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Cloud Services / Tech Culture

This Week in Programming: Natural Born Skeptics

Apr 19th, 2019 4:00pm by
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I don’t know about you, but the moment I hear the words “next-generation technology” the hairs on the back of my neck stand up, my spidey sense tingles, and I start listening carefully to see if the words I’m hearing have any tangible meaning, or if they all just allude to something that’s never ever said.

During my stint doing public relations for technology startups, this was among the phrases that I would always be on the lookout for. It was my personal mission to rid any press release I could of phrases like “next-generation,” “industry first,” and “leverage.” (That last one is just a pet peeve of mine.) Conventional wisdom might say that it’s my roots, having spent years actually using technology at a low level, that would leave me a skeptic. As such, most developers it seems fall into this same category of technological skeptic — they’ll believe it when they put it into use and it works and not a moment sooner.

In an article this week, The New Stack analyst Lawrence Hecht takes a look at some recent numbers regarding buzzwords like AIOps and blockchain, noting shifting developer opinions despite marketing efforts.

“We all hate when marketers cynically rebrand their existing products with the latest buzzword,” writes Hecht. “Just don’t close your eyes to real industry trends because of this tawdry phenomenon.”

Personally, having moved more into the writing-about-it business and less so in the using-it business, I struggle to balance my own skepticism. And so I turn to others for a dose of skepticism, such as developer Jessie Frazelle, who this week penned a related blog post on the topic, titled Questions I’d Ask My Cloud Provider, as well as several tweets on the topic of what Anthos, the multicloud platform announced by Google last week, actually does. In the blog post, Frazelle offers three basic questions, starting off with “what problem is this solving?” writing that “So many people tend to buy into the hype for ‘shiny,’ they miss if they even needed the thing in the first place. […] So often these features seem to be built for fun or based off a feeling a product manager had.”

Frazelle doesn’t appear to be alone, with a number of others chiming in on the thread. One, for example, offers that perhaps the point is to simply check off a bunch of buzzwordy boxes.

Others, meanwhile, offer some takes that toe the line between skepticism and cynicism.

While you can take a look for yourself and decide whether or not Google needs to up its copywriting game, there are definitely others out there that say Anthos has a definite purpose and attempt to describe it.

Industry analyst Janakiram MSV wrote a piece this week for Forbes explaining everything you want to know about Anthos, Google’s hybrid and multicloud platform. And despite that “next-generation technology” phrase appearing just once (along with “leverage”), MSV offers an explanation that seems grounded in reality, starting out with a concession:

“Anthos is different from other public cloud services. It’s not just a product but an umbrella brand for multiple services aligned with the themes of application modernization, cloud migration, hybrid cloud, and multicloud management.

Despite the extensive coverage at Google Cloud Next and, of course, the general availability, the Anthos announcement was confusing. The documentation is sparse, and the service is not fully integrated with the self-service console. Except for the hybrid connectivity and multicloud application deployment, not much is known about this new technology from Google.”

From there, he goes on to describe all of the “core building blocks” that comprise Anthos before offering some analysis on “Google’s Kubernetes Landgrab.” Calling Anthos “a bold move by Google,” MSV writes that the company “is taking a calculated risk in moving away from the clichéd hybrid cloud narrative that its competitors are using to lure enterprises” and “aims to become the VMware of [the] container ecosystem.”

So, dear (skeptical) developer, what is your take? Is Anthos all huff and puff? Or will it help enterprises do the things they need to do to solve real and existent problems? Is it simply a problem of copywriting, or will no level of explanation satisfy your hesitations?

This week wasn’t super heavy in the news realm, but we have a few select tidbits for you nonetheless, so read on…or get lost in the world programming spacecraft in the 1960s…

This Week in Programming

  • Twitter Adjusts Its API Rate Limits…Again: Ever the stalwart tracker of what Twitter is doing with its API, ProgrammableWeb this week has the story of how the company will adjust API rate limits for its User Timeline API and Mentions Timeline API beginning later this year. “The company insists the changes being made to its most commonly used API endpoints are to ensure that the APIs are being used in a ‘fair and consistent manner,'” they write. “Twitter hinted that it may not be able to keep its public APIs open and broadly accessible should it discover they are being abused.” The limits will begin June 19 and will limit total GET requests to the v1.1 /statuses/mentions_timeline and /statuses/user_timeline endpoints to 100,000 requests per day. Twitter explained in a blog post that “this limit allows us to make concrete progress to combat inappropriate use of our developer platform, while isolating the impact to the developers using these endpoints the most.” The company also said that it plans to use developer feedback over the next two months to help it fine-tune its approach. For further details, an FAQ is available as well as documentation.
  • Keeping It Simple, Stupid: InfoWorld has the tale of how Microsoft aims for simplicity with Bosque programming language, a new open source project that aims to “build a functional programming language that avoids ‘accidental complexity’ in the development process.” The Bosque language project has design goals that “include improved developer productivity, better software quality, and enablement of a range of new compilers and tool experiences” and position the language as “an experiment in regularized design for a machine-assisted, rapid, and reliable software development lifecycle.” A key point of the language is for it to be “simple and easy to comprehend for both machines and humans.” Currently, documentation and examples are available on GitHub, with tutorials in the works but make sure to check out the InfoWorld article for a much more in-depth description of the language features.

  • You are standing in an open field… : It’s probably been a decade or three since you’ve read the opening words to Zork, “one of the earliest interactive fiction computer games,” but if you’re anything like me, you remember it with a mix of fondness and frustration. Well, now you can see the source code for Zork, Hitchhiker’s Guide, and other Infocom games over on GitHub in “A collection of historical source files, for education and perusal.” The project includes 140+ mostly Infocom games from that nascent era of computer gaming, which offer quite a glimpse at how things were done back then. For example, the description of Arthur offers the following: “This repository is a directory of source code for the Infocom game “Arthur,” including a variety of files both used and discarded in the production of the game. It is written in ZIL (Zork Implementation Language), a refactoring of MDL (Muddle), itself a dialect of LISP created by MIT students and staff. […] In general, Infocom games were created by taking previous Infocom source code, copying the directory, and making changes until the game worked the way the current Implementor needed. Structure, therefore, tended to follow from game to game and may or may not accurately reflect the actual function of the code.” Enjoy the time warp.
  • So, How Long Do You Think That Will Take? I don’t know about you, but I fear those words, and this week, Erik Bernhardsson takes a look at why software projects take longer than you think. “Anyone who built software for a while knows that estimating how long something is going to take is hard. It’s hard to come up with an unbiased estimate of how long something will take, when fundamentally the work in itself is about solving something,” Bernhardsson writes. “Funny thing is I’ve had this gut feeling for a while. Adding up estimates rarely works when you end up with more than a few tasks. Instead, figure out which tasks have the highest uncertainty – those tasks are basically going to dominate the mean time to completion.” For the interested, make sure to check out the code for his statistical model and the discussion on Hacker News and on Reddit.

Feature image by photosforyou from Pixabay.

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