Lenovo | June 19, 2020
Lenovo Data Center Group. Our new ThinkSystem servers are designed to enhance mission-critical applications like SAP HANA and accelerate next-generation workloads like AI.
The servers, combined with the DM7100 and business intelligence solutions from SAP, are material to helping customers address their data challenges in a variety of ways
A new remote deployment service offering for the Lenovo ThinkSystem DM7100 offers up to 80% faster implementation vs. scheduling on-site deployments.
Today, Lenovo Data Center Group (DCG) announced new flexible solutions to empower customers to simplify common data management challenges. DCG is announcing the launch of the ThinkSystem SR860 V2 and SR850 V2 servers, which now feature 3rd Gen Intel Xeon Scalable processors with enhanced support for SAP HANA based on Intel Optane persistent memory 200 series. In addition, Lenovo is announcing new remote deployment service offerings for the ThinkSystem DM7100 storage systems.
With these new offerings, customers can more easily navigate complex data management needs to deliver actionable business intelligence through artificial intelligence (AI) and analytics, while getting maximum results when combined with business applications like SAP HANA®. Many industries are faced with the ever-increasing challenge of having to analyze greater volumes of data, maintain the velocity of the data being transacted and support the variety of the data being collected and stored.
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Lenovo’s new ThinkSystem SR860 V2 and SR850 V2 mission critical servers feature 3rd Gen Intel Xeon Scalable processors and support for enhanced Intel® Deep Learning Boost enabling customers to handle their most data intensive workloads.
Without proper storage and processing capabilities, organizations are missing critical insights about their customers and business, while others experience bottlenecks due to a variety of data types that need to be analyzed, categorized and more quickly utilized to drive business value. Finally,
the insights that come from data have definitive time limits, so the faster that systems can handle data, the greater amount of value that can be extracted.
To help customers accelerate high performance workloads and improve efficiency, Lenovo’s new ThinkSystem SR860 V2 and SR850 V2 servers feature the latest in high-end processing and memory capabilities, with twice the amount of NVMe storage capacity1. The servers, combined with the DM7100 and business intelligence solutions from SAP, are material to helping customers address their data challenges in a variety of ways. The new 3rd Gen Intel Xeon Scalable processor-based enable more rapid data ingest capabilities to help tackle the growing volume of data coming into the data center.
When combined with Lenovo DB fiber channel switches, customers can now achieve end-to-end NVMe deployment, delivering higher throughput and up to a 50 percent reduction in latency.
The constant change in information and ever evolving needs of customers means there must be faster and more efficient solutions to turn data into information that empowers businesses,” said Kamran Amini, Vice President and General Manager of Server, Storage and Software Defined Infrastructure, Lenovo Data Center Group. “Our new ThinkSystem servers are designed to enhance mission-critical applications like SAP HANA and accelerate next-generation workloads like AI, analytics and machine learning, enabling mission critical performance and reliability for all data centers and maximum business value for our customers.
Lenovo is a US$50 billion Fortune Global 500 company, with 63,000 employees and operating in 180 markets around the world. Focused on a bold vision to deliver smarter technology for all, we are developing world-changing technologies that create a more inclusive, trustworthy and sustainable digital society. By designing, engineering and building the world’s most complete portfolio of smart devices and infrastructure, we are also leading an Intelligent Transformation – to create better experiences and opportunities for millions of customers around the world. Select configurations of the ThinkSystem SR860 V2, SR850 V2 and DM7100 solutions are available through Lenovo TruScale, the pay-for-what-you-use data center, offering customers a flexible and cost effective option for adoption.
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DevOps | June 04, 2020
Artificial intelligence and ML can help us take DevOps to the next level through identifying problems more quickly and further automating our processes.
The automation wave has overtaken IT departments everywhere making DevOps a critical piece of infrastructure technology.
This automation frees up valuable IT resources to focus on innovative solutions, Here are three areas where AI and machine learning are advancing DevOps.
The automation wave has overtaken IT departments everywhere making DevOps a critical piece of infrastructure technology. DevOps breeds efficiency through automating software delivery and allowing companies to push software to market faster while releasing a more reliable product. What is next for DevOps? We need to look no further than artificial intelligence and machine learning.Most organizations quickly realize the promise of AI and machine learning, but often fail to understand how they can properly harness them to improve their systems. That isn’t the case with DevOps. DevOps has some natural deficiencies that are difficult to solve without the computing power of machine learning and artificial intelligence.
They are key to advancing your digital transformation. Here are three areas where AI and machine learning are advancing DevOps. As our technology stack grows, the complexity of our systems become increasingly magnified. Consider a distributed application architecture where IoT devices are contacting microservices running on a Kubernetes cluster. There are numerous potential points of failure, and data points are continuously logging every transaction. Sifting through massive data stores to pinpoint the root cause of an issue can be extremely time intensive for the team. Humans weren’t built for this kind of work. This is where artificial intelligence and machine learning thrive. With machine learning, we can build models to analyze patterns hidden within these mountains of data.
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It can recognize abnormalities, identify the underlying cause and provide suggestions for potential optimization. Through this predictive analysis, machine learning can not only help us identify problems eroding our systems.
It can recognize abnormalities, identify the underlying cause and provide suggestions for potential optimization. Through this predictive analysis, machine learning can not only help us identify problems eroding our systems, but also trap issues before they become problems. By performing early prediction and notification, we can address concerns as they step their way through the development pipeline, so few ever reach production. AI and machine learning can analyze usage data and security threats to help us optimize our applications. It can inspect user behavior to identify what application modules and functions are doing the heaviest lifting so we can focus our efforts on improving the user experience in these areas. We can also compare current releases to previous ones to be alerted to subtle performance degradations.
Vendors are actively creating impressive tools to integrate with DevOps processes, Some IT departments are hoisting this responsibility on themselves, creating custom AI solutions tailored specifically to their business needs. .
By continuously evaluating user behavior, AI can help us keep user experience at the forefront of our release planning. In tracking security threats with AI, we can readily see where hackers are trying to breach our systems so we can fortify our defenses. If a denial-of-service attack is directed at the organization, we can have a decision engine kick in to minimize the impact on the business. Rogue hackers aren’t the only threat AI can help reign in. It can churn through data in real time to spot fraudulent activity tied to unusual data patterns. There are no moral victories discovering $100,000 has been lost when an employee has been sypho DevOps brings automation and consistency to our release process. Try as it might, there are still areas that require a person to manage the process. With AI, we can continue to automate tedious, mundane tasks that are rife for human error. This automation frees up valuable IT resources to focus on innovative solutions.ning it off over the past year.
Not only can we let AI automate our DevOps process, we can also take it a step further to self-heal problems without human intervention. Not ready to let the computers manage themselves? AI can recommend solutions for writing more efficient and performant code. It can even prioritize the anticipated impact of a change so the development team has direction when sizing up what should be addressed next. Some may say, we are essentially talking about AIOps. To a degree, this is true. Yet, the argument can be made that clear boundaries don’t exist marking where DevOps ends and AIOps begins. The overlap between the two can be significant, and AIOps is quickly becoming an indispensable part of the toolkit for DevOps practitioners. This isn’t Star Trek. We aren’t pondering about the technology of tomorrow. We can implement artificial intelligence and machine learning into our DevOps environment today. Vendors are actively creating impressive tools to integrate with DevOps processes. Some IT departments are hoisting this responsibility on themselves, creating custom AI solutions tailored specifically to their business needs.
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IoT Tech News | July 26, 2018
Automotive giant Ford has decided its self-driving efforts are important enough to warrant a separate company with $4 billion of investment. Ford Autonomous Vehicles LLC will be based in Detroit, Michigan and will be tasked with developing the company’s self-driving technology. Jim Hackett, President and CEO of Ford, explained the decision: “Ford has made tremendous progress across the self-driving value chain – from technology development to business model innovation to user experience. Now is the right time to consolidate our autonomous driving platform into one team to best position the business for the opportunities ahead.”