SAS, AWS, Google Cloud | May 21, 2021
SAS has expanded support for extra cloud providers because the demand for public cloud deployments of massive data and analytics (BDA) software grows.
As a part of its strategic partnership with Microsoft, SAS Viya was released in November on Microsoft Azure.
SAS now expands cloud-native support for Amazon Web Services and Google Cloud, with Red Hat OpenShift coming later this year.
SAS Viya is an AI, analytic, and data management platform that runs on a contemporary, scalable architecture.
It is cloud-native software, designed to be delivered and updated continuously and convey analytics to more businesses, teams, and use cases.
According to the corporate, SAS Viya integrates deciding with AI and advanced analytics, helping organizations to form better decisions, faster.
In its Worldwide Big Data and Analytics Software Forecast, 2020–20241 report, IDC says public cloud deployments represented 30.5% of the general BDA software market in 2019.
Furthermore, they're expected to grow at a CAGR of 23.2% through 2024, compared with a CAGR of -1.2% for on-premise/other software deployment methods.
According to SAS, that growth trend suggests organizations slow to adopt this technology may find themselves struggling compared to early adopters.
IDC program vice chairman worldwide AI and automation research practice Ritu Jyoti anticipates more cloud expansion from SAS as it’s what the marketplace demands.
Jyoti says, “It’s clear SAS is committed to supporting customers’ cloud choices. Expanding to Amazon Web Services and Google Cloud makes SAS Viya available to even more users.”
SAS CIO Jay Upchurch says, “Analytics within the cloud is what our customers want. We’re pleased with our pioneering work with Microsoft and running SAS Viya on Microsoft Azure.
"We also respect our customers’ decisions to settle on other cloud providers. We’ll meet them where their data is found and help them leverage their existing cloud investments to power their analytic aspirations.”
Upchurch added that the SAS Cloud runs on Microsoft Azure and enjoyed 34% growth year-over-year for Q1 2021.
SAS chief technical officer Bryan Harris says, “Over the last year, companies that have embraced digital transformation were ready to uniquely adapt to fast-changing market conditions. And digital transformation requires analytically-driven decisions.
"By expanding SAS Viya support for more cloud providers, we’re giving customers choice and control to deploy world-class analytics anywhere and at any scale across their enterprise.”
One example of the answer in action is with the COPD Foundation. The COPD Foundation may be a nonprofit that works on speeding up innovations to form COPD (chronic obstructive pulmonary disease) treatment simpler and affordable.
The foundation needed to explore unstructured data, identify patterns and make meaningful reports that might better help members, and ended up choosing SAS for in-house tongue processing of text data.
Chief information officer Vincent Malanga says, “Once we decided SAS was the thanks to going, we knew we wanted our SAS solution hosted during a cloud environment, which is why we partnered with Pinnacle Solutions and went with an Amazon Web Services infrastructure to support it.
"While there are many moving parts, everything runs seamlessly, and we’ve had a positive experience.”
CLOUD APP DEVELOPMENT
Cloud Security Alliance | June 23, 2022
Measuring Risk and Risk Governance was just made available by the Cloud Security Alliance (CSA), the foremost global organization for establishing standards, certifications, and best practices to assist assure a safe cloud computing environment. The survey, developed by CSA in partnership with Google Cloud to evaluate the maturity of public cloud adoption and risk management processes within the company, provided a deeper knowledge of these practices.
Adopting technology that improves operational and customer experiences is a part of the digital transformation process. The cloud is increasingly being considered as a way to boost an enterprise's risk posture with a view to enhancing overall business risk management; this action is frequently supported by an improved strategy for application, data, and infrastructure security. Because both the cloud service provider and the customer have ownership in the provision of services, business risk assessment methodologies must be adjusted to the cloud model and take these consequences into account. A greater understanding of IT's impact on an enterprise's entire risk maturity, including the adoption of a shared fate partnership between CSP and customers, is provided by evaluating cloud and business risk together.
"With enterprises continuing to add production in the cloud and the growing use of cloud services, managing cloud and digital assets will be critical in risk management and measurement. While there is still work to be done as organizations mature their ability to manage cloud and multi-cloud security and risk mitigations, these issues are improved in the cloud when compared to current on-premise and legacy IT environments. This study confirms that an organization's best path to viable risk management involves IT modernization into the cloud or cloud-like on-premise infrastructure,"
Jim Reavis, co-founder and CEO, Cloud Security Alliance
The survey, which was conducted in two phases, was designed to advance industry understanding of business risk. More than 600 IT and security experts from a range of company sizes and locations responded to the second component of the study, an online survey, using the information acquired in the first round of interviews, which were conducted by CSA.
"Increasingly, cloud is becoming less of a risk to manage and more of a means to manage these risks. Continuously evaluating your risk status allows enterprises to properly configure and maximize the effectiveness of their security solutions, which in turn, protects their assets and improves business productivity. This study has shone a light on the opportunities enterprises can take to manage and measure their risk, and will hopefully lead to improved risk management practices. And, whereas these practices impact many areas in the enterprise, modernizing the approach helps both businesses and providers improve their cloud adoption," said Phil Venables, Chief Information Security Officer and Vice President of Google Cloud.
CLOUD APP DEVELOPMENT
Aurora, AWS | December 02, 2021
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company announced that Aurora a leader in self-driving vehicle technology, has selected AWS as its preferred cloud provider for machine learning training and cloud-based simulation workloads. Aurora uses AWS’s proven infrastructure and unparalleled portfolio of capabilities to safely accelerate the development of the Aurora Driver, its scalable self-driving vehicle technology. The Aurora Driver consists of sensors that perceive the world, software that plans a safe path through it, and a computer that powers and integrates Aurora’s hardware and software with any vehicle platform. For its machine learning training and cloud-based simulation workloads, Aurora is all-in on AWS, and it uses the cloud to process trillions of data points each day. Now, the company is scaling its training workloads in the cloud to complete up to 12 million physics-based driving simulations per day by the end of the year, building on the petabytes of data it collects during real-world road tests.
Autonomous driving is an immensely complex technological challenge that relies heavily on cloud computing to enable breakthroughs in perception, embedded computing, machine learning, motion planning, decision making, and advanced sensor technologies. With AWS’s capabilities in high-performance computing, machine learning, storage, and security, Aurora optimizes and scales its virtual testing efforts to expand the capabilities of the Aurora Driver safely and quickly.
“Aurora’s advanced machine learning and simulation at scale are foundational to developing our technology safely and quickly, and AWS delivers the high performance we need to maintain our progress. With its virtually unlimited scale, AWS supports millions of virtual tests to validate the capabilities of the Aurora Driver so that it can safely navigate the countless edge cases of real-world driving.”
Chris Urmson, CEO of Aurora
Aurora’s AWS-powered Virtual Testing Suite is a unique accelerator for the development of the Aurora Driver. Aurora can use data from just one testing situation it observes in the real world to inspire hundreds of permutations in the Virtual Testing Suite. That virtual testing helps train the Aurora Driver to more quickly and safely navigate complex situations, such as road construction, jaywalkers, and unprotected left-hand turns. For example, before the Aurora Driver ever attempted an unprotected left-hand turn on a physical road, it completed nearly 2.3 million turns in simulation—estimated to be roughly equal to 20,000 hours of real-world driving practice. Aurora has been running simulations at scale on AWS since 2019, and plans to triple the volume of simulations it runs on AWS to more than 12 million per day by the end of 2021.
The offline components of the Aurora Driver software stack all run on AWS, including the Virtual Testing Suite, high-definition road maps (the Aurora “Atlas”), machine learning models, and software development tools. For example, Aurora uses Amazon SageMaker (an AWS service that helps developers and data scientists build, train, and deploy machine learning models quickly) to create, run, and continuously refine the machine learning models that enable its driving simulations. With that service, Aurora accesses Amazon Elastic Compute Cloud (Amazon EC2) instance types like P4d, which deliver the highest performance for machine learning training in the cloud.
Before developing simulations, Aurora uses AWS to securely store and process the petabytes of data it logs during real-world testing, and then train its machine learning models on that data. The pre-processing workloads run on Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon EMR, AWS’s service for processing vast amounts of data in the cloud using open-source tools. Aurora’s machine learning training workloads then rely on AWS-optimized deep learning frameworks, such as TensorFlow and PyTorch. Finally, Aurora orchestrates and auto-scales its simulation workflows over hundreds of thousands of concurrent vCPUs and thousands of concurrent GPUs with Amazon EKS and Amazon EC2, which provides accelerated computing instance types like G4dn.
“AWS’s highly scalable compute, machine learning, and analytics services are helping Aurora move self-driving vehicle technology forward, toward broad real-world use,” said Swami Sivasubramanian, Vice President of Machine Learning at Amazon Web Services, Inc. “Our reliable infrastructure and comprehensive set of cloud services, including industry-leading machine learning services like Amazon SageMaker, provide the ideal foundation for Aurora to gain insights from the trillions of data points it generates every day to continuously enhance its technology. We are proud to support the acceleration of autonomous vehicle innovation, and look forward to the improved safety and efficiency the transformation of trucking, delivery, and mobility will allow.”
About Amazon Web Services
For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 81 Availability Zones within 25 geographic regions, with announced plans for 27 more Availability Zones and nine more AWS Regions in Australia, Canada, India, Indonesia, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs.
Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon.
Founded in 2017 by experts in the self-driving industry, Aurora is on a mission to deliver the benefits of self-driving technology safely, quickly, and broadly. To move both people and goods, the company is building the Aurora Driver, a platform that brings together software, hardware and data services to autonomously operate passenger vehicles, light commercial vehicles, and heavy-duty trucks. Aurora is backed by Sequoia Capital, Baillie Gifford, funds and accounts advised by T. Rowe Price Associates, among others, and is partnered with industry leaders including Toyota, Uber, Volvo, and PACCAR. Aurora tests its vehicles in the Bay Area, Pittsburgh, and Dallas. The company has offices in those areas as well as in Bozeman, MT; Seattle, WA; Louisville, CO; and Wixom, MI.