Today: Visual Studio Code fueled Microsoft's decade-long enterprise winning streak, but new challenges loom, why Google and Microsoft are forcing you to use their AI tools, and the latest enterprise moves.
Visual Studio Code is a vital pieces of Microsoft's enterprise strategy, which banks on the goodwill developers have for both products to drive business to Azure and its other enterprise software products. But software development practices and preferences are changing rapidly.
AI use cases are becoming more powerful and pervasive across the software delivery lifecycle, but adopting any new technology comes with some risks. Nine members of our Roundtable discussed how technology leaders can reap the benefits of AI software-development tools while avoiding the pitfalls.
Visual Studio Code is a vital pieces of Microsoft's enterprise strategy, which banks on the goodwill developers have for both products to drive business to Azure and its other enterprise software products. But software development practices and preferences are changing rapidly.
AI use cases are becoming more powerful and pervasive across the software delivery lifecycle, but adopting any new technology comes with some risks. Nine members of our Roundtable discussed how technology leaders can reap the benefits of AI software-development tools while avoiding the pitfalls.
Even companies eager to jump on the GenAI bandwagon have struggled to organize their data and get past deployment hurdles, and nobody likes to spend all that time, effort, and money to build technology that can't be shipped because it can't be trusted.
Figma's collaboration tools are a hit with designers thanks to its decision to take a page from the gaming software playbook and rebuild its databases for "infinite scale."
Like many companies that have grown through acquisitions over the years, Rajesh Naidu's job involves integrating those acquisitions onto a common tech stack, which requires taking a hard look at the SaaS applications used by those companies.
A convoluted series of mergers, acquisitions, and divestitures had left Cushman & Wakefield with "hundreds" of separate enterprise-resource planning applications. It wanted a flexible but standardized base to get everyone on the same page.
For many years financial services companies Principal Financial Group started its transition to the cloud just before the pandemic made the need for modern digital services an existential crisis, and has only accelerated that process since Kathy Kay came on board.
AWS didn't ignore AI during Garman's presentation Tuesday, but it spent a significant amount of time on the services that turned it into a $100-billion a year enterprise computing powerhouse: compute, storage, and databases.
Despite recent challenges to their hegemony, x86 chips still power the vast majority of cloud and on-premises servers in use today. However, over all those years Intel and AMD tweaked x86 in subtle but incompatible ways to suit their own needs, and Tuesday's agreement is a promise to unify x86.
This week a U.K. regulatory agency published summaries of hearings it conducted this past July with AWS, Microsoft, and Google Their responses provide an interesting look into how the cloud providers see themselves, their competitors, and the current state of the market.
For years, Oracle tried to convince longtime database customers who wanted to shed their on-premises data centers to run those databases on Oracle's public infrastructure cloud, slamming AWS at every turn. Times have changed.
Most enterprises are still struggling to turn their generative AI experiments into actual production applications. They've done more than 99% of the work, but the last 1% has proven much harder than anticipated, according to AWS's Swami Sivasubramanian.
This era of enterprise software is either the dawn of a new era of corporate productivity or the most hyped money pit since the metaverse. ServiceNow's Amit Zavery talks about the impact of generative AI, how SaaS companies should think about AI models, and his decision to leave Google Cloud.
Anyscale is built around Ray, an open-source project that was designed to help AI workloads scale. But in recent years, commercial pressures have forced several companies with similar open-source origin stories to put restrictions on their projects to ward off competition.
In an interview at the Data Cloud Summit, Ramaswamy described how enterprise customers are working with generative AI, outlined growth opportunities for Snowflake's future, and lamented the "insular" culture at Google that denied it the opportunity to lead the generative AI transition.
GitHub Copilot users will be able to swap in AI models from Anthropic and Google in place of the default models from OpenAI. When the flagship product of the generative AI era takes such a step, it's a sign OpenAI's leadership position is waning.
Openings for tech jobs regularly generate an overwhelming number of applications, partly because remote work is more common and AI tools are automating the process. That creates a significant burden on both hiring organizations and would-be employees.
After Cockroach Labs announced earlier this month that CockroachDB would switch to a proprietary model, Oxide Computer Company decided to take a unique approach to preserving its investments in Cockroach's open-source software.
There are lots of companies interested in generative AI apps with money but limited skills. They'll need helpful platform tools to get up and running, and competition in this category could set the tone for the enterprise AI era.
Nobody has any idea when a real quantum computer will actually impact enterprise tech, but NIST wants companies to upgrade their security sooner rather than later.
A software update with one more variable than expected crashed 8.5 million Windows computers. Should Windows security vendors continue to have access to the kernel?
The shared-responsibility model is groaning under the weight of the modern security environment. Snowflake's ongoing nightmare should be a wake-up call for any infrastructure or SaaS provider that they need to do more to protect their customers, because the old model is no longer working.
Global teams across an enterprise are likely to speak different languages, of course, but also might be using different keyboard layouts with different characters. Those differences can lead to confusion about password requirements that could hinder collaboration and even compromise security.
No one really agrees on a strict definition of "agent," but recent breakthroughs in large-language models have allowed companies to build enhanced versions of chatbots that can respond to natural-language queries with a plan of action.
Now that open data formats are here to stay, unifying them to remove incompatibilities will be a challenge. Delta Lake and Iceberg get all the attention, but tech developed by the creators of Hudi could make it happen.
Tech and media leaders are increasingly worried that the push to use generative AI to automate analytical business tasks could produce a generation of workers that never develop the foundation to do the job well at a senior level.
As Snowflake and Databricks gear up for back-to-back user conferences in early June, their customers are increasingly betting on open storage formats that give them new flexibility.
