Businesses have transformed the way they are run as a result of the transition to cloud computing, which is now the key to achieving flexibility and scalability in IT service delivery. This kind of transformation has been instrumental in the emergence of the Internet technology service sector especially in areas related to communication, documents sharing and working from home services. If businesses are already adopting these innovations, several cloud stocks have come out as frontrunners in this field. Zoom Communications (ZM), DocuSign (DOCU) and Upwork (UPWK) are the leaders of change in the future workplace.

As work from home and other flexible working models become more widespread, cloud computing is the foundation of today’s business. The key trends that have been identified in this industry are growth of hybrid cloud, AI services, and enhanced collaboration tools. All these advancements are as a result of the growing need for flexible and affordable solutions that can help organizations to change and grow quickly.

The cloud computing market around the world is projected to increase at a CAGR of 21.2% in the period between 2024 and 2030. As a result, the global IT services market, which was $1.4 trillion in 2023, is expected to be $2.9 trillion in 2034 with a CAGR of 7.1%. Such growth reflects the rising demand for cloud solutions in different spheres of business.

Zoom Communications (ZM)

Zoom Communications is one of the leading cloud stocks that are available to investors in the market. It has a full suite of unified communications solutions, which include Zoom Meetings, Zoom Phone, Zoom Rooms and Zoom Webinar. These solutions cater for various fields such as healthcare, education, financial, government and retail among others.

Hybrid cloud solution was launched in September 2024 when Zoom partnered with Mitel Networks to provide it. This partnership combines Zoom Workplace with Mitel’s communications solution to deliver increased efficiency and security to address enterprise demands for hybrid unified communications.

Source analysis: The most recent fiscal performance of Zoom speaks for itself. In detail, for the third quarter ending October 31, 2024, ZM recorded YoY growth of 3.6% in its revenue, $1.18 billion. Overall income from operations not on a GAAP basis increased by 2.4%, and the company also reported increased non-GAAP net income as well as non-GAAP EPS. For the financial year ending on 31st January 2025, Zoom has forecasted revenue of $1350.76, up from $1308.69, an increase of 3.2% while Earning per share has been forecasted to be 2.95, up from 2.81, an increase of 5.1%.

The leading cloud stocks is Zoom, which has risen 21.3% over the past year and 15.9% this year to date.

Given that companies are adopting cloud solutions at the speed of light, remote work and collaboration enablers such as Zoom Communications, DocuSign and Upwork remain at the forefront. These cloud stocks are still well-poised for growth in the future because the use of cloud technologies is only going to increase in the future and businesses around the world will continue to require more scalable IT solutions.

Source::   stocknews.com

Custom Chips: Innovating the Future of Cloud Computing

The cloud computing industry is transitioning, and custom chips are becoming the center of innovation when it comes to GPU shortages, energy consumption, and the changing workload. This is not just a reaction to the problems looming over supply chains but a proactive effort on the part of cloud providers to recast infrastructure effectiveness and elasticity.

The Challenges with GPUs

GPUs have been used for the development of AI and ML applications, particularly for computing and analysis for training and real-time use. But these shortcomings of these sources are now beginning to manifest themselves. GPUs are energy-consuming, produce much heat and therefore, need elaborate cooling systems. IDC analysts have said these disadvantages, alongside the global supply shortage, are making cloud suppliers look for new solutions. For example, its Blackwell GPUs, in particular, that attract a great deal of demand are already booked for a year, indicating the need to expand solutions.

The Role of Custom Silicon

To fill these gaps, cloud providers are now extending efforts toward custom chips for particular functions. Compared to the conventional processors, these chips provide greater capacity and effectiveness, and so are a better proposition. This is according to Mario Morales, an industry expert who has pointed out that custom accelerators allow for superior price-performance and energy efficiency ratios, thereby allowing hyperscalers to offer superior computing at lower prices.

Microsoft in particular has led this process. At its Ignite 2024 conference, the company introduced two innovative custom chips:

Azure Boost DPU (Data Processing Unit): This chip enhances data throughput for both hardware and software with a co-design technique, providing better performance for reduced power.

Azure Integrated HSM (Hardware Security Module): Catered towards security, this chip maintains that the encryption keys can only reside within the hardware to provide a boost in processing while improving security.

Besides these innovations, there were infrastructure enhancements like liquid cooling racks and Meta co-designed power racks for Azure, to support demanding workloads.

Competitive Landscape

The pressure to innovate in the custom chips space is growing even greater. Others in the industry such as Google, AWS, and others are also using custom silicon to boost their platforms. The AWS Nitro system and Google Titan chip are good examples of the dual approach to both performance and security considerations. Whereas AWS aims at the firmware assurance, the Googles’ approach of a hardware-based root of trust ensures secure system functioning.

Microsoft has made great strides but the field is still highly competitive. Experts note that specialists from such corporations as Nvidia and AMD, with their Bluefield and Pensando solutions, respectively, set very high standards within the DPU market.

The Future of Custom Silicon

The use of custom chips therefore represents a trend in cloud computing more generally. When hardware is developed to fit the workloads, the providers are in a better place to solve the current problems as well as look at the future market possibilities. This is not just the story of getting over GPU shortages; it is the story of how cloud architecture can unlock never-seen-before levels of performance, flexibility and security.

Alexander Harrowell of India has noted that the investment in custom silicon is a conscious move to maximize the margins, address the new workload brought about by AI, and serve the needs of other new applications. The inclusion of custom chips into cloud platforms is a new age that is revolutionizing computing through the hardware solutions.

source:: techhq.com

The 5 Key Tactics for Boosting cloud computing configuration  Across Multiple Regions

Thus, while establishing the cloud computing configuration  in different regions, organisations have higher availability, decrease latency, and address changing data regulations. However, the operation of a multi-region strategy creates such advantages. Taking efficient control of this, however, may not be easy. Here are five best practices to consider when deploying your multi-region cloud setup so that you can make the most of your setup.

• Just as you do not run a car on empty or over exhaust it, you should also avoid spending all your time on the computer, or overworking it to the extent of its capability, by not following the DRY Principle.
• Multi-Region cloud computing configuration  can be made efficient and effective by the principle known as Don’t Repeat Yourself (DRY). When setting resources across the regions do not copy the same code. For example, while using Terraform or OpenTofu, you need to define a map variable for your regions. This variable can contain region-specific data such as AMI IDs so that if you need to change some configurations, this script will not have to be rerun. This method makes updating easier and also guarantees that the configurations are standard.
• The next is to centralise resource management across regions:

As a cloud computing configuration, there is always the challenge of managing a configuration across regions especially in active-active. In other words, leverage centralized provisioning dashboards such as AWS EC2 Global View or AWS Organizations with Control Tower. These tools have capabilities to cluster resources like VPCs, instances and security groups so that it is easier for you to monitor and manage your multi-region cloud environment.

• Geographical Partitioning should be used for Improved Data Management

While working with multiple regions in the cloud, geo-division is crucial when it comes to data jurisdiction. Some such as the GDPR may even compel you to store data within a particular geography. Do not attempt to create different databases for each region; try to look for databases that support geo-partitioning. Splitting the data by the region helps to follow the legislation of the country where the data is stored, keep the latency low, and optimize replication.

• Select the Proper Technique of Data Replication

It is very essential to choose the correct data replication approach in multi-region cloud deployment. CAP theorem states that one must choose between consistency, availability, and partition tolerance, while the latter is obligatory in the multi-region solution. 

• • Active-passive environments should focus on replication while active-active environments should focus on availability. To achieve these, switch to asynchronous replication, which offers eventual consistency and can work effectively regarding latency in busy sites.

• The following is another strategy that should be adopted for better traffic distribution;

In the case of multi-region cloud computing configuration, routing mechanisms are instrumental in determining efficiency. While using an active-passive environment, ordinary routing might be enough while using an active-active environment needs more complex policies. Services like Amazon Route 53 come with the routing policies of latency, weighted, geo location and geo proximity so that traffic can be routed optimally and with least latency on a resource.

Using the above approaches it becomes easy to improve the multi-region cloud computing configuration, leading to improved performance, compliance and cost efficiency of the cloud infrastructure. These steps are meant to get the most from your cloud, as well as make sure that it is scalable, secure, and flexible within regions.

Source::   informationweek.com

Cloud computing GPUs have become popular especially with the emerging Artificial Intelligence (AI). But since demand has outdone supply, cloud providers are embracing the challenge by designing new chips that can fill the gap. These custom accelerators are intended to optimize specific workloads for better and cheaper solutions than those offered by cloud computing GPUs.

Probably the biggest reason why custom chips are becoming popular is because of the issues with GPUs. However, GPUs are critical, especially in training AI models, but they have some severe issues like high power consumption, heat dissipation, and the global shortage of GPUs that affect many industries. Nvidia, for instance, has its GPU pipeline filled for the next year, which underlines the necessity of having more options. As a result, cloud providers such as Amazon web service, Google, and Microsoft are developing custom chips to address emerging market requirements of their clients.

At Microsoft’s Ignite conference the company introduced two new custom chips built specifically for its Azure cloud computing platform. This is a new development as Microsoft follows others such as AWS and Google who have moved to custom silicon with their solutions including AWS Trainium and Google’s TPUs. New chips by Microsoft, Azure Boost DPU, and Azure Integrated HSM work on the enhancement of data processing for AI workloads and security respectively.

The Azure Boost DPU is specially built for data processing with its own operating system and the Azure Integrated HSM is designed to provide additional security to encrypt and manage keys. This places Microsoft squarely in a league with Google’s E2000 IPU and AWS Nitro, which has already been deployed in cloud infrastructure.

Security is another major domain where implementation of custom chips have shown to be beneficial. For example, The Azure Integrated HSM chip in Microsoft helps to lessen the latency and also enhance the scalability of encryption jobs. Both AWS and Google have their own security custom chips; AWS has a Nitro system that does not allow any changes to the firmware without its permission and Google has Titan that sets up a root of trust to check the health of the system.

The drive for cloud computing GPUs and custom chips is not letting up. These innovations give the cloud providers the capacity to meet this ever increasing demand for specialized, high-performance computing that is required by the current market. The future of cloud computing GPUs  is to embrace more of new custom silicon, which will be the next frontier of cloud performance.
source:;  cloudcomputing-news.net

The partnership between NetApp and Vultr is now official: Vultr is now a member of the Cloud Alliance. Allying NetApp’s robust data management tools with Vultr’s extensive global cloud platform will create flexible, scalable AI services for the enterprise. Organisations get to leverage NetApp’s ONTAP platform in Vultr’s data centres, while Vultr can leverage its highly flexible infrastructure to optimise data workload handling for the organisations.

The Cloud Alliance is meant to help organisations get the tool that will enable them to scale AI operations without running into vendor lock-in problems. Using both NetApp’s data management knowledge and Vultr’s solid infrastructure, industries such as finance, healthcare, manufacturing, and media can now obtain potent solutions. These sectors, where AI is applied to such processes as model training and high-performance computing, will find the enhancement of the management of the workflow and the usage of the cloud resources more efficient.

The first of these benefits is Cloud Alliance’s ability to provide its clients with a tailored approach to cloud infrastructure. This flexibility makes it easy for businesses to develop AI solutions that meet their immediate needs while at the same time being scalable to meet any future needs. Members of the Cloud Alliance, including AMD, SQream, and Run:human, each bring their strengths to the table, thus making the environment competitive and which fulfills various needs of businesses.

For enterprises adopting AI the integration solves several issues among them being; security, compliance and cost. According to the report by S&P Global Market Intelligence conducted for Vultr, the key considerations that customers need to consider before deploying an AI model include, F 24.8% flexible pricing and F 35.3% security and compliance. NetApp and Vultr meet these issues head-on by offering NetApp features such as integrated encryption, automatic backup, as well as compliance features.

The partnership also offers several technical features, such as:

• Hybrid cloud storage integration across all Vultr’s 32 locations.
• Further AI & ML assistance through Vultr’s Cloud GPU and NetApp Storage optimization.
• Data tiering to enhance cost optimization of the business.
• The ability to perform migration and synchronisation processes in a short time and with short interruptions.

With the work done in different sectors of industries, this partnership puts NetApp and Vultr at the forefront of the future of AI in business. Established to champion high-performance computing, data protection, and elasticity, the Cloud Alliance is revolutionizing business’s approach to AI and cloud environments.

SOURCE::  cloudcomputing-news.net