Virus-Inspired Virtue Signaling by Attention Hungry AI Developers
April 22, 2020
An article at HackerNoon describes several uses of AI that have an impact on society—some that went very wrong and some that are going quite right. It ponders “The Future of Artificial Intelligence: To Kill or To Heal?” The article covers the issue of biased AI, using the example of the US criminal justice system. It also discusses the resistance in most countries to governments’ use of facial recognition software. While China’s use of the technology to control its citizens has been largely (and rightly) decried, the write-up asserts it has been very useful in containing the spread of the novel coronavirus in that country. See the article for details. AI has also been helping address the pandemic through the use of machine learning to track disease around the globe. We’re told:
“BlueDot is an AI platform that uses NLP and machine learning to track infectious diseases across the globe. It does this by employing algorithms that rapidly browse a multitude of sources. The algorithms are designed to flag early signs of epidemics. In the last weeks of December 2019, the platform recognized a cluster of ‘unusual pneumonia’ diagnoses in Wuhan, China. A little over a week later, the World Health Organization (WHO) came out with an official statement on the existence of a ‘novel coronavirus’ in a patient in Wuhan. BlueDot isn’t the only AI that can flag areas of concern across thousands of sources. Alibaba, a global E-commerce powerhouse, created StructBERT, which is powered by NLP models. The models are capable of processing viral gene-sequences at a fast rate, as well as screening proteins. Alibaba has put the platform to use in the fight against COVID-19. It is freely available to researchers and scientists who can use the information and technology to speed the development of vaccines.”
Then there is the search for a cure. One recent paper describes a machine learning model from Deargen, a firm out of South Korea. The model has identified four possible antiviral meds that might just mitigate COVID-19. Another paper, this one from Hong Kong’s Insilico Medicine, reveals that firm’s AI platform is busy modeling thousands of novel molecules in the hope of turning up one that can disrupt the virus’ replication.
Keep in mind that there are more AI solutions solving virus problems than DarkCyber can monitor. It is easier to count wonky infection data than get AI to deliver more than lists of probables to investigate.
Cynthia Murrell, April 22, 2020
The JEDI Knight Wounds Amazon
April 17, 2020
The Bezos bulldozer has stalled against a bureaucratic stone wall. The overheated engine is idling in outside the Pentagon Metro stop. DarkCyber was informed by a couple of helpful readers that the US government is going Microsoft for the significant Joint Enterprise Defense Infrastructure Project. A representative summary of the review of the contract process appeared in “Pentagon: $10B Cloud Contract That Snubbed Amazon Was Legal.” The write up reported:
“We could not review this matter fully because of the assertion of a ‘presidential communications privilege,’ which resulted in several DOD witnesses being instructed by the DOD Office of General Counsel not to answer our questions about potential communications between White House and DOD officials about JEDI,” the report said.
“As a result, we could not be certain whether there were any White House communications with some DOD officials which may have affected the JEDI procurement,” it said.
“However, we believe the evidence we received showed that the DOD personnel who evaluated the contract proposals and awarded Microsoft the JEDI cloud contract were not pressured … by any DOD leaders more senior to them, who may have communicated with the White House,” the report said.
Clear enough. Amazon’s bulldozer may have to reverse and head over to other Executive Branch agencies. Copies of the Bezos bulldozer have been spotted in Australia pushing insurance data and in United Arab Emirates moving digital sand for the government.
The problem for Amazon is that displacing PowerPoint is a very, very tough mountain to move. Just ask Google. Palantir’s baby forklift moved some paperwork while forming a relationship with a certain figure of note in Washington, DC.
Maybe Amazon should wear a fashionable Azure T shirt and wear a Dwarven Ring of Power from The Lord of the Rings available on Etsy?
Stephen E Arnold, April 17, 2020
Online Pricing: Analysis Misses the Door to the Bank
April 13, 2020
I spotted a discussion about online pricing written in 2018. The focus was Google. “Would Google Search Make More Money If They Charged 1 Cent per Search?” contains some interesting information. In fact, the write up underscores how those wearing blindfolds outside the online sector wake up in the dark only to discover they have been swallowed by a whale. (How did that work out for Jonah?)
The write up contains an analysis by Jasper who does “a little back of the napkin calculation.” The results are that Google could charge for each search and possibly generate more than it generates from online advertising.
Rop-ke, another participant in the discussion, points out:
But to tell you the truth, people would search a lot less if they were charged money per search.
In fact, Rop-ke pointed out that “Google will die.”
Alenda made clear that the free Craigslist killed newspapers. (Well, not quite, but Craigslist added to the hurt.)
The most recent comment about this article appeared on April 12, 2020. I quote:
They would until someone replaced them with a free service.
Several observations may be warranted:
- There are times when people will pay for online information. The most common is a “must have” situation. What would you pay for an online search for an antidote to save your child from death by poisoning? What would a person like Harvey Weinstein pay for an online LexisNexis search as part of his effort to avoid further prosecution in Los Angeles? The idea is that “must have” information will cause people to pay.
- Asking people to pay for online information splits the user base into two groups: Those who will pay to use the service and to have access if the service is needed. In general, only a small number of online information services can stay generate enough revenue to make the online service into a sustainable business.
- The modes of online access have shifted dramatically in the last 30 years. In 1980, one needed a separate device like a Texas Instruments Silent 700; today one can do a search talking to a smart television set. Most of those searching are not aware that their actions are an online search. The lack of awareness creates a clueless mass which can be converted to revenue.
How do online companies make money today? Let me highlight a few of the more popular approaches:
- Selling data either directly or indirectly. The user’s actions are the bits that matter. Even cash strapped enforcement agencies will pay for data when the investigation warrants.
- Online is a stepping stone to other businesses. Example? Online sales. The Amazon model is built upon search. Want a cloud service? Do a free search of the AWS documentation. The motivation is gratification like buying an eBook or shifting to the cloud so pesky information technology staff can be riffed.
- Online search facilitates a new type of revenue stream. If you want to make a fortune in digital currency, you need to find a digital wallet. Then you need to find a “how to.” For those providing that information, the payoff comes from getting their hands around money churn.
The problem with selling online information is that it is difficult to generate sustainable revenue, cover the infrastructure and other costs, and spin a profit. But when online provides options for other streams of revenue, the digital bits can be like gold dust.
Will Google charge for search? Maybe, but the company is charging to use its search infrastructure. The company offers a Microsoft Office killer for a fee. Google sells phones, mostly not so good, but like the Loon balloons, the company is trying. One can also rent the Google plumbing for cloud computing.
I am fond of pointing out that Google has one business model, a model it obtained in a moment of inspiration from Yahoo. Google was more clever than Yahoo’s management. Google has been more clever than many companies.
Will that cleverness come to an end when a better search engine comes along? Not likely. For now, online search seems easy to do and monetize. Every human construct winds down. But with Google’s seemingly free services rolling along, the firm has momentum. Its tie up with Apple suggests that no quick changes will occur.
What does persist? Some misunderstandings about the costs of offering online information in either free or for fee mode. I remarked decades ago that online is a fairly tricky business to make pay even for criminals selling contraband on the Dark Web.
Imagine how difficult it is for LexisNexis to pay for the technological debt it has strapped to its back. Most online companies are in the same slog. The New York Times talks about its rapidly growing online business. What the NYT doesn’t say is that the cost of its missteps in online which began when Jeff Pemberton’s in house online system was terminated with extreme prejudice. Yeah, I know the current crop of NYT managers will ask, “Technical debt. Who’s Jeff Pemberton?”
The cloud of unknowing about online continues to swell just like the ad revenues from search at Amazon, Facebook, and Google. These are not habits; they are addiction. There’s money in serving addicts: Perceived must havism.
Stephen E Arnold, April 13, 2020
Stephen E
Enterprise Search: Not Exactly Crazy but Close
April 13, 2020
I think I started writing the first of three editions of the Enterprise Search Report in 2003. I had been through the Great Search Procurement competition for the US government’s search system. The original name for the service was FirstGov.gov (the idea was that the service was the “first” place to look for public facing government information. The second name was USA.gov, and it was different from FirstGov because the search results were pulled from an ad supported Web index.
The highlight of the competition was Google’s losing the contract to Fast Search & Transfer. (Note: The first index exposed to the public was the work of Inktomi, a company mostly lost in the purple mists of Yahoo and time.) Google was miffed because Fast Search & Transfer had teamed with AT&T and replied to the SOW with some of the old fervor that characterized the company before Judge Green changed the game. I recall one sticking point: Truncation. In fact, one of the Google founders argued with me about truncation at a search conference. I pointed out that Google had to do truncation whether the founders wanted to or not. My hunch is that you don’t know much about truncation and what it contributes. I won’t get into the weeds, but the function is important. Think stemming, inflections, etc.
I examined more than 60 “enterprise” search systems, including the chemical structure search systems, the not-so-useful search tools in engineering design systems like AutoCAD, and a number of search systems now long forgotten like Delphis and Entopia, among others.
I have also written “The New Landscape of Search” published by Pandia and “Successful Enterprise Search Management” with Martin White, who is still chugging along with his brand of search expertise. Of course, I follow search and retrieval even though I have narrowed my focus to what I call intelware and policeware. These are next-generation systems which address the numerous short coming of the oversold, over-hyped, and misunderstood software allowing a commercial enterprise to locate specific items of interest from their hotchpotch of content.
In this blog, Beyond Search/DarkCyber I write about some enterprise search systems. In general, I remain very critical of the technologies and the mostly unfounded assertions about what a search-and-retrieval system can deliver to an organization.
With this background, I reacted to “Enterprise Search Software Comparison” with sadness. I was not annoyed by the tone or desire to compare some solutions to enterprise content finding. My response was based on my realization about how far behind understanding of enterprise search’s upsides and downsides, the gap between next-generation information retrieval systems and the “brand” names, and the somewhat shallow understanding of the challenges enterprise search poses for licensees, vendors, and users.
The write up “compares” these systems as listed in the order each is discussed in the source article cited above:
- IBM Watson Discovery
- Salesforce Einstein Search
- Microsoft Search
- Google Cloud Search
- Amazon Kendra
- Lucidworks
- AlphaSense.
Each of these system merits a couple of paragraphs. For comparison, the discussion of systems in the Enterprise Search report typically required 15 or more pages. In CyberOSINT, I needed four pages for each system described. I had to cut the detail to meet the page limit for the book. A paragraph may be perfect for the thumb typing crowd, but detail does matter. The reason is that a misstep in selecting enterprise software can cost time and money and jobs. The people usually fired are those serving on the enterprise search system procurement team. Why? CFOs get very angry when triage to make a system work costs more than the original budget for the system. Users get angry when the system is slow (try 120 seconds to find a document in a content management system and then learn the document has not been indexed), stakeholders (the investment in search cannot be recovered without tricks, often illegal), and similar serious issues.
Let’s look at each of these systems described in the write up. I am going to move forward in alphabetical order. The listing in the source implies best to worst, and I want to avoid that. Also, at the end of this post, I will identify a few other systems which anyone seeking an enterprise search system may want to learn about. I post free profiles at www.xenky.com/vendor-profiles. The newer profiles cost money, and you can contact me at benkent2020 at yahoo dot com. No, I won’t give you a free copy. The free stuff is on my Xenky.com Web site.
AlphaSense. This is a venture backed company focused on making search the sharp end of a business intelligence initiative. The company is influenced by Eric Schmidt, the controversial Xoogler. The firm has raised about $100 million. The idea is to process disparate information and allow users to identify gems of information. AlphaSense competes with next-generation information services like DataWalk, Voyager Labs, and dozens of other forward looking firms. Will AlphaSense handle video, audio, time series data, and information stored on a remote workers’ laptop? Yeah. To sum up: Not an enterprise search solution; it is a variant of intelware. That’s no problem. AlphaSense is a me too of a different category of software.
Amazon Kendra. Amazon has a number of search solutions. This is Lucene. Yes, Lucene can deliver enterprise search; however, the system requires a commitment. Amazon’s approach is to put enterprise search into AWS. There’s nothing quite like the security of AWS in the hands of individuals who have not been “trained” in the ways of Amazon and Lucene.
Google Cloud Search. This is the spirit of the ill fated Google Search Appliance. The problems of GSA are ameliorated by putting content into the Google Cloud. What’s Google’s principal business? Yep, advertising. Those Googlers are trustworthy: Infidelity among senior managers raises this question, “Can we trust you to keep your body parts out of our private data?” You have to answer that question for yourself. (Sorry. Can’t say. Legal eagles monitor me still.)
IBM Watson Discovery. Okay, this is Lucene, home brew, and acquired technology like Vivisimo. Does it work? Why not ask Watson. IBM does have robust next-generation search, but that technology like IBM CyberTap is not available to the author of the article or to most commercial organizations. So IBM has training wheels search which requires oodles of IBM billable hours. Plus the company has next-generation information access. Which is it? Why not ask Watson? (If you used ITRC in the 1980s, you experienced my contribution to Big Blue. Plus I took money. None of that J5 stuff either.)
Salesforce Einstein Search. If a company puts its sales letter and contacts into this system, one can find the prospect and the email a salesperson sent that individual. Why do company’s want Salesforce search? When a salesperson quits, the company wants to make sure it has the leads, the sales story, etc. There are alternatives to Salesforce’s search system. Why? Maybe there are sufficient numbers of Salesforce customers who want to control what’s indexed and what employees can see? Just a thought.
Microsoft Search. I would like to write about Microsoft Search. (Yep, did a small thing for this outfit.) I would like to identify the acquisitions Microsoft completed to “improve” search. I would like to point out that Microsoft is changing Windows 10 search again. But that’s the story. One flavor of Microsoft Search is Fast Search & Transfer. It is so wonderful that a competitive solution is available from outfits like Surfray, EPI Server, and even Coveo (yep, the customer support and kitchen sink vendor). Why? Microsoft Search is very similar to the Google search: Young people fooling around in order to justify their salaries and sense of self worth. The result? I particularly like the racist chat bot and the fact that Microsoft bought Fast Search & Transfer as the criminal case for financial fraud was winding through Norway’s court system. Yep, criminal behavior. Why? Check out my previous write ups about Fast Search & Transfer.
Lucidworks. Okay, I did some small work for this outfit when it was called Lucid Imagination. Then the revolving door started to spin. The Lucene/Solr system collected many, many millions and started its journey to … wait for it… digital commerce and just about anything that could be slapped on open source software. Can one “do” enterprise search with Solr? Sure. Just make sure you have money and time. Lucidworks’ future is not exactly one that will thrill its funding sources. But there is hope for an acquisition or maybe an IPO. Is Lucidworks a way to get “faceted search” like Endeca offered in 1998? Sure, but why not license Endeca from Oracle? Endeca has some issues, of course, but I wanted to put a time mark in this essay so the “age” of Lucidworks’ newest ideas are anchored with a me-too peg.
What vendors are not mentioned who can implement enterprise search?
I will highlight three briefly, just to make clear the distortion of the enterprise market that this article presents to a thumb typing millennial procurement professional:
- Exalead spawned a number of interesting content companies. One of them is Algolia. It works and has some Exalead DNA.
- SearchIT is an outfit in Europe. It delivers what I consider a basic enterprise search system.
- Maxxcat produces a search appliance which is arguably a bit more modern than the Thunderstone appliance.
- Elastic Elasticsearch. This is the better Compass. How many outfits use Elasticsearch? Lots. There’s a free version and for-fee help when fans of Shay Bannon get stuck. Check out this how to.
There are others, of course, but my point is that mixing apples and oranges gives one a peculiar view of what is in the enterprise search orchard. It is better to categorize, compare and contrast systems that perform “enterprise search” functions. What are these? It took me 400 pages to explain what users expect, what systems can deliver, and the cost/engineering assumptions required to deliver a solution that is actually useful.
Search is hard. The next-generation systems point the way forward. Enterprise search has, in my opinion, not advanced very far beyond the original Smart system or IBM STAIRS III.
PS. Notice I did not use the jargon natural language processing, semantics, text analytics, and similar hoo haa. Why? Search has a different meaning for each worker in quite distinct business units. Do you expect a chemical engineer looking for Hexamethylene triperoxide diamine to use a word or a chemical structure? What about a marketing person seeking a video of a sales VP’s presentation at a client meeting yesterday? What about that intern’s Instagram post of a not-yet-released product prototype? What about the information on that sales VP’s laptop as he returns to his home office after a news story appeared about his or her talk? What about those human resource personnel data files? What about the eDiscovery material occupying the company’s legal team? What about the tweet a contractor sent to a big client about the cost of a fix to a factory robot that trashed a day’s production? What about the emails between an executive and a sex worker related to heroin? (A real need at a certain vendor of enterprise search!) Yeah! Enterprise search.
Stephen E Arnold, April 13, 2014
Amazon: More Than Warehouse Staff Hired?
April 10, 2020
Google and Microsoft are taking away some of Amazon’s growing technological power. Jeff Bezos is not happy that, so AWS is hiring more people. What is the logic behind that? The Register explains why in the article, “AWS To Double Sales Droids As. Google, Microsoft’s Growing Clouds Threaten To Gobble Larger Slices of Bezos’ Pie.”
Due to the growing amount of sales Google and Microsoft are making in their cloud departments, AWS is hiring more sales people. AWS hopes that by increasing their sales staff they will make more sales and steal customers away from its rivals. These will not be regular sales people, though. AWS is hiring experts in security, AI, and data analytics. AWS will not reveal the size of its sales team or the exact number of people its hiring. Supposedly there are thousands on the team.
AWS currently dominants the cloud computing market at 32.3%. Microsoft has 16.9% and Google has 5.8% of the market. Will that growth last in 2020?
“But the Jeff-Bezos-run titan’s enormous growth has begun to slow recently as other providers catch up. Of the big four cloud providers, Google grew the most last year, swelling 87.8 per cent, Microsoft came in second, with 64 per cent growth. Alibaba was close behind with 63.8 per cent. But AWS’s growth, at 36 per cent, was half that of its nearest rival. AWS still posted the biggest revenue increase in absolute terms – with $9.2bn compared with Microsoft’s $7.1bn – but many saw the pair’s recent financial results as an early sign that rival services were beginning to catch up with Bezos’ behemoth.”
Google also plans to triple its size team, while Microsoft is trying to poach AWS’s cloud clients. So far Microsoft has been successful. The best example is that Microsoft won the Department of Defense’s $10 billion decade-long JEDI IT supply deal. AWS did not like that business decision, so AWS appealed and the courts will decide if the contract was fairly awarded.
The new hiring is the biggest business move from AWS in years. AWS wants to focus less on its basic services that assists organizations in developing products to actually building the finished product themselves and selling them. The battle is on for the cloud market, but it looks like thugs are going to go the Google way. Google controls most of western searches and AWS will control most cloud computing systems.
Whitney Grace, April 10, 2020
A Minor Point about Google Wave
April 9, 2020
I read “Google Wave’s Failure is a Great Lesson for Modern Real-Time Collaboration Tools.” I sure don’t want to get in a digital squabble. Revisionism is a respected skill at this time. The article points out:
The idea to focus on communication came from Jens who noticed a significant shift in the way people interacted online. The consensus between the brothers was that they should build a platform that would reflect those changes in its functionality.
I would suggest checking out Dr. Alon Halevy (who was Alon Levy for a while). He wrote:
I was the CEO of Megagon Labs from November 2015 until December 2018. Prior to Megagon, I headed the Structured Data Group of Google Research in Mountain View, California for a decade (here are a few thoughts about that decade). I joined Google in 2005 with the acquisition of my company, Transformic. Prior to that, I was a professor of Computer Science at the University of Washington, where I founded the UW CSE Database Group in 1998. You can follow me on Twitter for more (un)frequent updates. In the past, I used to blog and maybe I’ll return to it some day.
He added:
My group is responsible for Google Fusion Tables, a service for managing data in the cloud that focuses on ease of use, collaboration and data integration. Fusion Tables enables users to upload spreadsheets, CSV and KML files and share them with collaborators or with the public. You can easily integrate data from multiple sources (and organizations) and use a collection of visualizations to look at your data. In particular, Fusion Tables is deeply integrated with Google Maps, making it easy to visualize large geographic data sets. To facilitate collaboration, users can conduct fine-grained discussions on the data. You can see some examples of how Fusion Tables is being used. You can interact with Fusion Tables through our UI or our API.
The source for these quotes is https://homes.cs.washington.edu/~alon/.
With thousands of Googles, why did I focus on Dr. Halevy. The name change was a signal to which I attended. With a bit of work, one can locate slide decks which explain some of the functionality Dr. Halevy brought to Google.
Did Dr. Halevy inform the younger Googlers?
My research for Google Version 2: The Calculating Predator (Infonortics (now out of business says, “Yes.” Dr. Halevy had a significant impact on Google and influenced the company’s efforts in surveillance, data transformation, and collaborative services.
But as one of my friends says to me when we talk, “Nobody cares.” I would add that many of those waiting about Google are unaware of Transformics. That’s too bad. There was a reason why the Google acquired the firm. What is Dr. Halevy contributing to Facebook. Those early Transformic slide decks and Dr. Halevy’s technical papers may yield some insights. But that’s work. Better to go with revisionism.
Stephen E Arnold, April 9, 2020
Virtual China: Beefing Up
April 3, 2020
I want to keep this brief. “Tencent to Build AI Supercomputing Center, Industrial Base in Shanghai.” So what’s new? The write up states:
The internet titan and the city’s Songjiang district government signed an deal today to deepen collaboration in areas such as AI…
DarkCyber noted this checklist:
The center will undertake various large-scale AI algorithm calculations, machine learning, image processing, and scientific and engineering computing tasks based on Tencent’s AI capabilities, and provide cloud computing services to the whole of society with data processing and storage capabilities…
Edge computing? Smart manufacturing? Intercept and data analytics?
Check, check, check.
Stephen E Arnold, April 3, 2020
Nervous about AI? Google Uses It and You Do Too
April 2, 2020
Despite the deployment of smart speakers, virtual assistants, language translation automation, and many other technologies we use every day, AI still feels like a future innovation. We are probably stuck on the idea that AI means walking, talking robots, but AI, in fact, is already part of our daily lives. Techni Pages wrote, “5 Uses Of Advanced AI Already Being Used By Google” to demonstrate how AI is currently being used.
Have you ever sent a text message using the voice-to-text feature on your mobile phone? Surprise, that is a form AI! Human language is very complex and in order for machines to understand it, Google uses Deep Neural Networks to model language sounds. Current endeavors have designed voice-to-text to be faster, siphon out more noise, and more accurate.
Google Maps is another huge AI project. Powered by real time predictions, Google Maps delivers the fastest route to destinations. It takes into consideration accidents, traffic, and constructions so users can avoid those hindrances. The Google Assistant is another AI tool that acts as your own personal assistant to perform Internet searches, schedule appointments, set reminders, and make simple notes. Gmail also uses AI to categorize emails and filter spam from your inbox.
Google offers the Cloud AutoML too:
“The Cloud AutoML is an advanced AI that helps developers to create other AI smart solutions. The machine learning models are of high quality and enable developers to create AI that suits their business needs. Cloud AutoML has state-of-the-art performance and also enables the machine learning to happen with minimal effort since it uses neural architecture search technology and transfer learning.”
Google is an industry leader in developing innovative AI tools. The AI tools we use might not be robots, but they are very helpful.
Whitney Grace, April 2, 2020
Zoom: Room for Improvements and Hardly a Joke
April 1, 2020
Yesterday a former CEO asked me, “Who is this Ben guy?” The question was in bounds. Since I signed up for Zoom three or four years ago, I sniffed the Silicon Valley outfit and learned that there was some smart money from the Middle Kingdom supporting the operation. Further poking around revealed mixed signals about security. Despite the nice looking interface, some effort was taken years ago to omit, obscure, or misdirect one’s attention from some basic functions. Then there was icon litter. There’s the lack of statefulness when one leaves a meeting from the Zoom Web site to an instant meeting on a user’s computer. There are other oddities if not efforts to do a digital magician’s trick.
The Facebook data thing has been publicly exposed, and allegedly Zoom has cleaned up its act. The Zoom bombs featuring people exposed some individuals who follow the dress code of Adam and Eve have been revealed.
I spotted “Zoom Meetings Aren’t End to End Encrypted, Despite Misleading Marketing.” News on March 31, 2020. Not exactly a revelation to our Ben fellow, but the information is now public:
Zoom is using its own definition of the term, one that lets Zoom itself access unencrypted video and audio from meetings.
Now where does that information go? Maybe the Middle Kingdom?
Ben’s Zoom set up involves:
- A prepaid credit card which is used to pay for the “pro” service
- An email created just for Zoom
- A network separated Mac Mini just for video conferences
- A hot spot so that traffic flows through a pre paid service, not DarkCyber’s regular provider
- No use of Zoom cloud recording
- Turn off anything that allows an attendee to fiddle around
- Ignore in meeting message functions.
Not perfect but for those students who had a bit of a surprise when Zoom bombed, our approach has prevented this type of revelation.
Stephen E Arnold, April 1, 2020
Microsoft Azure: The Reoccurring Blues
March 30, 2020
On a call this weekend, a person mentioned this explanation: “Microsoft Details Impact of Coronavirus on Cloud Services Usage.” The main idea is that “A 775 percent increase in overall cloud services usage in those regions that have enforced social distancing or shelter in place orders.”
Short version: Microsoft’s cloud services do not scale seamlessly.
That “gee, Microsoft is good to me” explanation is interesting, just muffled by snuggling.
This morning (March 30, 2020), the DarkCyber news feed presented this interesting write up: “Microsoft Teams Not Working Again – Here’s What You Need to Know.” This write up reports:
Research from online outage watchdog Downdetector saw a huge spike in complaints concerning Microsoft Teams at 9am BST as much of the UK and Western European workforces came online.
Let’s assume that the snuggle report and the down again report are accurate. DarkCyber concludes:
- Not even Microsoft’s influence can snuff out grousing about its online collaboration Teams service. (Skype? Ho, ho, ho)
- Microsoft hopes to build the cloud centric services for the US Department of Defense. Sounds good, but will the outage and scaling blues color the deal. (An armed conflict? Sorry may not make the DoD comfortable.)
- The yipyap about automatic scaling, failover, and redundancy is definitely marketing baloney. (Down means fail, doesn’t it?)
Net net: Microsoft’s cloud like the Amazon and Google clouds are billing machines. The complexity almost guarantees problems. Google’s follow through on stuff that does not work; Amazon’s magical invoices with mysterious line items; and now Microsoft’s magic.
Silver or azure bullets? Ho, ho, ho.
Stephen E Arnold, March 30, 2020
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