Daily Archives: December 25, 2023

Industry cloud platforms are designed to meet the unique needs of vertical industry customers inadequately served by generic solutions. Yet finding a service that covers all the bases at reasonable terms can be a challenging task.

The main thing to consider when selecting a cloud provider is identifying candidates that fit your companys requirements, advises James Meade, digital solution architecture director with NTT Data Services in an email interview.

Look inward when considering industry cloud providers, suggests Brian Campbell, a principal in Deloitte Consultings strategy practice. An industry cloud should be closely tied to your business strategy, he says via email.

Find the fastest path to value, Campbell says. Many generic cloud players also offer specific industry cloud solutions. Pre-existing vendor relationships may make some platforms easier to integrate than others. Strive to preserve flexibility and the ability to innovate, he advises. The market is rapidly evolving, and monolithic implementations are giving way to user-friendly building blocks that are continuously improved. These are proving to provide the greatest advantage, Campbell observes.

Begin with your organizations current business strategy and work backwards, Campbell suggests. Consider the most important capabilities, then scan for solutions that can be leveraged in those particular areas. However, ensure that you take a wider view as well, so you dont lock yourself into your current ecosystem, he adds.

Related:Amazon CTO Talks Cloud, Creative Architecture, and Cost

An industry cloud package should also be evaluated on the basis of how well it meshes with existing applications and storage requirements. Re-educating the support staff to work with the new cloud environment can be costly and complex without the right guidance and precautions in place, Meade cautions.

Dont overlook your due diligence when searching for the right industry cloud for your organization. In a recent email interview, Bernie Hoecker, a partner and enterprise cloud transformation lead with technology research and advisory firm ISG, suggests breaking the industry cloud selection process into eight basic steps.

1. Define your requirements. Outline your organizations technical and business requirements and establish defined business goals and outcomes. The goals should be approved by senior management and coupled with strong management and governance practices.

2. Consider your overall cloud strategy. In many cases, a firm has already established a hybrid/multi-cloud strategy for internal and external workloads. Its critical to have the industry cloud aligned with the overall enterprise cloud strategy and to ensure that the firms data, security, and cost are integrated into an enterprise-wide IT and business strategy.

Related:What You Need to Know About Hybrid Cloud Computing

3. Perform a needs assessment. Conduct a review of the existing IT environment to identify gaps that should be addressed during the industry cloud journey.

4. Examine the clouds support attributes. The platform should offer strong data management and analytics functions to inform decision-making.

5. Understand the pricing structure. Consider the total cost of ownership, including any possible hidden costs.

6. Budget wisely. Establish a multi-year budget for deploying and running the industry cloud. The budget should focus on ROI and the value the cloud will bring to the enterprise and end-user clients.

7. Research. Meet with multiple cloud service providers, consultants, and services firms specializing in your specific industry. Also explore industry forums, associations, user groups, publications, and case studies to learn from others about their industry cloud experiences and models.

8. Ensure regulatory compliance. Be certain that the cloud selected complies with industry-specific regulations and standards.

Related:Getting Aggressive with Cloud Cybersecurity

One of the biggest mistakes IT leaders make when shopping for an industry cloud is searching for a solution without first constructing a holistic strategy, Campbell says. He recommends focusing on areas that will maximize the overall investment value, including data management and security operations, while ensuring both business and IT buy-in.

Due to multiple factors, including, compliance, business continuity, customer trust, and financial health, cybersecurity should be a central consideration when assessing industry clouds, says Nigel Gibbons, a director and partner with cyber threat consultancy NCC Group. Businesses store sensitive data in the cloud, such as customer details, financial records, and intellectual property, making cybersecurity essential to safeguard against unauthorized access and breaches, he notes. Gibbons adds that its also important to be aware of data sovereignty requirements and the impact of laws on where and how data is stored, particularly for businesses operating internationally.

To ensure tight alignment with both present and future business goals its important to choose a forward-looking provider, Gibbons says. Its essential to future-proof investments by choosing a provider that regularly innovates and updates its offerings.

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How to Select the Right Industry Cloud for Your Business - How to Select the Right Industry Cloud for Your Business - InformationWeek

The provision of computer services via the internet, including servers, storage, databases, networking, software, analytics, and intelligence, is known as cloud computing. Users can access and use these services without having to pay for and maintain physical infrastructure thanks to cloud computing. Additional advantages of cloud computing include scalability, dependability, security, and cost-effectiveness.

The global cloud computing market is anticipated to develop at a compound annual growth rate (CAGR) of 15.1% from USD 626.4 billion in 2023 to USD 1,266.4 billion by 2028, according to a research analysis by MarketsandMarkets.

The market for cloud computing is expanding due to several factors, including the rising demand for cloud services across various verticals and industries, the COVID-19 pandemics acceleration of cloud spending, the growing adoption of emerging technologies like edge computing, 5G, big data, artificial intelligence (AI), and machine learning (ML), and the growing need for digital transformation. This article will examine some of the major developments and prospects in the cloud computing market, as well as how they will affect the direction of the sector going forward.

A hybrid cloud is an on-premises infrastructure, private cloud, and public cloud combined into one cloud computing model. With a hybrid cloud, customers may benefit from the greatest features of both public and private clouds, including cost-effectiveness, scalability, and flexibility, all while retaining control, security, and performance from on-premises infrastructure and private clouds.

Applications that are created, developed, and implemented utilizing cloud computing concepts and tools, like serverless architecture, microservices, containers, and DevOps, are referred to as cloud-native applications. Users may fully benefit from the clouds features, like agility, scalability, resilience, and portability, with cloud-native apps.

A distributed computing paradigm known as edge computing moves processing and data storage closer to the places where they are required, such as near users, sensors, or other devices. Edge computing improves data processing security, privacy, and dependability while lowering transmission latency, bandwidth, and costs.

Amazon Web Services (AWS): AWS provides a vast array of cloud services, including networking, analytics, machine learning, computing, storage, databases, internet of things, security, and more.

Microsoft Azure: A wide range of cloud services, including computing, networking, analytics, machine learning, storage, databases, internet of things, security, and more, are provided by Azure.

Google Cloud: A wide range of cloud services, including computing, networking, analytics, machine learning, storage, databases, internet of things, security, and more, are provided by Google Cloud.

Alibaba Cloud: Numerous cloud services, including computing, storage, database management, networking, analytics, machine learning, the internet of things, security, and more, are provided by Alibaba Cloud.

IBM Cloud: Cloud computing, storage, databases, networking, analytics, machine learning, the Internet of things, security, and other services are all provided by IBM Cloud.

Data security and privacy: Working with cloud settings raises several security concerns because users are responsible for their data and because some cloud providers cannot guarantee 100% data privacy.

Cost management and containment: Managing expenses can be difficult when utilizing cloud services because users are only charged for the resources they use and may run into unforeseen or hidden expenses. Some of the things that can drive up cloud costs are performance problems, underuse, overprovisioning, and wasted resources.

Cloud computing is predicted to reach a size of US$1,266.4 billion by 2028, at a compound annual growth rate (CAGR) of 15.1%, from US$626.4 billion in 2023. This information comes from MarketsandMarkets. The following is the annual anticipated market size:

2024: US$760.9 billion

2025: US$925.8 billion

2026: US$1,125.6 billion

2027: US$1,240.9 billion

2028: US$1,266.4 billion

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Cloud Computing Market Set to Reach US$1,266.4 Billion by 2028 - Analytics Insight

Cisco announced this week its intent to acquire Isovalent, a leader in open-source cloud-native networking and security, to bolster its secure networking capabilities across public clouds. Financial terms of the deal were not disclosed. The deal is expected to close in Q3 of 2024, the companies said in a statement.

This is technology M&A deal number 339 that ChannelE2E and MSSP Alert have covered so far in 2023. See more than 2,000 technology M&A deals for 2023, 2022, 2021, and 2020 listed here.

Cisco, founded in 1984, is based in San Jose, California. The company has 99,809 associated members listed on LinkedIn. Cisco's areas of expertise include Networking, Wireless, Security, Unified Communication, Cloud, Collaboration, Data Center, Virtualization, and Unified Computing Systems.

Isovalent, founded in 2017, is based in Cupertino, California. The company has 158 associated members listed on LinkedIn. Isovalent's areas of expertise include Kubernetes, security, observability, networking, k8s, eBPF, and zero trust.

Isovalents team is a major contributor to the open-source extended Berkeley Packet Filter (eBPF) technology, and has led the development of Cilium, a cloud-native solution for networking and security. eBPF provides visibility into the inner workings of the operating system to help teams build security systems that can protect a workload while it runs. Isovalent has also recently introduced:

The acquisition of Isovalent will build on the Cisco Security Cloud vision, an AI-driven, cloud-delivered, integrated security platform. The Cisco Security Cloud enables customers to abstract security controls from multi-cloud infrastructure to provide advanced protection against emerging threats across any cloud, application, or workload.

Together with Isovalent, Cisco will build on the open source power of Cilium to create a truly unique multi-cloud security and networking capability to help customers simplify and accelerate their digital transformation journeys, said Jeetu Patel, executive vice president and general manager of Security and Collaboration at Cisco. "Imagine in today's distributed environment - of applications, virtual machines, containers, and cloud assets - having security controls with total visibility, without hindering networking and application performance. The combination of Cisco and Isovalent will make this a reality.

Cisco is committed to nurturing, investing in, and contributing to the eBPF and Cilium open source communities, said Stephen Augustus, Head of Open Source at Cisco. Isovalents team will join Cisco's deep bench of open-source governance and technical leadership to solve complex cloud-native, security, and networking challenges. Their knowledge will accelerate innovation across the business and help further strengthen the Cisco Security Cloud platform to meet the growing demands of our customers.

Isovalent holds leadership positions in theCloud Native Computing FoundationandeBPF Foundation,in addition to upstream software contributions, and this acquisition strengthens Cisco's role in supporting the open-source ecosystem, the company said. Cisco and Isovalent will continue to build solutions powered by eBPF technology that aim to solve the challenge of protecting workloads no matter where they reside, according to the statement. Cisco is committed to Cilium and Tetragon as open-source projects and intends to create an independent advisory board to help steer Cisco's contributions to these important efforts in a way that is aligned with the needs of the open-source community, Cisco said.

The Isovalent team will join the Cisco Security Business Group once the acquisition closes, which is expected in the third quarter of fiscal year 2024.

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Cisco to Acquire Isovalent to Secure Cloud-Native Networking - Channel E2E

Karunakarn Palaniswamy, Senior Director - Delivery & Technology, MSys Technologies Businesses today need to remain agile, nimble, and competitive, and to that end, cloud-native applications can prove to be of immense help. Contrary to the monolithic networks underpinned by tightly coupled entities, cloud-native applications are based on loosely coupled microservices architecture boasting high scalability and resilience. Further, these applications run on cloud platforms that complement business processes through their distributed architecture, decentralized access, and flexible storage options. No wonder the demand for cloud computing is rising exponentially across sectors, with research reports predicting the segment to reach $1240.9 bn by 2027 from a market cap of $545.8 bn in 2022, thereby growing at a CAGR of 17.9%. Benefits of cloud-native applications Scalability: The seamless addition of the instances to the individual microservices makes cloud-native applications the best for the scalability process. The best part is that this addition can be done without impacting the overall performance, which is in stark contrast to monolithic applications where any such addition impacts the entire system's performance. Hence, cloud-native applications allow organizations to scale operations swiftly without mandating comprehensive changes in their entire system architecture.

Agility: Thanks to the modular architecture of microservices, the apps can be developed and deployed independently. This makes it easier for firms to introduce new features and integrate updates without causing any significant disruption in their current ecosystems. This swift development, independent deployment, and uninterrupted integration offer businesses a competitive edge by helping them stay ahead of the innovation curve and swiftly bringing new products and features to market.

Portability: Cloud-native applications' platform-agnostic nature is another significant aspect. These applications can run on any supporting platform, and their ability to move seamlessly offers service providers the freedom to choose the platform that best fits their needs. Further, access to a wide variety of options in the development space fuels healthy competition, stimulates innovation, and helps the industry stay competitive on both the demand and supply side.

Microservice architecture: Cloud-native applications are based on microservices made up of smaller, loosely coupled components that allow for scalability at the granular level. Based on the firm's specific requirements, each microservice can be scaled independently of others, thereby offering the freedom to scale specific components without altering the architecture of the entire application. This feature also helps organizations to allocate resources judiciously, develop rapidly, deploy efficiently, and scale optimally within the broader constraints of resources.

iLeveraging containerization: To unlock the immense potential of cloud-native applications, containerization technology is becoming increasingly crucial. Container technologies such as Docker and Kubernetes allow the development and running of microservices in an isolated environment. These platforms also allow for the quick scaling of individual components per the changing needs and demands of the business environment. In addition, modern container platforms offer customers a complete automation facility, thereby enhancing both the scalability and resilience of organizations.

Dynamic workload management: Among their differentiating competencies, cloud-native applications adjust resource allocations dynamically based on varying requirements on the workload front. This auto-scaling allows organizations to predefine thresholds and trigger responses (such as allocating more storage capacity or computing power) as and when situations mandate. This helps achieve performance optimization during peak times while minimizing operating costs during low-activity periods.

Amplifying agility

Agility helps businesses create superior value by quickly tapping into emerging opportunities and responding to changing customer needs. The facet is equally essential from the development standpoint as it allows firms to remain innovative, competitive, and responsive. Here are the crucial factors that cloud-native applications enable to equip organizations with desired levels of agility and performance:

Faster time-to-market: Compared to the conventional methods, the microservices used by cloud-native applications speed up the development process and time-to-market response. The modular approach allows different development teams to work independently on individual services and components, allowing businesses to introduce new features, update existing networks, and replace laggard services with novel, efficient processes. Continuous development and delivery: Thanks to the modular approach and loosely bound architecture, firms using cloudy-native applications can continuously run their development and delivery operations. These applications also enable the automation of the building, testing, and deployment processes, thereby minimizing manual interventions and human errors. This continuous development also makes the companies' product pipelines dynamic and vibrant, further augmenting their appeal among current and prospective consumers.

High elasticity: Cloud-native applications dynamically add or withdraw resources in response to the changing demands on the various work fronts. This elastic behavior allows more computational power or storage capacity during high demand while withdrawing them from usage in lean hours. This, in turn, helps firms achieve a higher degree of operational efficiency and resource optimization while minimizing the cost and wastage associated with the use of resources.

Real-world examples

Netflix: The leading streaming company, Netflix, uses the cloud-native application to offer its streaming services to its customers worldwide. The microservice architecture allows Netflix to scale its operations effortlessly, handle traffic optimally, and quickly improve and roll out new services per changing customer preferences.

Spotify: Spotify, a well-known music streaming platform, uses the microservice architecture to offer personalized music recommendations to its millions of users worldwide. It uses cloud-native technologies that, coupled with the loosely coupled architecture, help the company handle massive volumes of data and continuously improve its algorithm for superior search and recommendation results.

Airbnb: Airbnb handles millions of its bookings worldwide effortlessly thanks to cloud-native principles in its functional procedures and operational mechanisms. The company uses various containerization and orchestration tools that help it create better value and deliver superior customer experiences.

Cloud-native applications are changing how organizations develop, deploy, and integrate their services to deliver superior value to their end consumers. The potential of these applications is immense. By embracing these loosely coupled, decentralized, and cloud-oriented microservices, organizations explore new opportunities while maximizing customer reach and business profitability.

The author is Senior Director - Delivery & Technology, MSys Technologies Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.

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Cloud-native applications: Unlocking the potential of scalability and agility - ETCIO

Maybe we are doing microservices all wrong?

This was the main thesis of Towards Modern Development of Cloud Applications (PDF), a paper from a bunch of Googlers (led by Google software engineer Michael Whittaker) that was presented in June at HOTOS 23: Proceedings of the 19th Workshop on Hot Topics in Operating Systems.

The problem, as Whittaker et al pointed out, was that microservices largely have not been set up correctly, architecturally speaking. They conflate logical boundaries (how code is written) with physical boundaries (how code is deployed). And this is where the issues start.

Instead, the Google engineers suggested another approach. Build the applications as logical monoliths but hand them off to automated runtimes, which makes decisions on where to run workloads, based on what is needed by the applications and what is available.

With this latency, they were able to lower latency systems by 15x and cost by up to 9x.

If people would just start with organized modular code, we can make the deployment architecture an implementation detail, Kelsey Hightower commented on this work in October.

A few months earlier, the engineering team at Amazon Prime Video posted a blog post explaining that, at least in the case of video monitoring, a monolithic architecture has produced superior performance than amicroservices and serverless-led approach.

In fact, Amazon saved 90% in operational costs by moving off a microservices architecture.

For a generation of engineers and architects raised on the superiority of microservices, the assertion is shocking indeed.

This post is an absolute embarrassment for Amazon as a company. Complete inability to build internal alignment or coordinated communications,wroteanalystDonnie Berkholz, who recently started his own industry-analyst firmPlatify.

What makes this story unique is that Amazon was the original poster child for service-oriented architectures, weighed in Ruby-on-Rails creator and Basecamp co-founderDavid Heinemeier Hansson. Now the real-world results of all this theory are finally in, and its clear that in practice, microservices pose perhaps the biggest siren song for needlessly complicating your system. And serverless only makes it worse.

The original Amazon video delivery system.

The task of Amazon engineers was to monitor the thousands of video streams that Prime delivered to customers. Originally this work was done by a set of distributed components orchestrated by AWS Step Functions, a serverless orchestration service, AWS Lambda serverless service.

In theory, the use of serverless would allow the team to scale each service independently. It turned out, however, that at least for how the team implemented the components, they hit a hard scaling limit at only 5% of the expected load. The costs of scaling up to monitor thousands of video streams would also be unduly expensive, due to the need to send data across multiple components.

Initially, the team tried to optimize individual components, but this did not bring about significant improvements. So,the team moved all the components into a single process, hosting them on Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic Container Service (Amazon ECS).

Microservices and serverless components are tools that do work at high scale, but whether to use them over monolith has to be made on a case-by-case basis, the Amazon team concluded.

Arguably, the term microservices was coined by Peter Rodgers in 2005, though he called it micro web services. He gave a name to the idea that many were thinking though, especially in the age of web services and service-oriented architecture (SOA) gaining attraction at the time.

The main driver behind micro web services at the time was to break up single large monolithic designs into multiple independent components/processes, thereby making the codebase more granular and manageable, explained software engineer Amanda Bennett in a blog post.

The concept took hold, especially with cloud native computing, over the following decades, and has only started receiving criticism in some quarters.

Software engineer Alexander Kainz contributed to TNS a great comparison on monoliths and microservices.

In their paper, the Google engineers list a number of shortcomings with the microservices approach, including:

When The New Stack first covered the Amazon news, many quickly pointed out to us that the architecture the video folks used was not exactly a monolithic architecture either.

This definitely isnt a microservices-to-monolith story, remarkedAdrian Cockcroft, the former vice president of cloud architecture strategy at AWS,now an advisor for Nubank, in an interview with The New Stack. Its a Step Functions-to-microservices story. And I think one of the problems is the wrong labeling.

He pointed out that in many applications, especially internal applications, the cost of development exceeds the runtime costs. In these cases, Step Functions make a lot of sense to save dev time, but can cost for heavy workloads.

If you know youre going to eventually do it at some scale, said Cockcroft, you may build it differently in the first place. So the question is, do you know how to do the thing, and do you know the scale youre going to run it at? Cockcroft said.

The Google paper tackles this issue by making lives easier for the developer while letting the runtime infrastructure bets figure out the most cost-effective way to run these applications.

By delegating all execution responsibilities to the runtime, our solution is able to provide the same benefits as microservices but with much higher performance and reduced costs, the Google researchers wrote.

This year has been a lot of basic architectural reconsiderations, and microservices are not the only ideal being questioned.

Cloud computing, for instance, has also come under scrutiny.

In June, 37signals, which runs both Basecamp and the Hey email application, procured a fleet of Dell servers, and left the cloud, bucking a decades tradition of moving operations off-prem for vaguely defined greater efficiencies.

This is the central deceit of the cloud marketing, that its all going to be so much easier that you hardly need anyone to operate it, David Heinemeier Hansson explained in a blog post. Ive never seen it. Not at 37signals, not from anyone else running large internet applications. The cloud has some advantages, but its typically not in a reduced operations headcount.

Of course, DHH is a race car driver, so naturally he wants to dig into the bare metal. But there are others willing to back this bet. Later this year, Oxide Computers launched their new systems hoping to serve others with a similar sentiment: running cloud computing workloads, but more cost-effectively in their own data centers.

And this sentiment seems to be at least considered more now that the cloud bills are coming due. FinOps became a noticeable thing in 2023, as more organizations turned to companies like KubeCost to control their cloud spend. And how many people were taken aback by the news that a DataDog customer received a $65 million bill for cloud monitoring?

Arguably, a $65 million observability bill might be worth it for an outfit that generates billions in revenue. But as chief architects take a harder look at engineering decisions made in the last decade, they may decide to make a few adjustments. And microservices will not be an exception.

TNS cloud native correspondent Scott M. Fulton III contributed to this report.

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Year-in-Review: 2023 Was a Turning Point for Microservices - The New Stack

For a recent commentary in the Journal of the American College of Radiology, radiologistFlorence Doo, MDand colleagues examined the role of cloud computing in supporting the specialty's future.

The authors argued that radiologists, as pioneers in integrating technology into healthcare, grapple with the increasing importance of managing the vast amounts of medical imaging datawhich they said constitutes 90% of all healthcare data.

The advent of AI, particularly large language models (LLMs), poses challenges in computing power and storage for current noncloud systems. Considering the strain on these systems, cloud technologies emerge as potential game-changers, offering technical capabilities along with economic and environmental advantages, noted Doo, with theUniversity of Maryland Medical Intelligent Imaging Center.

Below are the three key takeaways for why the shift to the cloud deserves serious consideration:

1. Moving to the cloud makes business sense:Radiology's increasing reliance on data-driven processes makes migrating to cloud-based solutions a logical and strategic move. Cloud adoption signifies a fundamental shift in how radiology departments manage imaging data. Tangible benefits of cloud migration include reduced downtime, enhanced productivity, deferred hardware investments, and economic advantages.

2. The AI revolution needs the cloud:Radiology is on the brink of a technological revolution driven by AI, mainly LLMs, which necessitate robust computing capabilities and extensive storage space. Cloud solutions offer a potential remedy, providing necessary infrastructure while reducing costs associated with hardware ownership, maintenance and upgrades.

3. Reduces the environmental impact of practices:Cloud migration not only offers economic benefits but also champions environmental responsibility by concentrating hardware, optimizing energy consumption and reducing the environmental footprint of radiological operations.

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If AI is the future, radiology needs to look to the cloud - Health Imaging

The Cloud Adoption Imperative

The current macroeconomic landscape is marked by exceptional volatility and uncertainty, posing challenges to traditional models in the financial services sector. This climate demands greater flexibility and responsiveness from established players to meet evolving customer needs, while managing costs and risks effectively.

Cloud infrastructure and artificial intelligence (AI) are key technological drivers enabling financial institutions to adapt to this changing market. Cloud computing, in particular, has emerged as a fundamental component of the financial system. It supports the necessary transformations banks and other financial bodies must undertake.

The adoption of cloud computing aids firms in streamlining processes, minimising risks, and enhancing efficiency. It also improves the capacity to identify new business opportunities and revenue sources. A central aspect of its impact lies in offering more tailored customer propositions, better pricing, and conducting operations that are safer and less risky.

Furthermore, cloud computing is essential for maintaining competitiveness in the new financial landscape. It empowers financial institutions to be more agile, resilient, and efficient, aligning with regulatory standards, especially in terms of outsourcing. By embracing cloud technology, financial institutions can revolutionise their business models, fostering new competencies, increasing efficiency, and delivering greater value to customers.

Download this Finextra impact study, produced in association with Microsoft Azure, to learn more.

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AI and Cloud: The Proving Ground for Regulatory Resilience in 2024 - Finextra

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