CA’s BTCS2.1: Where Do We GrOw From Here?
Jun14

CA’s BTCS2.1: Where Do We GrOw From Here?

At last week’s second annual Built to Change Summit CA Technologies updated analysts and journalists on where it and the markets it’s pursuing — primarily DevSecOps, with a heaping helping of mainframe — are, where they’re going, and how the software toolmaker will grab a bigger slice of the rapidly growing digital transformation (DT) pie, which is being largely driven by software, and more specifically, applications. While the money being lavished on DT and DevSecOps are staggering, CA’s ability to grow with this opportunity remains at best a work in progress, with relatively flat sales and forecasts. Based on the market data, CA should be in the DT/DevSecOps sweet spot, and poised for rapid and sustainable growth. According to a new report, IDC’s forecast for the global DevOps software market — in excess of $5.6 billion by 2021 — was way off. MarketsandMarkets predicts that CA’s future has a much bigger potential upside — $10.31 billion by 2023 — up from $3.42 billion in 2018. Even better for CA, the market growth will be powered ‘due to the increase in the adoption rate of Artificial Intelligence (AI) and machine learning among enterprises.’ So all that remains to be seen is if CA can continue to grow with the software-enabled, data-driven, digital transformation business phenomenon that will run on DevSecOps, while reducing, if not eliminating, the shackles of its legacy businesses and embraces software-as-a-service and more flexible pay-as-you-go consumption models. It faces many competitors — including IBM, Micro Focus (HPE), Puppet, Red Hat, Microsoft and Chef Software — and must continue to innovate at speed, and execute with precision and agility. That’s a lot to ask, but for a company that’s been around since 1976, probably not too much. Automation, AI and ML were front and center at BTCS 2, and while the company didn’t coin this phrase — “Software is eating the world but AI is eating software” — it was critical to the company’s future, said Ashok Reddy, Group GM, DevOps. He and other company execs, made it clear that artificial intelligence and machine learning were being aggressively pursured in a multitude of initiatives and products. Just prior to the summit, CA’s CTO and EVP Otto Berkes said there is “massive potential” to apply machine learning and machine intelligence. amd that the company has some “very pragmatic solutions” already in the market, and is doing a “lot of experimentation” on machine learning and machine intelligence. They figured prominently in last weeks product initiatives, as well as a number of its boundary-stretching initiatives, i.e. CA Accelerator, its internal fail-fast venture-capital program, and its Strategic Research intiative, under which a...

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Intel Makes AI Understandable and Accessible…

Though they populate an industry that prides itself on tackling and solving complex puzzles, many IT vendors prefer simplistic story-telling. That’s partly due to simplicity being easier to sell than complexity, even if it fails to address many or even most of the issues related to complicated engineering efforts. But simple tales also feed the industry’s love of self-promotional mythologies, including the triumph and massive remuneration of plucky entrepreneurs. I raise this issue because storytelling shorthand also tends to infect areas where accuracy is a critical component, like still-emerging technologies. Keeping things easy may seem to be beneficial in terms of helping an audience initially understand difficult subjects. But relying on simplistic exposition can also mask over-inflated claims and promote questionable reports about a technology’s potential for commercial success. We’ve seen this dynamic occur many times in the past—virtual reality headsets and associated technologies are just one good example. More than four years after Facebook paid an unprecedented $2B for VR start-up Oculus—a deal that was supposed to rapidly propel VR into the commercial mainstream—the industry and vendors continues to be hindered by many of the same core technological barriers that existed in 2014. So, it’s a pleasure to find vendors that are willing and able to discuss complex work in both realistic and understandable terms. That was certainly the case at Intel DevCon 2018, the inaugural conference for artificial intelligence (AI) developers that Intel hosted recently in San Francisco. To read the complete article, CLICK HERE NOTE: This column was originally published in the Pund-IT...

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Will AI Keep Pure “growing like a bat out of hell”?
May31

Will AI Keep Pure “growing like a bat out of hell”?

Having accelerated from start-up to top-five vendor in the red-hot flash array market, Pure Storage is looking for new heights to scale. While it still has plenty of opportunity remaining in the storage segment, it is trying to broaden its horizons with a number of new initiatives, including a data-centric architecture, storage as a service and one of the latest buzzword-bingo catchphrases, artificial intelligence (AI) and machine learning (ML). “We were ahead of the market in all-flash,” said Pure Storage CEO Charlie Giancarlo in the earnings call earlier this month. “We were ahead of the market with NVMe. And we’re ahead of the market with AI.” At last week’s PURE//ACCELERATE 2018, its third annual customer/partner event, the company continued its AI push, which first surfaced with the NVIDIA partnership in March. It also made a number of other announcements intended to broaden its reach beyond just faster, smaller, less-complex and more-energy-efficient storage, which has fuelled its meteoric rise, including 40% year-over-year revenue growth last quarter.. “We’re guiding generally to 30+% year-on-year. We aspire to grow just as fast as we possibly can. Part of that is the market, part of that is one’s ability as a public company to scale without wanting to sacrifice quality,” said Giancarlo. “Last year was a great milestone for the company. We also have $1 billion in the bank. We are cash flow positive and are growing like a bat out of hell,” he added. “We’re not just enterprise storage. We’re in a very great place.” Pure faces stiff competition in its core business, the c (7%). However, it’s even further behind in the overall enterprise storage market, which rang up sales of $13.6 billion in Q4, compared to AFA’s $1.9 billion. Although it is looking at a total addressable market of $35 billion, the lights are much brighter in the AI segment, which is expected to generate $1.2 trillion in economic value this year, up 70% from 2017, and projected to add just under $4 trillion by 2022. “The interest in AI by corporations is just off the charts,” said Giancarlo in a recent interview. “At Pure, we are able to…feed GPUs, high speed applications, and AI environments — at the speed they want that data to provide the intelligence companies want to make their businesses better.” He said since AI is all about crunching huge amounts of data, older, tiered storage systems that rank data by age aren’t nimble enough to grant researchers quick access to even the oldest data sets. “These days, people want access to data, whether it was last week or last year or last decade,” Giancarlo said. Pure...

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Flash, AI Help Fuel Record Growth, Bright Future For Pure Storage
May24

Flash, AI Help Fuel Record Growth, Bright Future For Pure Storage

SAN FRANCISCO: I’m in the City by the Bay attending PURE//ACCELERATE 2018, the third annual customer/partner event from Pure Storage, and it appears the enterprise flash storage vendor couldn’t have scripted the timing any better. In addition to its new partnership with NVIDIA — AI-Ready Infrastructure (AIRI), a ‘major move in serving the artificial intelligence (AI) and machine learning (ML) space’ — and its ongoing relationship with Cisco — i.e. as an Original Storage Manufacturer (OSM) — on Monday the company reported Q1 revenue of $255.9 million, up 40% YoY. “Pure has delivered another strong quarter as we lead the industry in delivering new data-centric architectures that enable enterprises to succeed both today and tomorrow,” said Pure CEO Charles Giancarlo, in a prepared statement. “The combination of our innovative business model, first-to-market technology innovations, and focus on customer success drove continued momentum in Q1.” In addition to record revenues, the company announced it had added 300 new customers during the quarter, bringing its installed base to amost 5,000 organizations. It forecast an even better Q2 — $296 million to $304 million — and approximately $1.345 billion for the year, up from 2017’s $1.023 billion, as well as a slightly higher net loss, $64.3 million compared to last year’s net loss of $57.2 million. “We were ahead of the market in all-flash,” said Giancarlo in the earnings call. “We were ahead of the market with NVMe. And we’re ahead of the market with A.I. (artificial intelligence).” At last year’s event — more than 3,000 customers, partners and staff (with another 2,000 online, for a total increase of 300% over 2016’s inaugural event) — the vendor was predicting at least three more years of 30%-plus revenue growth, surpassing the $2-billion annual revenue mark by 2020. It also stated that the total addressable market for its faster solid-state storage arrays is $35 billion, but according to Dave Vellante, chief analyst of Wikibon, Pure was involved in a knife fight, and a market ripe for consolidation. “If it can stay ahead of what I call the ‘storage cartel,’ it will emerge a winner.” Shortly after last year’s event the company hired Giancarlo, formerly the Cisco CTO and then Avaya CEO,  who took over as CEO in late August when Scott Dietzen was bumped up to chairman of the board. Late last year he told Zeus Kerravala, founder and principal analyst with ZK Research, that if “you had asked me at the beginning of 2017 if I would join a storage company, I would have said probably not. I was caught up in the conventional wisdom that the storage industry had reached its zenith,...

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Pure Storage: Empowering Artificial Intelligence

Today, Pure Storage announced the release of AI-Ready Infrastructure (AIRI), a major move in serving the artificial intelligence (AI) and machine learning space. The newly announced solution combines Pure Storage FlashBlade and NVIDIA DGX-1 technology. According to Pure Storage, it is the industry’s first integrated AI-ready infrastructure for deploying deep learning at scale. With AI and machine learning still relatively nascent technologies, the first question that comes to mind might be, “Why an integrated solution, and not just a reference architecture?” I can give you three answers: To read the complete article, CLICK...

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