Category Archives: Cloud Computing

Cognata had been chosen by Microsoft to drive the ADPH global program as a global leader for its photorealistic sensor simulation and unique sensor models such as thermal cameras and 4D Lidars.

Key Highlights

REHOVOT, Israel, Dec. 21, 2023 /PRNewswire/ -- Cognata proudly announces its collaboration with Microsoft to drive the Automated Driving Perception Hub (ADPH) global program, running on Microsoft Azure, and AMD EPYC processors and Radeon GPUs, to allow Automotive customers to virtually and efficiently evaluate ADAS/AV sensors through digital twin-based sensor simulation. Cognata's Automated Driving Perception Hub allows sensors to be evaluated versus a common set of industry-standard scenarios, and their performance is quickly and easily analyzed.

Sensor selection is pivotal in steering the automotive industry toward reliable and safe autonomous vehicles and ADAS systems. Cognata's ADPH platform incorporates highly accurate sensor modeling, manufacturer approved, with a wide spectrum of sensors such as RGB cameras with varying lens distortions, Point-cloud (LiDAR) systems, as well as Thermal cameras (IR), all integrated with a DNN-based photorealistic layer, ensuring sensor performance precision.

With Microsoft's support, Cognata is accelerating the digital transformation on Azure's global cloud, services, and computing capabilities to accelerate ADAS/AV development, verification, and validation. Cognata's digital twin-based simulation requires powerful computing and graphics resources to run and scale. These advanced workloads and features are accelerated by AMD high-performance CPU and GPU technologies, enabling streamlined execution.

"We have joined forces to advance the automotive industry by bringing digital twin-based simulation into Microsoft Azure. The ADPH is a milestone achievement in our collaboration, showcasing our commitment to delivering cutting-edge technology," DannyAtsmon, CEO and founder of Cognata, highlights the significance of the project. "This platform seamlessly integrates manufacturer-approved sensor models and a sophisticated simulation environment, solving the challenge of optimizing sensor selection in a fully scalable manner."

"AMD is excited to deliver transformative innovation to the autonomous driving market in collaboration with Cognata and Microsoft," said Jeff Connell, corporate vice president and general manager, Strategic Silicon Solutions, AMD. "Our innovative portfolio of highly performant computing solutions, including AMD Radeon PRO V620 GPUs and AMD EPYC processors, provides an ideal combination of capabilities to power the critical workloads that enable autonomous driving technologies."

"We are pleased to collaborate with AMD for their high-performance CPU and GPU IP and Cognata for their photorealistic sensor simulation capabilities to provide a platform that will allow engineers to accurately evaluate real-world sensor performance on the cloud early on in the design process, said Dominik Wee, Corporate Vice President, Manufacturing & Mobility at Microsoft. "By front-loading upstream design and moving sensor evaluation from the physical world to the virtual world, we believe our customers will be able to innovate more rapidly and cost-effectively."

About Cognata

Cognata provides cutting-edge autonomous driving technologies with its end-to-end solutions for autonomous platforms. Other than an advanced engine creating a photorealistic simulation platform, Cognata offers the know-how of the market offerings, product integration, and a comprehensive V&V walkthrough, end-to-end. Working with some of the largest autonomous vehicle makers tier 1's in the world, Cognata accelerates the autonomous and ADAS engineering capabilities, and brings the unique power and expertise of artificial intelligence and computer vision, taking off years of the development process.

AMD, the AMD Arrow logo, EPYC, Radeon and combinations thereof are trademarks of Advanced Micro Devices.

Contact: Shay Rootman [emailprotected] http://www.cognata.com

SOURCE Cognata

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Cognata Redefines Sensor Suite Selection Processes Through Digital Twin-based Sensor Simulation and Cloud ... - PR Newswire

About Ian Lyall

Ian Lyall, a seasoned journalist and editor, brings over three decades of experience to his role as Managing Editor at Proactive. Overseeing Proactive's editorial and broadcast operations across six offices on three continents, Ian is responsible for quality control, editorial policy, and content production. He directs the creation of 50,000 pieces of real-time news, feature articles, and filmed interviews annually. Prior to Proactive, Ian helped lead the business output at the Daily... Read more

Proactive financial news and online broadcast teams provide fast, accessible, informative and actionable business and finance news content to a global investment audience. All our content is produced independently by our experienced and qualified teams of news journalists.

Proactive news team spans the worlds key finance and investing hubs with bureaus and studios in London, New York, Toronto, Vancouver, Sydney and Perth.

We are experts in medium and small-cap markets, we also keep our community up to date with blue-chip companies, commodities and broader investment stories. This is content that excites and engages motivated private investors.

The team delivers news and unique insights across the market including but not confined to: biotech and pharma, mining and natural resources, battery metals, oil and gas, crypto and emerging digital and EV technologies.

Proactive has always been a forward looking and enthusiastic technology adopter.

Our human content creators are equipped with many decades of valuable expertise and experience. The team also has access to and use technologies to assist and enhance workflows.

Proactive will on occasion use automation and software tools, including generative AI. Nevertheless, all content published by Proactive is edited and authored by humans, in line with best practice in regard to content production and search engine optimisation.

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Microsoft and Amazon the focus of cloud computing probe - Proactive Investors USA

Host with the most the cloud hosts the IT you want; it also offers a host of knock-on benefits. Aristides Zenonos describes the key choices, and the latest developments.

The concept of digital transformation has gained significant attention recently. It involves integrating digital technologies across an organisations operations, reshaping how they deliver value to customers, optimise internal processes and maintain competitiveness.

One essential aspect of it is the migration of data from traditional storage systems to a centralised data lake that is hosted on the cloud, while leveraging the powerful processing capabilities offered by cloud platforms. This opens up opportunities for data-driven solutions and the optimisation of business processes, enabling organisations to modernise their systems and adopt new software applications.

In the actuarial sector, motor and health insurance stand out for their handling of substantial data volumes. Today, as insurers seek enhanced precision, flexibility and efficiency from their digital tools and ecosystems, cloud computing is redefining the actuarial profession and enabling a wealth of new possibilities.

What are the definitions?

Cloud environments encompass the flexible provision of computing power, databases, storage, applications and other IT resources through the internet; delivery of these services is referred to as cloud computing. An on-premises environment involves the deployment of resources within an organisations internal IT infrastructure.

In simpler terms, on-premises refers to the physical servers and infrastructure on an organisations literal site, while the cloud refers to remote resources that are managed by a cloud provider somewhere else.

The three major players in cloud computing are Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), which currently have market shares of around 32%, 23% and 10% respectively.

Cloud computing is redefining the actuarial profession and enabling new possibilities

Control

On-premises environments give organisations complete control, ensuring the infrastructure is self-contained and eliminating the need for third-party involvement. This offers a sense of security and mitigates issues around internet connectivity or remote servers. They can also be advantageous in situations where organisations rely on legacy systems that are particularly difficult to migrate to the cloud.

Cloud environments obviously offer less control, as they rely on third-party providers. One significant advantage, though, is the flexibility. There are three main categories of cloud services: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).

IaaS essentially forms the foundation, providing the building blocks for network access, computing power and data storage. It offers maximum flexibility and control over IT resources, which can be tailored to an organisations needs.

PaaS is in the next level up. It removes the burden of overseeing the underlying infrastructure, enabling users to develop and manage applications without worrying about operating-system updates or hardware maintenance. Fully managed services such as data warehousing and machine learning modelling options fall under PaaS, such as AWS Redshift or GCP BigQuery and AWS SageMaker and GCP Vertex AI.

At the top is SaaS, which offers complete, ready-to-use applications that eliminate the need for installation, configuration or maintenance on users own systems. With SaaS, users can directly access fully functional cloud-based products, such as Gmail and Google Drive, without concerns about the underlying infrastructure.

By leveraging different cloud service models, particularly SaaS, end users can direct their attention to their primary tasks and actuaries can change the way they deliver value to clients. They can exploit machine learning and artificial intelligence (AI) to achieve higher accuracy in reserving, ratemaking, pricing and capital modelling. By analysing new data points, actuaries could address changing dynamics in life and pensions and understand emerging risks such as ESG (environmental, social and governance) and even AI itself.

Deployment

Rapid deployment is essential for meeting user expectations in todays competitive market, making it critical when comparing environments. A benefit of cloud computing is its speed and agility. With cloud resources instantly available, they can be accessible to practitioners in just minutes.

On-premises environments, on the other hand, must be configured and maintained by the organisation so that they are accessible for practitioners. These set-ups often need more time, due to having to configure their own systems.

Cloud solutions excel at speed; data-driven solutions can be effortlessly deployed in multiple regions worldwide with just a few clicks, allowing organisations to deliver solutions with low latency and back-up options. However, its important to note that on-premises environments can offer lower latency and faster response times in some cases, especially when cloud providers do not host resources in locations close to end-users.

Cost

Cost is where the two environments show significant differences. Cloud computing offers a pay as you go model, which provides flexibility and cost optimisation. On-premises infrastructure, meanwhile, often involves a significant upfront cost but provides long-term cost predictability. Organisations can plan their expenses more accurately over time without worrying about things like potential price increases.

One of cloud computings key advantages is its economy of scale. Cloud providers aggregate the usage of hundreds of thousands of customers, enabling them to offer lower prices. On-premises environments typically serve a single organisation, limiting the potential for cost optimisation through shared resources.

By adopting cloud computing, organisations can shift their focus away from managing and maintaining costly data centres and towards core business projects. This allows them to allocate resources to customer-centric initiatives and strategic endeavours, reducing overheads associated with physical infrastructure management.

Security

Many organisations place their trust in on-premises environments because the data remains on local machines, providing a sense of control and ownership. This is particularly crucial for industries with strict regulatory requirements or sensitive data that cannot be stored or processed in a public cloud environment. Industries such as healthcare and finance often have strict compliance and security requirements that necessitate maintaining data this way.

However, cloud providers extensive network of data centres ensures high availability, redundancy and disaster-recovery capabilities, which can be beneficial in ensuring business continuity. In addition, cloud providers nowadays follow strict protocols such as encryption, user and group permissions, and firewall components to ensure the safety of their data against malicious attacks.

Its true that an on-premises environment without direct internet connectivity provides more data security than the cloud. However, such isolated on-premises systems may lack a cloud-based solutions flexibility, scalability and collaborative features. Using the power of the cloud and tools such as version control and shared platforms promotes collaboration among staff.

In recent years, new approaches such as federated learning have emerged to foster collaboration while addressing data privacy concerns. Federated learning is a distributed method for training machine learning models; it operates in a decentralised manner, eliminating the need to transfer data from client devices to central servers. Cloud solutions also provide easily configurable functionalities and user permissions to meet diverse actuarial workflow needs, ensuring compliance with global insurance industry regulations such as Solvency II and IFRS 17.

Hybrid solutions

All this said, there is another option: the hybrid cloud. This offers businesses the ability to host resources both locally and remotely. Simply put, it combines different computing environments to support application deployment and data management. It allows organisations to leverage the benefits of both on-premises infrastructure and cloud computing.

This approach is widely adopted because it provides flexibility and enables businesses to continue using their existing on-premises services while taking advantage of the possibilities offered by cloud computing. It offers a balance between control, security and scalability, allowing organisations to optimise their own IT infrastructure.

Positioning for success

Cloud computing has emerged as a leading force that is driving innovation. To stay competitive, an increasing number of companies are embracing digital transformation, and actuarial professionals are recognising the role of data readiness in leveraging the potential of data-driven solutions and AI. They understand that access to high-quality and abundant data is essential for optimising business processes.

Deciding between on-premise or cloud environments requires a thorough understanding of your organisations circumstances. By considering factors such as data sensitivity, budget and resource requirements, businesses can make an informed choice. The goal is to create an infrastructure that supports operations, maximises efficiency, and positions the business for success in the technological era.

Aristides Zenonos is a senior data scientist

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Cloud cover benefits of being on the cloud - The Actuary

(Photo courtesy: dict.coursebank.ph)

A remarkable collaboration among the Department of Information and Communications Technology (DICT), ICT Literacy and Competency Development Bureau (DICT-ILCDB), and Digitaljobsph, Coursebank has opened doors to democratize knowledge about information technology.

The result? A treasure trove of 36 FREE online courses accessible to the general public, ushering in an era of seemingly limitless learning opportunities.

A Vision of Upskilling Excellence

Initially conceived as a means to elevate the skills of the Philippine Government's Information Technology (IT) professionals, the program's objectives have grown to encompass a broader horizon. It now aspires to empower IT professionals across government agencies, LGUs (Local Government Units), and SUCs (State Universities and Colleges), among others, while nurturing the next generation of tech-savvy professionals.

The driving force behind this initiative is a shared vision of a digital future where every individual is equipped with the knowledge and expertise to thrive in a rapidly evolving technological landscape.

The courses offered cover a spectrum of cutting-edge technological tools and emerging fields, including AI (Artificial Intelligence), Big Data, IoT (Internet of Things), and Cloud computing.

The Future of Learning: Asynchronous Online Training

One of the hallmarks of this program is its adaptability to the modern learner's needs.

Recognizing the diversity of schedules and learning paces, the training program adopts an asynchronous online training approach. Drawing inspiration from global leaders in massive open online courses, this method ensures that knowledge is accessible to all, irrespective of their daily commitments.

Embark on Your Learning Journey

If the prospect of enhancing your skills, exploring the frontiers of technology, and contributing to a digitalized future excites you, then Coursebank's array of free online courses is the gateway you've been waiting for.

To discover more about these groundbreaking programs brought to you in collaboration with Coursebank, visit dict.coursebank.ph. Your journey toward a digitally empowered future begins with a single click.

Don't miss this unparalleled opportunity to unlock your potential, enrich your knowledge, and become a part of a brighter, digitally adept Philippines. Embrace the future of learning today! (PIA-NCR)

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AI, Cloud Computing among 36 FREE Online Courses Now ... - Philippine Information Agency

Thisarticleis fromBig Technology, a newsletter by Alex Kantrowitz.

Amazons absence fromthis years generativeA.I. bonanza has been a bit puzzling. The company invented Alexa, intuiting peoples interest in speaking with computers, yet when OpenAI released ChatGPT it seemed to cede the territory.

But rather than sitting out the game, Amazon is waiting to play on its terms. Instead of building one A.I. product, it wants a piece of all of them. And its not shy about its ambition.

I wouldnt be at all surprised if just the A.I. part of our cloud-computing business was larger than the rest of AWS combined in a couple years, Amazon Web Services vice president Matt Wood told me in an interview at the cloud services summit this week.

Rather than releasing just one product or a large language model by itself, Amazon wants to enable companies building with generative A.I. to create any product using any model. Put another way, instead of developing one ChatGPT or GPT-4, Amazon wants to empower every would-be ChatGPT developer to use any GPT-like model and get going. Amazon will supply the model access, customization, and raw computing power to developers, and make its money as they build.

It is a great business opportunity, said Andrew Lipsman, principal analyst at Insider Intelligence. Its smart strategically to focus on where the profits are.

At the core of Amazons effort is a new product called Bedrock. Available inside AWS, Bedrock lets developers select from a range of A.I. models, including from Anthropic, AI21 Labs, and Stability AI. Using these models, developers can build their own products, like A.I. chatbots, and then run them on AWS infrastructure.

Bloomberg, for instance, built BloombergGPT, a bot for financial information, on a Bedrock precursor called SageMaker. To do it, the company took four decades of unstructured financial data and analytics, loaded them into AWS, added some other training material, and tuned the model. Bedrock should make such a process faster, with preloaded models in a catalog. Once a product is built, Amazon will continue to support it. When people chat with BloombergGPT, for instance, it uses Amazons storage to work, so Amazon gets a slice every step of the way.

We get paid by providing compute capacity to actually do the model training, and for providing the access to the large amounts of storage that are needed, said Wood. You may train a model once a month, once a week, but youre going to be running predictions and inference and chatting with that model hundreds, thousands, tens of thousands of times a day.

Competitors including Microsoft and Google offer similar capabilities, but Amazon has a few advantages. Without its own consumer chatbot, or a multibillion-dollar attachment to an A.I. research house, its pitching itself as a company with more neutrality and pragmatism than its peers. This could be compelling for developers looking for more customizability or assurance that their data stays at home, a pressing issue for many. Its also helpful for Amazon that so many internet companies already have their data on its cloud.Youd be surprised how many customers have exabytes of data on AWS, said Wood. An exabyte is 1 billion gigabytes.

Amazon does have its own A.I. model, called Titan, that it offers alongside its menu of others. So its not entirely neutral. The company also develops its own A.I.specific chips, which underlie some of the computing, but it doesnt sell them like Nvidia does. Both efforts are meant to enhance the core service offering.

Long ago, Amazon learned theres value to being first. It established its cloud-services lead early and still dominates. But on A.I., its playing catch-up as Microsoft appears to be in the lead, with11,000 customers using its generativeA.I. servicevia a partnership with OpenAI.

Amazon is, at least, joining right after the starting gun, with a plan that could work no matter what model or product wins. We are three steps into a marathon race, said Wood. And I dont think anybody without a smile on their face could call a winner three steps into a marathon, right?

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Amazon Web Services isn't trying to win the A.I. race. It wants to own the road. - Slate

This article was originally published on Network Computing.

FinOps is gaining steam, but companies shouldn't just forge ahead. They should carefully consider their approach to FinOps. The tech which garners most of the headlines is only one ingredient. The amount of data cloud services generate is so complex that people and processes are just as important.

Related: Why FinOps Is Key to Cloud Cost Optimization

Think about what FinOps has to do:

The human brain can't possibly do all of this. So, today's typical human tools manual processes and spreadsheets are not up to the task.

Related: How FinOps Can Help Optimize Cloud Spending

Integration:Cost management requires integration to discover shadow IT and evaluate usage across hundreds of SaaS apps, as well as private and publicIaaS. Integration is crucial so you can understand, in granular detail, cloud usage. In turn, this helps put boundaries around spending and can track dynamic pricing. FinOps should work in synch with financial management systems and should be able to produce general ledger files.

Real-time AI, ML, behavioral analytics (BA), and predictive analytics (PA):Handling all the data that the cloud produces means FinOps platforms must handle the cloud usage data that comes along for the ride. Multiple times a day, you'll have to crunch expansive data sets, track dynamic pricing (which can change daily), and compare your service configurations to millions of other pricing schemas all while normalizing cost data across multiple providers. AI, ML, BA, and PA can help with this task.

Cloud optimization and CEM working together:FinOps requires cloud service usage optimization and expense management to work in unison. Cloud optimization tools alone can only go so far. Yes, you need usage optimization tools that identify waste and unused resources, recommend lower-coststorage tiers, and help with rightsizing. But you also need an expense management platform to handle and automate invoice processing, cost allocations, and forecasting. And you need it all automated with a single-pane view, so you leave the manual headaches in the past.

Automated response (closed-loop automation):Insights are useless if you can't act. FinOps solutions and tech platforms should generate more than recommendations. They should be integrated into IaaS service control panels so you can approve a recommendation and ensure the system makes suitable service modifications automatically, which speeds up the time to savings.

How a tech research firm moved from manually managing the cloud to FinOps and started controlling multi-cloud infrastructure costs.

Talking about FinOps in the abstract is one thing. Seeing it at work is something else.

Senior IT and financial leaders at a technology research firm faced visibility, management, and cost control challenges after migrating much of the company's network infrastructure to the cloud. As their digital transformation matured, they found the cloud resource intensive.

Every month, IT financial analysts manually evaluated millions of dollars in expenses with little control over costs and invoice information. Analysts had to study tens of thousands of rows of billing information to decipher which departments were using each cloud service. Allocating each cost to its associated department was also a manual process. With roughly 500 departments, this administrative work had mushroomed into a full-time job for a larger group of employees. Because this work had become so laborious, finding the time to optimize costs seemed nearly impossible.

The company had been using a third-party cloud optimization tool for several years. As a point solution, it could highlight ways to optimize costs but couldn't automate IaaS financial management tasks. The company asked Tangoe to solve both problems, replacing the existing tool with one comprehensive FinOps solution for improved productivity and cost savings and do it all in 30 days, just before their contract expired.

Using the Tangoe One Cloud for IaaS solution, expense management experts implemented a proof-of-concept that worked across Amazon Web Services, Microsoft Azure, as well as Google Cloud Platform to deliver what the existing tool could not:

The company recognized productivity gains in both IT and financial departments. What used to take IT financial analysts an estimated 40 hours of manual work every week or month now happens in just minutes.

Today, company leaders have one complete solution giving them the peace of mind that comes from knowing their cloud investments are being utilized responsibly, and their spending is under control across their multi-cloud estate.

Taking a DIY approach can be risky unless you can build all these tools in-house with homegrown systems.

You need a sophisticated technology platform behind your cost management program and team. Tangoe is one such system. I recently wrote a buyer's guide titled, What To Look For In A Cloud Expense Management Solution. You can access ithere.

Zeus Kerravala is the founder and principal analyst with ZK Research.

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The Machines Behind the FinOps Curtain: Operationalizing Your Strategy with AI - ITPro Today

Steven Tamm is a technology adviser to Spin.AI and a former Salesforce CTO with extensive experience in cloud computing, e-commerce, virtualization, developer tools, cybersecurity, compliance and SaaS.

Managing security across multiple SaaS cloud deployments is becoming more challenging as the number of zero-day and ransomware attacks continues to rise. In fact, recent research reveals that a staggering 76% of organizations fell victim to a ransomware attack in the past year.

Its no secret that protecting data is hard, and with the rise of cloud technologies, its becoming harder. But when it comes to cloud SaaS application risk, what does that look like? And what actionable steps can teams and IT pros take to help mitigate those risks at their organization? In this article, Im going to explore those questions and provide some insights.

Modern organizations encounter a variety of SaaS challenges, including the absence of configuration standards, multiple APIs, and user interfaces (UIs) with varying access levels and potential data leaks across interconnected systems. Securing structured data in CRM applications, communication data in messaging platforms, and unstructured data from file providers is already difficult.

However, when these systems are sourced from different vendors, it becomes even more challenging to detect and prevent attacks in a timely manner. The interconnected nature of these systems makes tracking data provenance difficult and facilitates broad spread of malware and ransomware.

This challenge is further exacerbated when organizations extend their systems to include external users. With expanding footprints, the inadvertent leakage or destruction of sensitive data becomes a significant concern. Popular platforms like Salesforce Communities, Slack Connect, Microsoft Teams, Microsoft 365, and Google Drive create a complex web of identity, permissions, and integration controls.

Unfortunately, most endpoint management tools on the market were designed for a pre-cloud, pre-bring-your-own-device (BYOD) era, making them inadequate for managing the modern SaaS landscape. So how do you take control?

When managing risk in the cloud, its crucial to select IT and security solutions that truly address the intricacies of the deployed SaaS applications and were born 100% in the cloud without any legacy on-premises components. The good news is that vendors are developing innovative solutions to help IT and security teams do this. But its essential to explore the options and consider the following:

First, do they go beyond basic factors such as OAuth scopes, login IP addresses, and high-level scores, and instead delve deeper into data usage patterns and even examine the code of all integrations?

Second, many major SaaS vendors provide event monitoring, antivirus protection, and basic data leak prevention as check boxes. But these features often fall short when it comes to preventing and remediating data attacks because of miscalibrated thresholds in alert systems and logs that are not tuned for specific organizations. That results in alert overload and fatigue. Its important to understand how a solution improves risk scoring and alert prioritization.

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Strengthening security in a multi-SaaS cloud environment - TechCrunch

New OracleCloud Native SCCA Landing Zone solution reduces barriers to cloud adoption and enables mission owners to rapidly build compliant architectures

AUSTIN, Texas, July 31, 2023 /PRNewswire/ -- Oracle Cloud Infrastructure (OCI) has introduced a new Secure Cloud Computing Architecture (SCCA) for the U.S. Department of Defense (DoD). The solution helps make security compliance and cloud adoption for mission-critical workloads easier, faster, and more cost effective by using a framework of cloud native services.

SCCA is a DoD security frameworkdesigned to provide a standard approach for boundary and application-level security for the Defense Information Systems Agency(DISA) Impact Level 4 and 5 data hosted in commercial cloud environments. Historically, SCCA compliance has required significant investment from DoD mission owners in the form of independent development efforts and third-party software licensing. The cost and time result in a significant challenge during cloud migrations.

Oracle Cloud Native SCCA Landing Zone provides a framework for securely running DoD mission workloads and storing Impact Level 2, 4, and 5 data in OCI government regions. The automation provided by the solution enables DoD mission owners to establish a compliant security architecture in just a few hours or days, instead of months. It uses cloud native infrastructure services, significantly accelerating the time to deployment of mission critical workloads by reducing architecture time and minimizing decision points.

"Oracle Cloud Native SCCA Landing Zone is a game changer for our customers. What we are doing is fundamentally different,"said Rand Waldron, vice president, OCI Global Government Sector. "We will deliver all the capabilities necessary for SCCA completely in native OCI services. Our customers will no longer have to manage multiple licenses, multiple vendor relationships, or multiple kinds of security configurations. Our SCCA solution will provide everything the customer needs to stand up an SCCA-compliant workload in the cloud.".

Learn more about Oracle's new Cloud Native SCCA Landing Zone solution in the OCI SCCA Architecture Guide.

Simplifying and accelerating DoD security complianceThe Oracle Cloud Native SCCA Landing Zone includes baseline configurations, rules, and templates that meet DISA Impact Level 2, 4 and 5 accreditation requirements. This is delivered using a standardized Infrastructure-as-Code (IAC) template that meets a set of SCCA controls in a simplified and repeatable way. Based on Terraform, OCI Landing Zones allow OCI customers to perform one click, best-practice deployments of multiple Oracle services at once. Customers can launch the templates from the Cloud Native SCCA Landing Zone, answer a few simple questions about their configuration, and have an architecture set up same day.

The solution also addresses the four primary technical componentsof the SCCA framework; Cloud Access Point (CAP), Virtual Data Center Security Stack (VDSS), Virtual Data Center Management Service (VDMS), and Trusted Cloud Credential Manager (TCCM). Customers who deploy the secure baseline using the Cloud Native SCCA Landing Zone are provided with an architecture guide, implementation guide, requirements checklist, reference architecture, and best practices to accelerate the accreditation of their application on OCI.

Security, compliance, consistent high performance, and simple, predictable pricingThe Oracle Cloud Native SCCA Landing Zone script and associated technical documentation are provided at no separate or additional charge under a customer's contract. Underlying consumable cloud services used to stand up Oracle Cloud Native SCCA in a customer's tenancy may be billable in accordance with the customer's contract. Oracle Cloud for DoD services are priced at the same, consistent global pricing as Oracle's commercial public cloud regions and meet DISA Impact Levels 2, 4, and 5 and FedRAMP+ authorization standards.

Commercial customers can also take advantage of the automated security posture outlined above. All OCI customers can leverage custom security zones with the SCCA and other OCI Landing Zones that allow organizations to apply security policies and prevent changes that could weaken a customer's security configuration quickly and easily. Learn more about Oracle Landing Zones here.

Oracle Cloud Native SCCA Landing Zone scripts are available within the OCI Console, through GitHub, and from the Hosting and Compute Center (HaCC) website.

Additional Resources

About OracleOracle offersintegrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud.For more information about Oracle (NYSE: ORCL), please visit us atoracle.com.

TrademarksOracle, Java, MySQL, and NetSuite are registered trademarks of Oracle Corporation. NetSuite was the first cloud company--ushering in the new era of cloud computing.

SOURCE Oracle

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Oracle Introduces First Cloud Native Secure Cloud Computing ... - PR Newswire

Unleashing the Power of Cloud Computing: Revolutionizing Database, Storage, and Backup Software Publishing

The power of cloud computing is transforming the landscape of database, storage, and backup software publishing, revolutionizing the way businesses operate and manage their data. This technological advancement is not just a trend, but a paradigm shift that is reshaping the industry, offering unprecedented opportunities for efficiency, scalability, and innovation.

Cloud computing, at its core, is the delivery of computing services over the internet, or the cloud, rather than using local servers or personal devices. This includes servers, storage, databases, networking, software, analytics, and intelligence. The benefits of this model are manifold, including cost savings, increased productivity, speed and efficiency, performance, and security.

In the realm of database, storage, and backup software publishing, cloud computing is proving to be a game-changer. Traditional methods of data storage and backup involve physical hardware and servers, which can be costly, time-consuming to maintain, and vulnerable to damage or loss. Cloud computing, on the other hand, offers a more efficient and reliable solution. Data is stored in the cloud, which means it can be accessed from anywhere, at any time, and from any device with an internet connection. This not only enhances accessibility but also facilitates real-time updates and collaboration.

Moreover, cloud computing provides scalable storage solutions. Businesses can easily adjust their storage capacity based on their needs, paying only for what they use. This flexibility is particularly beneficial for businesses with fluctuating bandwidth demands. Additionally, cloud services often come with built-in backup and recovery solutions, making them a more secure option for data storage.

The impact of cloud computing on software publishing is equally profound. Software publishers are increasingly turning to cloud-based platforms to develop, distribute, and update their products. This approach allows for faster and more efficient software deployment, as updates and patches can be rolled out automatically, without the need for users to manually download and install them. Furthermore, cloud-based software can be accessed from anywhere, providing users with greater flexibility and mobility.

The shift to cloud computing also opens up new avenues for innovation in software publishing. With the cloud, software developers can leverage advanced technologies such as artificial intelligence (AI) and machine learning to create more sophisticated and intelligent applications. For instance, AI can be used to analyze user behavior and provide personalized recommendations, while machine learning can help improve software performance and functionality over time.

In conclusion, the power of cloud computing is revolutionizing the database, storage, and backup software publishing industry. By offering more efficient, scalable, and innovative solutions, it is helping businesses optimize their operations and stay competitive in the digital age. As cloud technology continues to evolve and mature, we can expect to see even more transformative changes in the way we store, manage, and use data.

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The Power of Cloud Computing: How it's Transforming Database ... - Fagen wasanni

The Department of Defense (DoD) leads adoption of cloud technologies to advance its various missions. As battlefields become more diverse and more dispersed edge computing is essential to support the DoD with insights and threat assessments that enable real-time decision making. To realize the full potential of edge technologies, cloud and edge ecosystems are coming together to support todays warfighters. MeriTalk sat down with Frank Reyes, cloud solutions leader at Maximus, to discuss the DoDs cloud strategy, the future of cloud computing across the DoD, and how industry can partner with the DoD to support cloud integration and achieve mission success.

MeriTalk: With DEOS, Cloud One, Stratus, and others, the Defense Department is taking a multi-cloud approach to cloud computing. What is driving the DoDs cloud strategy?

Reyes: There are three key drivers for the DoDs multi-cloud strategy. The first is interoperability and data portability. The DoD collects, stores, and analyzes vast amounts of data from multiple domain systems. With a multi-cloud approach, it can integrate data from a variety of systems and applications, allowing the data to be accessed and shared more efficiently across the different service branches, commands, and coalition partners. The second driver is agility. The DoD needs to rapidly access its infrastructure and applications to support evolving mission requirements. With a multi-cloud approach, the DoD takes advantage of diverse cloud service offerings to enable rapid provisioning and deployment of mission-critical applications. The third driver is innovation. The DoD recognizes the importance of harnessing emerging technologies including artificial intelligence (AI), machine learning (ML), advanced analytics, Internet of Things, and others to gain a competitive edge. A multi-cloud strategy allows the DoD to tap into innovations being developed by its cloud service providers (CSPs).

MeriTalk: Cloud-native applications are increasingly powerful. How are they helping DoD agencies meet their missions faster?

Reyes: By adopting cloud-native applications and architectures, the DoD can accelerate from monolithic to microservices architectures. This allows the department to develop, deploy, and scale applications faster, respond faster to changing mission needs, and deliver capabilities more efficiently. And, with the real-time data streams, ML algorithms, and predictive analytics baked into most cloud computing platforms, the DoD is able to generate insights from large data sets for better situational awareness and more effective operations.

MeriTalk: From remote sensors to satellites to drones, the DoD is collecting more data at the edge. How is that impacting the DoDs cloud needs and cloud computing capabilities?

Reyes: The DoDs ability to collect data from edge devices has grown exponentially, and cloud computing is currently the best capability that provides the infrastructure, storage capacity, and advanced analytics tools required to accommodate large-scale ingest, rapid analysis, and long-term retention of massive volumes of edge data.

The DoDs cloud needs are also being shaped by the requirements to establish reliable and secure connectivity between edge devices and the cloud infrastructure, especially in environments where backhaul is limited. Real-time or near real-time data transmission from remote sensors, satellites, and drones to the cloud is essential for that timely decision-making. The CSPs now offer a range of hardware that provides secure, high-bandwidth connectivity to facilitate the seamless data transfer between edge devices and the cloud.

And, when you dont have backhaul capability, you need to do your computing at the edge. The DoD is reducing latency, improving response times, and alleviating the burden on centralized cloud infrastructures by adopting more edge computing at the point of collection. This distributed approach enhances the performance of mission-critical applications, enabling real-time decisions.

MeriTalk: As edge computing continues to grow, what can Federal technology leaders do now to prepare for more insights generated at the edge?

Reyes: Leaders should strongly be considering leveraging the global infrastructure, such as edge servers and points of presence locations, closer to where the data is collected. Government can co-invest in these services with CSPs, along with partnering to enhance bandwidth and connectivity, including 5G and low-Earth satellite capabilities. As security is paramount with any device collecting and sharing information at the edge, government should develop security protocols for edge devices and data transmission.

MeriTalk: As the DoD explores use cases for generative AI, how will this affect edge computing and the DoDs cloud capability needs at the edge?

Reyes: Because generative AI involves computationally intensive tasks and requires large foundational models, it will be challenging to use the technology at the edge unless there are edge devices and capabilities to support it. That will require investments in purpose-built edge devices with improved compute capabilities. Improved devices will also allow the DoD to process data collected at the edge before sending it to the cloud for further analysis, reducing the amount of data transferred to the cloud. Another benefit of generative AI at the edge is improved cybersecurity. When sensitive DoD data supporting AI is processed and encrypted locally, the DoD maintains greater control over that data, which helps reduce the risk of unauthorized access.

MeriTalk: Can you share an example of how generative AI can be used in the field with the right cloud computing capabilities to support it?

Reyes: One example is images collected by drones in the field. Currently, drones on a mission collect information and images and send those back to a central location for analysis, which takes time. But, if we add edge computing resources and generative AI technology onto the drone, the device can process the data in near real-time and make inferences based on its training. Moving the compute function and generative AI technology to the edge drastically increases situational awareness and decision-making speed.

MeriTalk: What are some other ways cloud functionality at the edge can support the DoDs mission?

Reyes: Beyond the benefits of real-time data analysis to improve decision time, moving cloud functionality to the edge will be critical in environments with limited connectivity. Cloud at the edge also supports latency-sensitive applications such as precision-guided munitions and unmanned vehicle controls that require extremely low latency for performance. By moving cloud functionalities to the edge, those latency-sensitive applications can be executed locally, minimizing roundtrip time to the offsite cloud and enabling near instantaneous response time.

MeriTalk: The Joint Warfighting Cloud Capability (JWCC) allows the DoD to explore and acquire cloud solutions to serve missions from headquarters to the tactical edge. How can industry support the DoDs evolving cloud needs so it can realize the full potential of advanced edge technologies?

Reyes: First, industry can develop and offer meaningful cloud solutions that are tailored specifically to take advantage of an edge cloud computing infrastructure, cloud-enabled generative AI, and smarter edge devices. Industry can also help enable the seamless integration of those advanced edge technologies with the cloud. Secondly, industry can invest in the development and deployment of edge computing around the world and smaller edge computing infrastructure devices and in establishing standards-based interfaces, protocols, and APIs that enable seamless communication and data exchange between the edge devices and cloud for agencies. The third area is training support. Industry can help DoD personnel gain the necessary skills and knowledge they need to really understand how to extract the value of these new edge devices and cloud computing infrastructure.

MeriTalk: How can Maximus support the DoD with improving cloud capabilities to realize the full potential of edge technologies?

As a Federal systems integrator, we know the cloud and edge very well. With our expertise in cloud computing, we offer tailored solutions integrating cloud and edge ecosystems to enhance the DoDs ability to leverage data at the edge more efficiently. We collaborate with technology teams to design data architectures, implement a data governance framework, and leverage advanced analytics techniques to extract valuable insights from the vast amount of data generated by edge technologies. We then layer on AI and ML capabilities to deliver real-time situational awareness and fast decision-making capabilities. Maximus is also keenly focused on security and compliance. Our Maximus Cloud solution is FedRAMP accredited, and we manage multiple security operations centers throughout government. We can leverage that experience to implement robust security measures ensuring data protection while meeting regulatory standards.

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From Headquarters to the Edge: The Future of Cloud in the Defense ... - MeriTalk