Kinda wish there were more details on this page to understand or interpret what the author is talking about or compared it to.
I have a Canon 9000F (consumer grade) that is getting very old now and often difficult to get running when I pull it out, but it scans film at 2400dpi which has been adequate for my home archival purposes. I don't know if this is in the ballpark of what the author used as the comparison for the consumer scanner (nor is the DPI cited). About 8 years ago I was going to start a new film scanning project and thought "Hey, maybe now's the time to buy an updated film scanner" but I learned there is very little on the consumer market and it's gotten very expensive.
I think the 9000f hasn't been made in a while but I still find it to be a great scanner when I need this.
There are a couple of sample zooms at the very end of the page comparing an X1 (6300dpi) to the best the author could get on a consumer scanner (unspecified dpi, but fuzzy). The range given is 6300dpi-8000dpi for the scanners the author's talking about.
As I'm WFH next to my Synology and look down at my ESD bag-wrapped spare WD Red, I can't help but be reminded of Peter Graves glancing down at his tray with a perfectly cleaned fishbone in "Airplane!"
It's not a horrible place to work. I've worked at Microsoft and work for Amazon now. It's unavoidable that with a company the size of Amazon there will be some (maybe a lot) of bad areas to work and it's obvious that despite even the best hiring practices in the world, you'll find people winding up in a position for which they are not a good fit.
There's a lot of interesting work, though, and a lot of people happy working on it. I wouldn't tell anyone it's the best place to work or that it's "better" to work than another place, but I love what I do and work with hundreds of people who (more or less) feel the same. I also know people who don't feel this way and I encourage them to move on or move out because nobody should be in a job they really dislike (and I'm aware of the incredible privilege that's reflected by my ability to say that).
KIRO TV in Seattle did a small test of impairment on a closed course with participants using varying amounts of marijuana a few years ago around the time Washington voters were choosing to legalize pot and found similar results:
I don't know if it's statistically valid, but I've used methods similarly based on this to do calculations like you're talking for a role similar to what you described.
There are more subtleties that it might be important for you to take into account - primarily:
1) need to sample fairly extensively before/after outage to calibrate more accurately against Holt-Winters (the Holt-Winters seasonal projection should accurately project the trend, but actual numbers are probably running at some slight or significant rate above/below projections)
2) When running those samples, it's important to sample data where you believe the data points are definitely not impacted by the outage. This is often quite challenging since outages sometimes might span low / peak traffic periods or ramp-up/down periods.
3) Finally, it can be hard to pinpoint the actual start / end of the event (the identify the time samples you want to consider in your measurement for the outage cost). Particularly the end, since there's often some pressure for queued operations (by software or by your users who are itching to complete what they were trying to do) that may make your samples fluctuate. That backfill pressure can be substantial and is important to not ignore in your measurement of the actual cost of the issue. Say you're a retail site - if you have a 15 minute period of 50% order drop but the first 5 minutes where service is restored, the total order rate was 50% above projections. Do you count that as 15 minutes of 50% order drop, or 10 minutes of 50% order drop? Both are legitimate but it's important to know what metric you're measuring yourself against so you're as correct / honest as you can be.
1. This is a good point. I haven't incorporated sampling after the outage into the analysis, but that should be a good qualitative measure of the accuracy of the forecast.
2. I typically have good data from server logs of when an outage started. Outages during low volume periods are quite difficult to analyze though. I usually revert to just comparing the outage volume to the average volume for the whole outage period.
3. The end is typically more difficult to determine, as there's typically a period of instability as servers are restarted sporadically, followed by a "recovery" caused by the backfill pressure that you mentioned. My solution is to count any samples above the forecast's confidence interval as "recovery" and to subtract the total recovery from the loss estimate.
but essentially you're likely to find many models of software (from large software vendors) with a lot of different models for how you can try / use / own it. My sense is that most commercial software vendors want you to use their software and want you to get it legitimately and want to find a way where you can pay what vaguely seems like it should be mutually agreeable (if you're using it educationally, there are often ways to get it for free, if you're a developer for a large organization, they want that organization to actually pay for it and support the value they're getting out of you using it).
I worked on MS Office and I once remember Sinofsky (then in charge of Office) once talking about the pricing structure of Office and saying nobody paid the ~$400 MSRP. People get it bundled with new computers, pay substantially lower upgrade fees, or something else. I don't remember if he went so far as to say "at some level, people pirate it" but that's a reality that only the really oblivious would ignore. The point is - try stuff out, see what you like, and try to figure out what makes you the most productive without worrying about "some day I won't be able to afford this" (but by all means you should also rabble-rouse if you find the prices for the software you use are unreasonable and inflexible).
Call me a nitpicker and you'd be right, but the screenshots in this[1] and other ads[2] where they showcase this watch for GPS navigation while on a bike (or motorcycle) where the watch is not doing a 90 degree rotation on the content area so you can read it while your hands are on some handlebars really bugs me. I guess it bugs me more than some model getting on a motorcycle wearing what looks like a blazer with no helmet or gloves, too.
But to make this comment, say, 20% hn worthy, can someone explain whether it's unrealistic that I think the accelerometer should be able to figure out the "holding handlebars with forward velocity" scenario and orient the display properly?
Yeah, but this isn't to produce a drinkable brew. It's not even a super different projection from the brew time when I've homebrewed (which has been a while but was probably closer to 6 hours for me to get it into the primary fermentation tub). This thing looks pretty cool, but I'm interested in seeing more on the whole setup / maintenance and, especially, cleaning.
I have a Canon 9000F (consumer grade) that is getting very old now and often difficult to get running when I pull it out, but it scans film at 2400dpi which has been adequate for my home archival purposes. I don't know if this is in the ballpark of what the author used as the comparison for the consumer scanner (nor is the DPI cited). About 8 years ago I was going to start a new film scanning project and thought "Hey, maybe now's the time to buy an updated film scanner" but I learned there is very little on the consumer market and it's gotten very expensive.
I think the 9000f hasn't been made in a while but I still find it to be a great scanner when I need this.