(Note: I did this in Chrome – it’ll be a little different in other browsers)
I have several complaints about the book of the face – not least of which is that it likes to reset your News Feed from “Most Recent” (aka most useful) to “Top Stories” (aka whatever Facebook wants you to see).
I also like to avoid the fluff off the other columns (ads, games, groups, pages, chat, etc) when all I want is the most recent stream. So, after some searching, fiddling, and tweaking, I now have my news feed (and only my news feed) appear on the side of my screen in chronological order.
How to do what I did:
install the Auto Refresh extension for Chrome (only if you want the news feed to automatically update)
The news story making the rounds about Facebook the past few days indicates they’re working on a kind of “dislike” button.
The problem with the Facebook “like” button is the same problem Google has with Google+ and their “+1” button: it doesn’t tell you anything meaningful.
Voting on Reddit doesn’t really convey much meaning, either.
Stack Overflow tries to address this with its up/down voting and being able to see the gestalt votes as a ratio (if your rep is high enough (an admittedly low bar, but till a bar, and an aspect of the gamification of Stack Oveflow)). But that doesn’t really cut it, either.
The problem with online “voting” (or “liking”, or “plussing”, etc) is that it is a dimensionless data point.
Does getting 300 “likes” on a post make it “good”? Does it reflect on its quality in any way? How about getting nearly 400 upvotes (and only a handful of downvotes) on a question about MySQL (along with 100+ “favorites”) mean the question is good? Does it show something is popular? Are people clicking the vote mechanism out of peer pressure, because they actually agree, or because they think it needs more visibility?
Dimensionless data that gets used as if it has meaning is a problem – one of many problems of social media and web sites in general.
Of course, you will object, quality is a potentially-subjective term – what does “quality” mean, exactly, when talking about a post, website, question, etc? Is it how well-written it is? Is it how long? How funny? How sad?
Reddit has upvotes and downvotes – and your comment/post score is merely the sum of the ups and downs; below a certain [relative] threshold, you won’t see content unless you ask for it.
One of the biggest problems with all of these systems is that the “score” doesn’t actually tell you anything. An atheist subreddit, for example, will tend to downvote-into-oblivion comments that are theistic in nature (especially from Christians). Quora‘s voting system is highly untransparent – downvotes don’t really seem to mean much, and upvotes are pretty much just for show.
This derives from the fact that these sites use dimensionless data and try to give it a value or meaning outside of what it really is – a number.
What should be shown is the total number of “votes” a given post has gotten – positive negative, reshare, etc – but never combined. A ratio could be displayed, but the sum of the votes is a poor plan.
Facebook, Google+, and others should offer various voting options – “up”, “down”, “disagree”, “agree”, “share”, and possibly others – some of which may be mutually-exclusive (you cannot upvote and downvote the same thing), but you might downvote something you agree with (or upvote something you disagree with) just because of how it is written/presented, etc.
And the total of each type of click should be shown – show me 10,000 people disagreed with what I said, 15,000 agreed; 20,000 upvoted, and 30,000 downvoted; 12,000 reshared it (with, or without, comment).
Using voting as a means of hiding things (and trying to prevent others from seeing them) can be somewhat akin to online bullying – revenge voting has its problems; as does blindly upvoting anything a particular person says/does. Which is why assigning (and then displaying) dimensionless data anything more than a count is dangerous.
In follow-up to a post from 2013, and earlier this year, I’ve been working on a pointy-clicky deployable MooseFS+ownCloud atop encrypted file systems environment you can rent/buy as a service from my company.
I’ve also – potentially – kicked-off a new project from Bitnami to add MooseFS to their apps list.
Multipliers. They’re ubiquitous – from ratchet wrenches to fertilizer, blocks-and-tackle to calculators, humans rely on multipliers all the time.
Multipliers are amazing things because they allow an individual to “do more with less” – a single person can build a coral castle with nothing more complex than simple machines. Or move 70 people at 70 miles per hour down an interstate merely by flexing his foot and twitching his arm.
Feats and tasks otherwise impossible become possible due to multipliers.
Automation is a multiplier. Some automating is obviously multiplicative – robots on assembly lines allow car manufacturers to output far more vehicles than they could in the pre-robot era. Even the assembly line is an automating force, and multiplier regarding the number of cars that could be produced by a set number of people in a given time period.
In the ever-more-constrained world of IT that I orbit and transit through – with salary budgets cut or frozen, positions not backfilled, and the ever-growing demands of end-users (whether internal or external), technicians, engineers, project managers, and the like are always being expected to do more with the same, or do more with less.
And that is where I, and the toolsets I work with, come into play – in the vital-but-hidden world of automation. Maybe it’s something as mundane as cutting requisition-to-delivery time of a server or service from weeks to hours. Maybe it’s something as hidden as automatically expanding application tiers based on usage demands – and dropping extra capacity when it’s no longer needed (one of main selling points of cloud computing). The ROI of automation is always seen as a multiplier – because the individual actor is now able to Get Things Done™ and at least appearsmarter (whether they are actually any smarter or not is a totally different question).
Every day we all work at multiple levels of abstraction.
Perhaps this XKCD comic sums it up best:
But unless you’re weird and think about these kinds of things (like I do), you probably just run through your life happily interacting at whatever level seems most appropriate at the time.
Most drivers, for example, don’t think about the abstraction they use to interact with their car. Pretty much every car follows the same procedure for starting, shifting into gear, steering, and accelerating/decelerating: you insert a key (or have a fob), turn it (or push a button), move the drive mode selection stick (gear shift, knob, etc), turn a steering wheel, and use the gas or brake pedals.
But that’s not really how you start a car. It’s not really how you select drive mode. It’s not really how you steer, etc.
But it’s a convenient, abstract interface to operate a car. It is one which allows you to adapt rapidly to different vehicles from different manufacturers which operate under the hood* in potentially very different ways.
The problem with any form of abstraction is that it’s just a summary – an interface – to whatever it is trying to abstract away. And sometimes those interfaces leak. You turn the key in your car and it doesn’t start. Crud. What did I forget to do, or is the car broken? Did I depress the brake and clutch pedal? Is it in Park? Did I make sure to not leave the lights on overnight? Did the starter motor seize? Is there gas in the tank? Did the fuel pump quit? These are all thoughts that might run through your mind (hopefully in decreasing likelihood of probability/severity) when the simple act of turning the key doesn’t work like you expect.
For a typical computer user, the only time they’ll even begin to care about how their system really works is when they try to do something they expect it to do … and it doesn’t. Just like drivers don’t think about their cars’ need for the fuel injector system to make minute adjustments thousands of times per second, most people don’t think about what it actually takes to go from typing “www.google.com” in their browser bar to getting the website returned (or how their computer goes from off to “ready to use” after pushing the power button).
Automation provides an abstraction to manual processes (be it furniture making or tier 1 operations run book scenarios). And abstractions are good things .. except when they leak (or outright break).
Depending on your level of engagement, the abstraction you need to work with will differ – but knowing that you’re at some level of abstraction (and, ideally, which level) is vital to being the most effective at whatever your role is.
I was asked recently how a presentation on the benefits of automation would vary based on audience. The possible audiences given in the question were: engineer, manager, & CIO. And I realized that when I’ve been asked questions like this before, I’ve never answered them wrong, but I’ve answered them very inefficiently: I have never used the level of abstraction to solve the general case of what this question is really getting at. The question is not about whether or not you’re comfortable speaker to any given “level” of customer representative (though it’s important). It is not about verifying you’re not lying about your work history (though also important).
No. That question is about finding out if you really know how to abstract to the proper level (in leakier fashions as you go upwards assumed) for the specific “type” of person you are talking to.
It is vital to be able to do the “three pitches” – the elevator (30 second), the 3 minute, and the 30 minute. Every one will cover the “same” content – but in very different ways. It’s very much related to the “10/20/30 rule of PowerPoint” that Guy Kawasakipromulgates: “a PowerPoint presentation should have ten slides, last no more than twenty minutes, and contain no font smaller than thirty points.” Or, to quote Winston Churchill, “A good speech should be like a woman’s skirt; long enough to cover the subject and short enough to create interest.”
The answer that epiphanized for me when I was asked that question most recently was this: “I presume everyone in the room is ‘as important’ as the CIO – but everyone gets the same ‘sales pitch’ from me: it’s all about ROI. The ‘return’ on ‘investment’ is going to look different from the engineer’s, manager’s, or CIO’s perspectives, but it’s all just ROI.”
The exact same data presented at three different levels of abstraction will “look” different, even though it’s conveying the same thing – because the audience’s engagement is going to be at their level of abstraction (though hopefully they understand at least to some extent the levels above (and below) themselves).
A simple example: it currently takes a single engineer 8 hours to perform all of the tasks related to patching a Red Hat server. There are 1000 servers in the datacenter. Therefore it takes 8000 engineer-hours to patch them all.
That’s a lot.
It’s a crazy lot.
But I’ve seen it countless times in my career. It’s why patching can so easily get relegated to a once-a-year (or even less often) cycle. And why so many companies are woefully out-of-date with their basic systems from known issues. If your patching team consists of 4 people, it’ll take them a year to patch all 8000 systems – and then they just have to start over again. It’d be like painting the Golden Gate Bridge – an unending process.
Now let’s say you happen to have a management tool available (could be as simple as pssh with preshared SSH keys, or as big and encompassing as Server Automation). And let’s say you have a local mirror of RHN – so you can decide just what, exactly, of any given channel you want to apply in your updates.
Now that you have a central point from which you can launch tasks to all of the Red Hat servers that need to be updated, and a managed source from which each will source their updates, you can have a single engineer launch updates to dozens, scores, even hundreds of servers simultaneously – bringing them all up-to-date in one swell foop. What had taken a single engineer 8 hours is still 8 – but it’s 8 in parallel: in other words, the “same” 8 hours is now touching scores of machines instead of 1 at a time. The single engineer’s efficiency has been boosted by a factor of, say, 40 (let’s stay conservative – I’ve seen this number as high as 1000 or more).
Instead of it taking 8000 engineer-hours to update all 1000 servers, it’s now only 200. Your 4 engineer patching team can now complete their update cycle in well under 2 weeks. What had taken a full year, is now being measured in days or weeks.
The “return on investment” at the abstraction level of the engineer is they have each been “given back” 1900 hours a year to work on other things (which helps make them promotable). The team’s manager sees an ROI of >90% of his team’s time is available for new/different tasks (like patching a new OS). The CIO sees an ROI of 7800 FTE hours no longer being expended – which means the business’ need for expansion, with an associated doubling of server estate, is now feasible without having to double his patching staff.
Every abstraction is like that – there is a different ROI for a taxi driver on his car “just working” than there is for a hot rodder who’s truly getting under the hood. But it’s still an ROI – one is getting his return by being able to ferry passengers for pay, and the other by souping-up his ride to be just that little (or lot) bit better. The ROI of a 1% fuel economy improvement by the fuel injector system being made incrementally smarter in conjunction with a lighter engine block might only be measured in cents per hour driving – but for FedEx, that will be millions of dollars a year in either unburned fuel, or additional deliveries (both of which are good for their bottom line).
Or consider the abstraction of talking about financial statements (be they for companies or governments) – they [almost] never list revenues and expenditures down to the penny. Not because they’re being lazy, but because the scale of values being reported do not lend themselves well to such mundane thinking. When a company like Apple has $178 billion in cash on hand, no one is going to care if it’s really $178,000,102,034.17 or $177,982,117,730.49. At that scale, $178 billion is a close-enough approximation to reality. And that’s what an abstraction is – it is an approximation to the reality being expressed down one level. It’s good enough to say that you start your car by turning the key – if you’re not an automotive engineer or mechanic. It’s good enough to approximate the US Federal Budget at $3.9 trillion or maybe $3900 billion (whether it should be that high is a totally different topic). But it’s not a good approximation to say $3,895,736,835,150.91 – it may be precise, but it’s not helpful.
I guess that means the answer to the question I titled this post with is, “the level of abstraction appropriate is directly related to your ‘function’ in relation to the system at hand.” The abstraction needs to be helpful – the minute it is no longer helpful (by being either too approximate, or too precise), it needs to be refined and focused for the audience receiving it.
The big complaint I had while writing that was that I wanted to use ownCloud, but it doesn’t Just Work™ on CentOS 6*.
After finishing the tutorial, I decided to do some more digging – because ownCloud looks cool. And because it bugged me that it didn’t work on CentOS 6.
What I found is that ownCloud 8 doesn’t work on CentOS 6 (at least not easily).
The simple install guide and process really is about version 8, and the last one that can be speedy-installed is 7. And as everyone knows, major version releases often make major changes in how they work. This appears to be very much the case with ownCloud going from 7 to 8.
In fact, the two pages needed for installingownCloud are so easy to follow, I see no reason to copy them here. It’s literally three shell commands followed by a web wizard. It’s almost too easy.
You need to have MySQL/MariaDB installed and ready to accept connections (or use SQLite) – make a database, user, and give the user perms on the db. And you need Apache installed and running (along with PHP – but yum will manage that for you).
If you’re going to use MooseFS (or any other similar tool) for your storage backend to ownCloud, be sure, too, to bind mount your MFS mount point back to the ownCloud data directory (by default it’s /var/www/html/owncloud/data). Note: you could start by using local storage for ownCloud, and only migrate to a distributed setup later.
Pros of Pydio
very little futzing needed to make it work with CentOS 6
very clean user management
very clean webui
light system requirements (doesn’t even require a database)
What about other cloud environments like Seafile? I like Seafile, too. Have it running, in fact. Would recommend it – though I think there are better options now than it (including ownCloud & Pydio).
*Why do I keep harping on the CentOS 6 vs 7 support / ease-of-use? Because CentOS / RHEL 7 is different from previous releases. I covered that it was different for the Blue Grass Linux User Group a few months ago. Yeah, I know I should be embracing the New Way™ of doing things – but like most people, I can be a technical curmudgeon (especially humorous when you consider I work in a field that is about not being curmudgeonly).
Guess this means I really need to dive into the new means of doing things (mostly the differences in how services are managed) – fortunately, the Fedora Project put together this handy cheatsheet. And Digital Ocean has a clew of tutorials on basic sysadmin things – one I used for this comparison was here.