How AWS Can Work For Hybrid Cloud Customers

January 16, 2019 | 54 views

There are many reasons why an organization may opt for a hybrid cloud environment. The company may feel safer keeping certain applications, infrastructure, or data on premises; there may be a technical need, such as reliance on legacy software, that requires a hybrid environment; or they might require on-premises data storage because of the various existing regulations.

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SOTI

SOTI is a proven innovator and industry leader for mobility and IoT management. Organizations around the world depend on SOTI to enable their strategies for mobile devices, applications, content, as well as endpoints for the Internet of Things. Strong relationships with mobile technology and IoT partners around the world gives us advanced knowledge of new technologies and cutting-edge business solutions. Our commitment to innovation ensures your business is one step ahead with the solutions you need to take mobility to endless possibilities.

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SOFTWARE

The Revolutionary Power of 5G in Automation and Industry Digitization

Article | July 14, 2022

Fifth-generation (5G) mobile phone networks that can carry data up to 50 times faster than major carriers' current phone networks are now rolling out. But 5G promises to do more than just speed up our phone service and download times. The mobile industry's fifth-generation (5G) networks are being developed and are prepared for deployment. The expansion of IoT and other intelligent automation applications is being significantly fueled by the advancing 5G networks, which are becoming more widely accessible. For advancements in intelligent automation—the Internet of Things (IoT), Artificial Intelligence (AI), driverless cars, virtual reality, blockchain, and future innovations we haven't even considered yet—5 G's lightning-fast connectivity and low-latency are essential. The arrival of 5G represents more than simply a generational shift for the tech sector as a whole. Contributions by 5G Networks For a number of reasons, the manufacturing sector is moving toward digitalization: to increase revenue by better servicing their customers; to increase demand; to outperform the competition; to reduce costs by boosting productivity and efficiency; and to minimize risk by promoting safety and security. The main requirements and obstacles in the digitization industry were recently recognized by a study. Millions of devices with ultra-reliable, robust, immediate connectivity. Gadgets, which are expensive with a long battery life. Asset tracking along the constantly shifting supply chains. Carrying out remote medical operations. Enhancing the purchasing experience with AR/VR. Implementing AI to improve operations across the board or in various departments. The mobile telecommunications requirements of the Internet of Things cannot be met by the current 4G and 4G LTE networks. Compared to current 4G LTE networking technologies, 5G can also offer a solution to the problem and the quickest network data rate with a relatively low cost and greater communication coverage. The 5G network's quick speeds will lead to new technical developments. The upcoming 5G technology will support hundreds of billions of connections, offer transmission speeds of 10 Gbps, and have an extremely low latency of 1 ms. Additionally, it makes rural areas' services more dependable, minimizing service disparities between rural and urban areas. Even though the 5G network is a development of the 4G and 4G LTE networks, it has a whole new network design and features like virtualization that provide more than impressively fast data speeds.

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SOFTWARE

AI's Impact on Improving Customer Experience

Article | July 8, 2022

To enhance the consumer experience, businesses all over the world are experimenting with artificial intelligenace (AI), machine learning, and advanced analytics. Artificial intelligence (AI) is becoming increasingly popular among marketers and salespeople, and it has become a vital tool for businesses that want to offer their customers a hyper-personalized, outstanding experience. Customer relationship management (CRM) and customer data platform (CDP) software that has been upgraded with AI has made AI accessible to businesses without the exorbitant expenses previously associated with the technology. When AI and machine learning are used in conjunction for collecting and analyzing social, historical, and behavioral data, brands may develop a much more thorough understanding of their customers. In addition, AI can predict client behavior because it continuously learns from the data it analyzes, in contrast to traditional data analytics tools. As a result, businesses may deliver highly pertinent content, boost sales, and enhance the customer experience. Predictive Behavior Analysis and Real-time Decision Making Real-time decisioning is the capacity to act quickly and based on the most up-to-date information available, such as information from a customer's most recent encounter with a company. For instance, Precognitive's Decision-AI uses a combination of AI and machine learning to assess any event in real-time with a response time of less than 200 milliseconds. Precognitive's fraud prevention product includes Decision-AI, which can be implemented using an API on a website. Marketing to customers can be done more successfully by using real-time decisioning. For example, brands may display highly tailored, pertinent content and offer to clients by utilizing AI and real-time decisioning to discover and comprehend a customer's purpose from the data they produce in real-time. By providing deeper insights into what has already happened and what can be done to facilitate a sale through suggestions for related products and accessories, AI and predictive analytics are able to go further than historical data alone. This increases the relevance of the customer experience, increases the likelihood that a sale will be made, and increases the emotional connection that the customer has with a brand.

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FUTURE TECH

The Evolution of Quantum Computing and What its Future Beholds

Article | July 14, 2022

The mechanism of quantum computers will be entirely different from anything we humans have ever created or constructed in the past. Quantum computers, like classical computers, are designed to address problems in the real world. They process data in a unique way, though, which makes them a much more effective machine than any computer in use today. Superposition and entanglement, two fundamental ideas in quantum mechanics, could be used to explain what makes quantum computers unique. The goal of quantum computing research is to find a technique to accelerate the execution of lengthy chains of computer instructions. This method of execution would take advantage of a quantum physics event that is frequently observed but does not appear to make much sense when written out. When this fundamental objective of quantum computing is accomplished, and all theorists are confident works in practice, computing will undoubtedly undergo a revolution. Quantum computing promises that it will enable us to address specific issues that current classical computers cannot resolve in a timely manner. While not a cure-all for all computer issues, quantum computing is adequate for most "needle in a haystack" search and optimization issues. Quantum Computing and Its Deployment Only the big hyperscalers and a few hardware vendors offer quantum computer emulators and limited-sized quantum computers as a cloud service. Quantum computers are used for compute-intensive, non-latency-sensitive issues. Quantum computer architectures can't handle massive data sizes yet. In many circumstances, a hybrid quantum-classical computer is used. Quantum computers don't use much electricity to compute but need cryogenic refrigerators to sustain superconducting temperatures. Networking and Quantum Software Stacks Many quantum computing software stacks virtualize the hardware and build a virtual layer of logical qubits. Software stacks provide compilers that transform high-level programming structures into low-level assembly commands that operate on logical qubits. In addition, software stack suppliers are designing domain-specific application-level templates for quantum computing. The software layer hides complexity without affecting quantum computing hardware performance or mobility.

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FUTURE TECH

Language Models: Emerging Types and Why They Matter

Article | July 7, 2022

Language model systems, often known as text understanding and generation systems, are the newest trend in business. However, not every language model is made equal. A few are starting to take center stage, including massive general-purpose models like OpenAI's GPT-3 and models tailored for specific jobs. There is a third type of model at the edge that is intended to run on Internet of Things devices and workstations but is typically very compressed in size and has few functionalities. Large Language Models Large language models, which can reach tens of petabytes in size, are trained on vast volumes of text data. As a result, they rank among the models with the highest number of parameters, where a "parameter" is a value the model can alter on its own as it gains knowledge. The model's parameters, which are made of components learned from prior training data, fundamentally describe the model's aptitude for solving a particular task, like producing text. Fine-tuned Language Models Compared to their massive language model siblings, fine-tuned models are typically smaller. Examples include OpenAI's Codex, a version of GPT-3 that is specifically tailored for programming jobs. Codex is both smaller than OpenAI and more effective at creating and completing strings of computer code, although it still has billions of parameters. The performance of a model, like its capacity to generate protein sequences or respond to queries, can be improved through fine-tuning. Edge Language Models Edge models, which are intentionally small in size, occasionally take the shape of finely tuned models. To work within certain hardware limits, they are occasionally trained from scratch on modest data sets. In any event, edge models provide several advantages that massive language models simply cannot match, notwithstanding their limitations in some areas. The main factor is cost. There are no cloud usage fees with an edge approach that operates locally and offline. As significant, fine-tuned, and edge language models grow in response to new research, they are likely to encounter hurdles on their way to wider use. For example, compared to training a model from the start, fine-tuning requires less data, but fine-tuning still requires a dataset.

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Spotlight

SOTI

SOTI is a proven innovator and industry leader for mobility and IoT management. Organizations around the world depend on SOTI to enable their strategies for mobile devices, applications, content, as well as endpoints for the Internet of Things. Strong relationships with mobile technology and IoT partners around the world gives us advanced knowledge of new technologies and cutting-edge business solutions. Our commitment to innovation ensures your business is one step ahead with the solutions you need to take mobility to endless possibilities.

Related News

AWS Pushes Forward on Cloud Security, Database and AI Initiatives

eWeek | March 28, 2019

Amazon Web Services (AWS) is the leader in the public cloud market and it shows no signs of slowing down anytime soon. At the AWS Summit in Santa Clara on March 27, the public cloud provider announced several new services and capabilities, while reinforcing core elements of its platform growth including artificial intelligence and security. Among the new services is a concurrency service for the Redshift data warehouse, deep learning containers and the general availability of the App Mesh service mesh. Across all aspects of the cloud however, AWS sees security as being a foundational element. "I really want to emphasize that security is everyone's job," Amazon CTO Werner Vogels said during his keynote. "Because in the future, it is us as technologists that are responsible for protecting our customers and our businesses."Among the core areas of innovation that Vogels spent time discussing is AWS' expanding database capabilities in the cloud, which he sees as a key differentiator against rivals, including Oracle. Vogels said that because AWS has a new architecture that isn't reliant on legacy models for database deployment, it has been able to apply distributed systems techniques that have improved overall reliability and performance.

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AWS Issues Alert for Multiple Container Systems

Infosecurity Magazine | February 11, 2019

A security issue that affects several open source container management systems, including Amazon Linux and Amazon Elastic Container Service, has been disclosed by AWS. The vulnerabilities (CVE-2019-5736) were reportedly discovered by security researchers Adam Iwaniuk, Borys Poplawski and Aleksa Sarai and would allow an attacker with minimal user interaction to “overwrite the host runc binary and thus gain root-level code execution on the host.” Also among the affected AWS containers are the service for Kubernetes (Amazon EKS), Fargate, IoT Greengrass, Batch, Elastic Beanstalk, Cloud 9, SageMaker, RoboMaker and Deep Learning AMI. In its security issue notice published 11 February, AWS said that no customer action is required for those containers not on the list. Though blocked when correctly using user namespaces, the vulnerability is not blocked by the default AppArmor policy or the default SELinux policy of Fedora [++], according to Sarai. A common type of container exploit, this vulnerability is known as a host breakout attack, according to Praveen Jain, chief technology officer at Cavirin. “That these still occur, and will continue to occur, is all the more reason to ensure you have the people, processes and technical controls in place to identify and immediately remediate these types of vulnerabilities with a goal of securing their cyber posture.” If malicious actors were to leverage this vulnerability, Sarai said they could create a new container using attacker-controlled images or attach to an existing container to which the attacker had previous write access. “This is the first major container vulnerability we have seen in a while and it further enforces the need for visibility of your hosts and containers both in the cloud and traditional data centers using docker and other containers,” said Dan Hubbard, chief product officer at Lacework.

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AWS Unveils New Data Backup Service

SDxCentral | January 17, 2019

Amazon Web Services announced AWS Backup, a centralized service for customers to back up their data across both AWS’ public cloud as well as their on-premises data centers. The company said enterprises are having to deal with data located in multiple services such as databases, block storage, object storage, and file systems. While all of these services in AWS provide backup capabilities, customers often create custom scripts to automate scheduling, enforce retention policies, and consolidate backup activity to better meet their business and regulatory compliance requirements. AWS Backup removes the need for custom scripts by providing a centralized place to manage backups. Using the AWS Management Console, customers can create a policy that defines how frequently backups are created and how long they are stored. Bill Vass, VP of storage, automation, and management services at AWS, said in a statement that many customers want one place to go for backups versus having to do it across multiple, individual services. “Today, we are proud to make AWS Backup available with support for block storage volumes, databases, and file systems, and over time, we plan to support additional AWS services,” said Vass. Initially, AWS Backup is integrated with Amazon DynamoDB, Amazon Elastic Block Store (Amazon EBS), Amazon Elastic File System (Amazon EFS), Amazon Relational Database Service (Amazon RDS), and AWS Storage Gateway.

Read More

AWS Pushes Forward on Cloud Security, Database and AI Initiatives

eWeek | March 28, 2019

Amazon Web Services (AWS) is the leader in the public cloud market and it shows no signs of slowing down anytime soon. At the AWS Summit in Santa Clara on March 27, the public cloud provider announced several new services and capabilities, while reinforcing core elements of its platform growth including artificial intelligence and security. Among the new services is a concurrency service for the Redshift data warehouse, deep learning containers and the general availability of the App Mesh service mesh. Across all aspects of the cloud however, AWS sees security as being a foundational element. "I really want to emphasize that security is everyone's job," Amazon CTO Werner Vogels said during his keynote. "Because in the future, it is us as technologists that are responsible for protecting our customers and our businesses."Among the core areas of innovation that Vogels spent time discussing is AWS' expanding database capabilities in the cloud, which he sees as a key differentiator against rivals, including Oracle. Vogels said that because AWS has a new architecture that isn't reliant on legacy models for database deployment, it has been able to apply distributed systems techniques that have improved overall reliability and performance.

Read More

AWS Issues Alert for Multiple Container Systems

Infosecurity Magazine | February 11, 2019

A security issue that affects several open source container management systems, including Amazon Linux and Amazon Elastic Container Service, has been disclosed by AWS. The vulnerabilities (CVE-2019-5736) were reportedly discovered by security researchers Adam Iwaniuk, Borys Poplawski and Aleksa Sarai and would allow an attacker with minimal user interaction to “overwrite the host runc binary and thus gain root-level code execution on the host.” Also among the affected AWS containers are the service for Kubernetes (Amazon EKS), Fargate, IoT Greengrass, Batch, Elastic Beanstalk, Cloud 9, SageMaker, RoboMaker and Deep Learning AMI. In its security issue notice published 11 February, AWS said that no customer action is required for those containers not on the list. Though blocked when correctly using user namespaces, the vulnerability is not blocked by the default AppArmor policy or the default SELinux policy of Fedora [++], according to Sarai. A common type of container exploit, this vulnerability is known as a host breakout attack, according to Praveen Jain, chief technology officer at Cavirin. “That these still occur, and will continue to occur, is all the more reason to ensure you have the people, processes and technical controls in place to identify and immediately remediate these types of vulnerabilities with a goal of securing their cyber posture.” If malicious actors were to leverage this vulnerability, Sarai said they could create a new container using attacker-controlled images or attach to an existing container to which the attacker had previous write access. “This is the first major container vulnerability we have seen in a while and it further enforces the need for visibility of your hosts and containers both in the cloud and traditional data centers using docker and other containers,” said Dan Hubbard, chief product officer at Lacework.

Read More

AWS Unveils New Data Backup Service

SDxCentral | January 17, 2019

Amazon Web Services announced AWS Backup, a centralized service for customers to back up their data across both AWS’ public cloud as well as their on-premises data centers. The company said enterprises are having to deal with data located in multiple services such as databases, block storage, object storage, and file systems. While all of these services in AWS provide backup capabilities, customers often create custom scripts to automate scheduling, enforce retention policies, and consolidate backup activity to better meet their business and regulatory compliance requirements. AWS Backup removes the need for custom scripts by providing a centralized place to manage backups. Using the AWS Management Console, customers can create a policy that defines how frequently backups are created and how long they are stored. Bill Vass, VP of storage, automation, and management services at AWS, said in a statement that many customers want one place to go for backups versus having to do it across multiple, individual services. “Today, we are proud to make AWS Backup available with support for block storage volumes, databases, and file systems, and over time, we plan to support additional AWS services,” said Vass. Initially, AWS Backup is integrated with Amazon DynamoDB, Amazon Elastic Block Store (Amazon EBS), Amazon Elastic File System (Amazon EFS), Amazon Relational Database Service (Amazon RDS), and AWS Storage Gateway.

Read More

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