These investments can make quite a difference even outside of the technology sector. The data centers in Spain could add 8.4bn to Spanish GDP and contribute to the creation of 69,000 jobs in the period up to 2030, according to figures from tech analyst IDC.

Microsoft said it will work with the Spanish government on responsible AI and support industry and government cyber security, for example, by working with the Spanish National Cybersecurity Institute and offering access to telemetry and information on potential threats and cyber attacks.

Its certainly not the first big cloud and AI investment Microsoft has showcased recently.

Earlier this month, it unveiled plans to invest 3.2bn in Germany, which again will be its largest investment in the country in its 40-year history of operating there.

The tech giant plans to expand its data centers for cloud and AI applications and train more than 1.2 million people in digital skills by the end of 2025. Over the next two years, the company will expand its cloud region in Frankfurt am Main and its newly planned infrastructure in North Rhine-Westphalia.

Microsoft said German companies and startups using its AI service include Siemens, which has developed the Siemens Industrial Copilot with the Azure OpenAI Service, and Commerzbank which is developing an AI banking avatar using Microsoft Azure AI.

But thats not all.

In November 2023, Microsoft announced it will more than double its data center footprint in the UK, with plans to spend 2.5 billion over the next three years and bring 20,000 of the most advanced GPUs to the UK by 2026.

As part of the spending again the single largest investment in its 40-year history in the country - Microsoft said it will grow its data center footprint across sites in London and Wales, with potential expansion into northern England.

At the time, Microsoft said it would also be extending its Accelerating Foundation Models Research (AFMR) program to include prioritized access to GPUs for the UKs science and research community, and train one million people with the skills they need to build and work with AI, including the first Professional Certificate on Generative AI.

So why is Microsoft investing so much, so fast? Part of the answer is the sheer demand the tech giant is seeing from European customers.

While cloud computing is not growing at the same incredible rates compared to previous years, for most organizations the direction of travel is still only towards the cloud.

Worldwide spending on cloud computing is expected to top $1.3tn by 2027 according to predictions from analyst IDC. Microsofts Azure accounts for about a quarter of cloud infrastructure spending, according to Canalys, and that means building a lot of data centers to keep up with demand especially if the AI boom continues because.

Where those data centers are matters, too, and is likely to get more important.

Data sovereignty is an increasingly big issue for all sorts of organizations. That means making sure their data is being kept in the right physical place to make sure that organizations are meeting data protection obligations and ensuring that data is protected from the prying eyes of other governments.

According to tech analyst Gartner, by 2028, half of multinationals will have a digital sovereignty strategy, up from just 10% now. That means having data centers wherever the customers are, because they will increasingly want to keep their data close, too.

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Why Microsoft is spending billions on AI and cloud computing in Europe - ITPro

Researchers Need the Right Tools for Their Jobs

Jenay Robert, senior researcher atEDUCAUSE, says the cloud has become essential for supporting research as institutions recognize the importance of unifying data models. She notes that effective communicationbetween IT departments and researchershelps smooth the path to the public cloud. Thats one of the biggest challenges: making sure everyone is aligned so they can move through these processes in a timely way that protects data without impeding research, she says.

As Bentley began deployingAzureresources to faculty members, the IT department produced different user personas to guide resource allocations. Initially, Shah says, the team planned to design most individual cloud environments around Jimmy, a user with needs for multiple CPUs or GPUs andhigh-speed storage for large data sets. However, they soon found that the bulk of researchers are more like Bob, a user who simply needs a fast machine and adequate storage capacity.

Instead of deploying identicalcloud environmentsby default, Shahs team surveys faculty members to learn more about the resources they need for their specific research.

Each of these environments come with different costs, Shah notes. We compare them to cars: If youre going to the grocery store, are you going to take out your Ferrari? We wanted to build for the actual need.

RELATED: Find the technology solutions to take your universitys research to the next level.

In March 2023,Googleand theUniversity of California, Riversideannounced a first-of-its-kind partnership that allows the school to accessGoogles cloud computingresources at a fixed subscription rate.

The cloud, for us, solves a unique problem, says Matthew Gunkel, UC Riversides CIO. We dont have a lot of data centers. We dont have land or the money to build new data centers. We needed a strategy that would allow us to scale within the confines of our available resources.

At the time of the move, Gunkel predicted that it would double or even triple the schoolscomputing and storage capacity, and he says that the partnership has yielded immediate benefits.

Having flat-rate access to cloud computing and open availability of the entire service catalog has been transformative in helping onboard researchers, he says. People are maturing through the process, from the lift-and-shift of workloads to using cloud services for building efficiency around how they conduct their research.

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Universities Migrate Research Computing to the Cloud - EdTech Magazine: Focus on K-12

Cloud computing has rapidly transformed how businesses operate and has become an integral part of various industries. As a data analyst, you are likely aware of how cloud computing has significantly impacted data storage, processing, and analysis. This analysis will explore key trends, challenges, and implications of the evolving cloud computing landscape.

Cloud computing refers to delivering computing services, including servers, storage, databases, networking, software, analytics, and intelligence, over the Internet to offer faster innovation, flexible resources, and economies of scale. Since its inception, the cloud computing industry has continuously evolved, driven by technological advancements, changing business needs, and emerging trends. Below, we'll examine various facets of this evolution.

Certainly, let's delve into the various types of cloud services in detail. Cloud services play a crucial role in modern data analysis and data-driven decision-making. Here, we'll discuss the primary types of cloud services and their relevance to a data analyst like yourself.

IaaS provides virtualized computing resources over the internet. It includes virtual machines, storage, and networking. IaaS can be instrumental for data analysts in terms of provisioning scalable computing resources for tasks like data preprocessing, model training, and data storage. Services like Amazon EC2 and Microsoft Azure VMs fall under this category.

PaaS offers a platform with tools and services for application development and deployment. It abstracts infrastructure management. PaaS can streamline data analysis tasks by providing pre-configured environments for data analysis tools and databases. For example, Google Cloud's BigQuery or AWS Elastic Beanstalk can simplify the deployment of data-driven applications.

SaaS delivers software applications over the internet on a subscription basis. Users access them through web browsers. SaaS solutions like Tableau, Power BI, and Google Data Studio are widely used for data visualization and reporting. They enable data analysts to create and share insights without worrying about software installation or maintenance.

FaaS allows developers (and data analysts) to run individual functions or pieces of code in response to events without managing servers. Serverless computing can be advantageous for executing data processing tasks in response to triggers, such as ETL (Extract, Transform, Load) operations. AWS Lambda and Azure Functions are examples.

DBaaS provides managed database services, reducing the administrative burden of database management. Data analysts frequently work with databases. DBaaS offerings like Amazon RDS and Azure SQL Database simplify database provisioning, maintenance, and scaling.

This emerging category offers cloud-based analytics tools and services, often with built-in machine learning and AI capabilities. These services, like Google's BigQuery ML and AWS SageMaker, empower data analysts to perform advanced analytics tasks, predictive modeling, and machine learning without extensive coding knowledge.

Cloud storage services provide scalable, secure, and highly available storage solutions. These services, such as Amazon S3 and Azure Blob Storage, are essential for storing large datasets, making them easily accessible for analysis and sharing.

SecaaS offers security services in the cloud, including identity and access management, threat detection, and encryption. Data security is paramount. SecaaS solutions help protect sensitive data and ensure compliance with data privacy regulations.

The very nature of cloud computingoutsourcing the storage and retrieval of often-sensitive business datanecessitates a profound focus on security and trust. IT security is (or should be) a top priority in most organizations, since a single security breach has the potential to expose customer data, steal valuable intellectual property, and permanently damage a companys reputation. The demand for cybersecurity talent in general is massive and growing every day, but particularly in the cloud domain.

Simplilearns free Certified Cloud Security Professional (CCSP) course, consisting of seven hours of self-paced video tutorials, is a great place to start. This introductory course will help you understand common vulnerabilities and risks, cloud application security, cloud architecture security, and more. When youre ready to proceed toward your certifications, enroll in the full CCSP course. This program consists of 50 hours of applied learning (a combination of live, online, instructor-led courses, self-paced videos, and hands-on projects) and includes a voucher for the certification exam.

Machine learning and artificial intelligence in general is a red-hot market segment, cloud computing aside. But since the major cloud vendors have offered tools and services that provide greater access to cloud-based AI and machine learning applications, they have become vital cloud computing skills. Once referred to as infrastructure as a service by Amazons AWS division, cloud computing can deliver the computing power and infrastructure that organizations of every size need if they want to dabble in AI and machine learning.

As the machine learning industry has matured, the delivery of machine learning solutions over the cloud is now referred to as machine learning as a service, or MLaaS, and is expected to experience a compound annual growth rate (CAGR) of 43 percent through 2024. As with cybersecurity, machine learning and AI are in need of talent generally. Combining technical skills required for cloud computing with AI skills, however, could exponentially raise your stock as a professional in the field.

Simplilearn offers a variety of AI, machine learning, and deep learning courses that can get you up to speed, including:

As organizations continue to migrate native IT systems to cloud platforms, or from one cloud platform to another, they have a need for professionals with deployment and migration skills. This isnt as simple as flipping a switch, but requires advanced cloud computing skills in order to protect the integrity and security of data while minimizing downtime. While its always smart to avoid limiting yourself, many organizations need professionals who understand all three major cloud platforms. If you have AWS skills, Azure skills, and Google Cloud skills, youll have more career opportunities and more value within a given organization.

Simplilearns Post Graduate Program in Cloud Computing, designed in collaboration with CalTech CTME, offers a comprehensive, 12-month program focused on all three major cloud platforms. Best of all, its designed for working professionals. If you just need to brush up on one or two cloud platforms, you might consider the following courses:

As a cloud computing professional, there are other technical skills you should have to thrive in your career. Being skilled in databases, DevOps, and other related technologies can help you to succeed and grow in the cloud computing industry.

Globally, we create 2.5 quintillion bytes of data every day, much of it unstructured but with the potential to provide enormous value for organizations. As these databases are mostly hosted on cloud platforms, the interest in distilling useful insights from this information fuels the demand for professionals with the cloud computing skills to manage, store, and access data. If youre an IT professional, this is the perfect time to invest in learning a database querying language and an associated database platform.

The de-facto standard database language to learn is SQL. If you want to develop your skills a little more, you could consider learning MySQL, MongoDB, or Hadoop. If youre new to database querying languages, then a good place to start is with Simplilearns SQL Certification Training Course

Derived from the term developmental operations, DevOps refers to the popular method of software development that takes the entire software lifecycle into account, from planning to maintenance. The DevOps method enables organizations to automate certain updates and get updates out much quicker and efficiently. Its an important development process in the world of cloud computing, so adding DevOps to your set of cloud computing skills is a smart move.

Simplilearns Post Graduate Program in DevOps, designed in collaboration with CalTech CTME, offers a comprehensive education in this process and will prepare you for roles where DevOps plays a significant role. If youre unable to commit to the nine-month post graduate program or youre just looking for something more introductory, then the 56-hour DevOps Certification Course may be a better option.

Containers are a fundamental technology in cloud computing that allows you to package and run applications and their dependencies in a consistent and isolated environment. The most popular containerization technology is Docker. Skills related to containers include:

Disaster recovery ensures business continuity during system failures, natural disasters, or other catastrophic events. Cloud computing offers robust disaster recovery solutions. Key skills in this area include:

Data migration involves transferring data from one system or location to another, often when moving to the cloud. Effective data migration is crucial for minimizing downtime and ensuring data integrity. Skills related to data migration include:

It's important to recognize that the fast-paced evolution of technology and the intricate nature of the digital era might leave you with skills gaps in your chosen field. For those aspiring to build a career in cloud computing, the opportunity to acquire up-to-date cloud computing expertise, including AWS skills, awaits you within Simplilearn's Post Graduate Program In Cloud Computing. Simplilearn's top-tier courses combine live, instructor-led classes with practical projects and self-paced tutorials geared toward helping you attain your objectives.

The best certifications for cloud computing include AWS Certified Solutions Architect, Microsoft Certified: Azure Administrator, Google Cloud Professional Cloud Architect, and CompTIA Cloud+. These certifications validate your cloud skills and can boost your career in cloud computing.

To transition to a cloud computing career, start by gaining foundational knowledge through online courses, books, or formal education. Practice on cloud platforms like AWS, Azure, or Google Cloud, and pursue relevant certifications. Networking, joining cloud communities, and seeking internships or entry-level positions are also helpful steps.

Future trends in cloud computing include serverless computing, edge computing, hybrid and multi-cloud adoption, increased focus on cloud security, AI and machine learning integration, and the continued growth of containers and Kubernetes for application deployment and management. Keeping up with these trends can help you stay competitive in the field.

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Top Cloud Computing Skills You Need to Know in 2024 - Simplilearn

In our world, data and data management is of prime importance. The more data we store, the better we can function and progress towards success. Data management can ensure we have all we need for optimum performance. And let's face it, every company these days wants to function well and reach its potential as a team running like a bullet train.

Being a cloud computing tool it carries out most of the functions that a generic cloud computing tool would do.

That is to store and help you manage and organize data and resources to your liking as well as convenience through the internet. With this feature, any cloud computing, including AWS offers services like databases, storage, and much more. AWS stands out for being flexible, scalable, and reliable, becoming the demographic's first choice of cloud tools.

Being a digital toolbox, several companies can benefit from this cloud tool, for it offers useful services such as data storage, running applications and software, IT management, and more.

One may call Microsoft Azure a place to store data, compute power, and gain access to various other resources when you need them. One needs to worry about physical management as it is its manager. As a cloud data storage software with useful services that vary depending on needs, it is like having your cloud in the sky that you can tap into.

Like the other above-mentioned cloud tools, Oracle Cloud also is a digital space for storing data, running apps and IT management. If there is a place you want to find all the tools you need to manage your precious data, then this is it.

Besides managing and storing data, it allows companies and individuals to collaborate with others in the process without any hardware hassle.

Like any other cloud tool, this tool is owned by a big technological company, IBM. Using their tools, services, and features, one may consider IBM Cloud a virtual hub for all things cloud and store data, manage them, and access them when needed, without tackling physical hardware.

A connecting unit that helps connect software and web applications. In these cloud tools, data processes are seamlessly sent back and forth between parts of your business. Cloudhub allows seamless data integration, so there is an efficiency factor in your business functioning.

It is useful to have a tool around to tally your business profits and losses. Like AWS and MS Azure, it simplifies data gathering and usage from one axis. With Cloudability, businesses can keep track of their expenses and usage patterns and ensure maximum value for the investments made.

The fact that this helps manage the financial aspect of cloud tools makes it a good contender among others.

With this cloud tool, you can build your applications without the worry of an underlying infrastructure. One can get a good yield by investing time in a digital infrastructure, however, it requires a constant check on servers, scaling, and maintenance. Unlike other cloud tools, Cloud App Engine allows you to work on your coding while Google looks over most of it on your behalf.

One tool that helps companies control and maximize their cloud computing tools-related expenses is called Cloudyn. It monitors their cloud service expenses, finds cost-saving opportunities, and offers information to support them in making wise decisions about cloud usage. Helping businesses maximize their cloud investment, it functions similarly to a broker for cloud computing.

This cloud tool called CloudZero aids companies comprehend and control their cloud computing expenses. It monitors the amount of money an organization spends on cloud services, such as processing power or storage, and offers information about where that cash is being spent. Through the analysis of usage data, CloudZero assists companies in making the most of their cloud computing investment, finding ways to cut costs, and optimizing their cloud resources. It functions as a financial expert for cloud expenses, assisting companies in controlling costs and making more informed decisions.

Lacework functions similarly to a security guard in the digital realm. To ensure that your computer systems, networks, and cloud services are safe from cyber threats, it closely monitors everything that occurs in them. Real-time data analysis searches for any odd behavior or possible threats. It notifies you if it notices anything unusual so you may implement the necessary cybersecurity precautions to safeguard your data and maintain the security of your systems.

Software provider Informatica assists companies in efficiently managing and analyzing their data. It offers solutions and the best cloud computing tools to gather, arrange, and convert data from diverse sources into insightful knowledge. In essence, it aids companies in making the most of their information to enhance operations and make better decisions.

IT operations use Chef to streamline organizing and setting up computer systems. It lets users use code to specify the ideal state of their systems, and it then applies those configurations automatically to multiple servers or machines to guarantee consistency and dependability.

Puppet is a processing tool for computer system management, much like Chef. It helps users manage substantial installations, maintain consistency, and expedite system administration tasks by allowing them to set up and regulate the envisioned state of their IT systems using code.

Being an expert cloud migration tool, falling under the best cloud computing tools category, Cloudsfer makes transfers between numerous cloud storage easy and hassle-free.

Experience butter-like files, folders, and other data transfers that users can manage and will find extremely handy to arrange digital property in a safe and secure cloud environment.

One tool that aids in task automation for IT operations is Ansible. It makes it simpler to install programs, oversee layouts, and coordinate difficult tasks without human intervention by enabling you to control and configure numerous PCs or server systems from a single location.

Carbonite is your storage room, where you can restore whatever data you wish. Thus securing them from loss. In the event of a malware malfunction, accidental deletion, or some other calamity, having one of these tools acts as your safe that can backup, restore, and preserve your precious data anytime.

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Best Cloud Tools of 2024: Unleash Maximum Productivity - Simplilearn