"Oracle does not plan to provide additional browser-specific plugins as such plugins would require application developers to write browser-specific applets for each browser they wish to support," the company said in a white paper that outlines migration options for developers. "Moreover, without a cross-browser API, Oracle would only be able to offer a subset of the required functionality, different from one browser to the next, impacting both application developers and users." The main alternative proposed by the company is to switch from Java Applets to Java Web Start applications. This type of application can be launched from the Web without the need for a browser plug-in.
Government agencies approach risk management in different ways, and some may have more mature approaches than others. Additionally, governments need to deal with the fact that residents increasingly expect “24/7 access to government information and services, on mobile devices, without regard for how government develops, manages and pays for that access and those services.” The report says that local governments need to become “technologically proficient” in order to “identify, assess and manage technology risks.” There are four different ways that local governments can achieve this goal, the report notes.
As for the integration challenge, 61% indicated that it remains a major pain. In fact, a quarter of the respondents said that at least one cloud application project was abandoned due to the inability to link enterprise data to the cloud applications. While I expect that proportion to decline over time, due to improved tools and smarter implementation teams, it will remain a challenge. An important corollary to the need to integrate external cloud apps to internal on premises data is the fact that we now have a two-way challenge. The rise of XaaS means that many organizations now have valuable data in the cloud that needs to be accessed by their on-premises systems.
Security is a cross-functional concern a bit like Performance. And a bit unlike Performance. Like Performance, our business owners often know they need Security, but aren’t always sure how to quantify it. Unlike Performance, they often don’t know “secure enough” when they see it. So how can a developer work in a world of vague security requirements and unknown threats? Advocating for defining those requirements and identifying those threats is a worthy exercise, but one that takes time and therefore money. Much of the time developers will operate in absence of specific security requirements and while their organization grapples with finding ways to introduce security concerns into the requirements intake processes, they will still build systems and write code.
You will certainly need some folks with Hadoop skills, database/data management skills, system admin skills, programing skills and analytics skills. Currently, the market isn’t oversaturated with Hadoop admins that possess all of these skills along with several deployments and a few years of management experience under their belts ... As for the data scientist, they’re great if you can find one (and afford him/her). You’re talking about someone who gets statistics, algorithms, coding, data and database technologies and the underlying business logic. In many cases, companies are leveraging the skills of multiple individuals already on staff as opposed to hiring a dedicated data scientist.
Unikernels take the concept of minimalistic operating systems to the next level. It is a specialized OS which is compiled exclusively for the program that runs on it. So, a developer can create an extremely compact executable that not only has his code but even the operating system. Unikernels are single-user, single-process, single-purpose, specialized operating systems that strip away unwanted functionality at the compile time resulting in a stand-alone, self-contained unit. The new unit of deployment contains the entire software stack of system libraries, language runtime, and application, compiled into a single bootable VM image that runs directly on a standard hypervisor.
Over the past year, machine learning has gone mainstream in an unprecedented way. The trend isn't fueled by cheap cloud environments and ever more powerful GPU hardware alone; it’s also the explosion of frameworks now available for machine learning. All are open source, but even more important is how they are being designed to abstract away the hardest parts of machine learning, and make its techniques available to a broad class of developers. Here’s a baker's dozen machine learning frameworks, either freshly minted or newly revised within the past year.
Despite a booming R&D budget, the research done within Microsoft's labs rarely got productized, as I've written before. Or, as Ahmad Abdulkader, an engineer on Facebook's applied machine learning team, and formerly of Microsoft and Google, told Bloomberg, "Microsoft totally separated its research arm from the rest of the company and almost made it optional to contribute to the rest of the company. Google took the exact opposite approach." This sometimes left Microsoft scrambling to catch up with innovations released elsewhere. Under CEO Satya Nadella, Microsoft's R&D team is actively engaging with product teams to ensure all those R&D billions contribute to tens of billions in sales. But, this isn't the clearest sign of Microsoft's rebirth.
Unfortunately, this dual infrastructure approach rests on several false premises. The first is that startup DevOps teams are all using open source software, and that this is what enables agile application development. The reality is far different. Most startup DevOps teams use a lot of paid software and services out of necessity because they don’t have the time or resources to customize and tie together a bunch of open source applications to meet their IT infrastructure needs. If they did spend the time building this infrastructure themselves they would never get their businesses off the ground. Drawing on scores of on staff engineers and deep pockets, only the biggest of the big tech companies are building IT infrastructures that are based on open source and their own custom-built software.
The typical solution is to spend a lot of the corporate strategy team’s time and money on streamlining the strategic planning process and clarifying the accompanying instructions. This does make a difference, but strategists will be much more likely to help managers consider the long-term – and so help the firm make good long-term decisions – if they spend less time on planning process and more on counteracting executives’ operational mindsets. CEB data show that this is six times more successful in terms of improving long-term thinking during the strategic planning process.
Quote for the day:
"Whenever an individual or a business decides that success has been attained, progress stops." -- Thomas J. Watson