投稿時間:2022-02-28 04:16:58 RSSフィード2022-02-28 04:00 分まとめ(19件)

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AWS	AWSタグが付けられた新着投稿 - Qiita	AWS CopilotでWorker Serviceを試す	https://qiita.com/Shigai/items/d4808075d4cc011c6abe	しかし、実際のWorkerServiceはそのようなものではなく、基本的にコンテナは常駐し、SQSをポーリングしメッセージがあるか確認する処理などは自前で実装する必要があります。	2022-02-28 03:08:30
技術ブログ	Developers.IO	「DDoS流行ってるの？」「うちには来てないよね？」をAWS Shieldで確認する方法 + 対策	https://dev.classmethod.jp/articles/check-ddos-by-aws-shield/	awsshield	2022-02-27 18:42:53
海外TECH	MakeUseOf	How to Manage Your Linux Clipboard Effectively Using CopyQ	https://www.makeuseof.com/manage-linux-clipboard-using-copyq/	How to Manage Your Linux Clipboard Effectively Using CopyQIf you find yourself repeatedly copying and pasting text URLs or images consider installing a clipboard manager like CopyQ on your Linux desktop	2022-02-27 18:30:13
海外TECH	MakeUseOf	How to Fix Video Lag in Microsoft Teams on Windows	https://www.makeuseof.com/windows-10-microsoft-teams-fix-video-lag/	microsoft	2022-02-27 18:15:13
海外TECH	DEV Community	Should Frontend Devs Care About Performance??	https://dev.to/bytebodger/should-frontend-devs-care-about-performance-3eg1	Should Frontend Devs Care About Performance I was recently talking to an architect at Amazon and he made a very interesting comment to me We were talking about the complexity of a given algorithm discussed in Big O notation and before we even got too far into the explanation he said I mean it s not like we need to worry too much about this After all we re frontend devs I found this admission to be extremely refreshing and it was entirely unexpected coming from someone in the Ivory Tower that is Amazon It s something that I ve always known But it was still really nice to hear it coming from someone working for the likes of a FAANG company You see performance is one of those subjects that programmers love to obsess about They use it as a Badge of Honor They see that you ve used JavaScript s native sort method then they turn up their nose and say something like Well you know That uses O log n complexity Then they walk away with a smug smirk on their face as though they ve banished your code to the dustbin of Failed Algorithms Smart Clients vs Dumb TerminalsThe terms smart client and dumb terminal have fallen somewhat by the wayside in recent decades But they re still valid definitions even in our modern computing environments Mainframe ComputingWay back in the Dark Ages nearly all computing was done on massive computers e g mainframes And you interacted with those computers by using a terminal Those terminals were often called dumb terminals because the terminal itself had almost no computing power of its own It only served as a way for you to send commands to the mainframe and then view whatever results were returned from the mainframe That s why it was called dumb Because the terminal itself couldn t really do much of anything on its own It only served as a portal that gave you access to the mainframe For those who wrote mainframe code they had to worry greatly about the efficiency of their algorithms Because even the mainframe had comparatively little computing power by today s standards More importantly the mainframe s resources were shared by anyone with access to one of the dumb terminals So if people sitting at dumb terminals all sent resource intensive commands at the same time it was pretty easy to crash the mainframe This is also why the allocation of terminals was very strict and even those who had access to mainframe terminals often had to reserve time on them PC ComputingWith the PC explosion in the s suddenly you had a lot of people with a lot of computing power relatively speaking sitting on their desktop And most of the time that computing power was underutilized Thus spawned the age of smart clients In a smart client model every effort is made to allow the client to do its own computing It only communicates back to the server when existing data must be retrieved from the source or when new updated data must be sent back to that source This offloaded a great deal of work off of the mainframe down to the clients and allowed for the creation of much more robust applications A Return To Mainframe Computing Sorta But when the web came around it knocked many applications back into a server terminal kinda relationship That s because those apps appeared to be running in the browser but the simple fact is that early browser technology was incapable of really doing much on its own Early browsers were quite analogous to dumb terminals They could see data that was sent from the server in the form of HTML CSS But if they wanted to interact with that data in any meaningful way they needed to constantly send their commands back to the server This also meant that early web developers needed to be hyper vigilant about efficiency Because even a seemingly innocuous snippet of code could drag your server to its knees if your site suddenly went viral and that code was being run by hundreds or thousands of web surfers concurrently This could be somewhat alleviated by deploying more robust backend technologies For example you could deploy a web farm that shared the load of requests for a single site Or you could write your code in a compiled language like Java or C which helped somewhat because compiled code typically runs faster than interpreted code But you were still bound by the limits that came from having all of your public users hitting a finite set of server computing resources The Browser AS Smart ClientI m not going to delve into the many arguments for or against Chrome But one of its greatest contributions to web development is that it was one of the first browsers that was continually optimized specifically for JavaScript performance When this optimization was combined with powerful new frameworks like jQuery then Angular then React and it fostered the rise of the frontend developer This didn t just give us new capabilities for frontend functionality it also meant that we could start thinking again in terms of the desktop browser being a smart client In other words we didn t necessarily have to stay up at night wondering if that one aberrant line of code was going to crash the server At worst it might crash someone s browser And don t get me wrong writing code that crashes browsers is still a very bad thing to do But it s farrrrr less likely to occur when the desktop browser typically has all those unused CPU cycles just waiting to be harnessed So when you re writing say The Next Great React App how much exactly do you even need to care about performance After all the bulk of your app will be running in someone s browser And even if that browser is running on a mobile device it probably has loads of unleveraged processing power available for you to use So how much do you need to be concerned about the nitty gritty details of your code s performance IMHO the answer is simple yet nuanced Care But Not That MuchYears ago I was listening to a keynote address from the CEO of a public company Public companies must always understandably have one eye trained on the stock market During his talk he posed the question How much do I care about our company s stock price And his answer was that he cared but not that much In other words he was always aware of the stock price And of course he was cognizant of the things his company could do or avoid doing that would potentially influence their stock price But he was adamant that he could not make every internal corporate decision based upon one simple factor whether or not it would juice the stock price He had to care about the stock price because a tanking stock price can cause all sorts of problems for a public company But if he allowed himself to focus with tunnel vision on that stock price he could end up making decisions that bump the price by a few pennies but end up hurting the company in the long run Frontend app development is very similar in my eyes You should always be aware of your code s performance You certainly don t want to write code that will cause your app to run noticeably bad But you also don t want to spend half of every sprint trying to micro optimize every minute detail of your code If this all sounds terribly abstract I ll try to give you some guidance on when you need to care about application performance and when you shouldn t allow it to bog down your development Developer TrialsThe first thing you need to keep in mind is that your code will hopefully be reviewed by others devs This happens when you submit new code or even when someone comes by months later and looks at what you ve written And many devs LOVE to nitpick your code for performance You can t avoid these trials They happen all the time The key is not to get sucked into theoretical debates about the benchmark performance of a for loop versus the Array prototype function of forEach Instead you should try whenever possible to steer the conversation back into the realm of reality Benchmarking Based Upon RealityWhat do I mean by reality Well first of all we now have many tools that allow us to benchmark our apps in the browser So if someone can point out that I can shave a few seconds of load time off my app by making one or two minor changes I m all ears But if their proposed optimization only saves me a few microseconds I m probably gonna ignore their suggestions You should also be cognizant of the fact that a language s built in functions will almost always outperform any custom code So if someone claims that they have a bit of custom code that is more performant than say Array prototype find I m immediately skeptical But if they can show me how I can achieve the desired result without even using Array prototype find at all I m happy to hear the suggestion However if they simply believe that their method of doing a find is more performant than using the Array prototype find then I m going to be incredibly skeptical Your Code s Runtime Environment Reality is also driven by one simple question Where does the code RUN If the code in question runs in say Node meaning that it runs on the server performance tweaks take on a heightened sense of urgency because that code is shared and is being hit by everyone who uses the app But if the code runs in the browser you re not a crappy dev just because the tweak is not forefront in your mind Sometimes the code we re examining isn t even running in an app at all This happens whenever we decide to do purely academic exercises that are meant to gauge our overall awareness of performance metrics Code like this may be running in a JSPerf panel or in a demo app written on StackBlitz In those scenarios people are much more likely to be focused on finite details of performance simply because that s the whole point of the exercise As you might imagine these types of discussions tend to crop up most frequently during job interviews So it s dangerous to be downright flippant about performance when the audience really cares about almost nothing but the performance The Weight Of Data Types Reality should also encompass a thorough understanding of what types of data that you re manipulating For example if you need to do a wholesale transformation on an array it s perfectly acceptable to ask yourself How BIG can this array reasonably become Or What TYPES of data can the array typically hold If you have an array that only holds integers and we know that the array will never hold more than say a dozen values then I really don t care much about the exact method s you ve chosen to transform that data You can use reduce nested inside a find nested inside a sort which is ultimately returned from a map And you know what That code will run just fine in any environment where you choose to run it But if your array could hold any type of data e g objects that contain nested arrays that contain more objects that contain functions and if that data could conceivably be of nearly any size then you need to think much more carefully about the deeply nested logic you re using to transform it Big O NotationOne particular sore point for me about performance is with Big O Notation If you earned a computer science degree you probably had to become very familiar with Big O If you re self taught like me you probably find it to be onerous Because it s abstract and it typically provides no value in your day to day coding tasks But if you re trying to get through coding interviews with Big Tech companies it ll probably come up at some point So what do you do Well if you re intent upon impressing those interviewers who are obsessed with Big O Notation then you may have little choice but to hunker down and force yourself to learn it But there are some shortcuts you can take to simply make yourself familiar with the concepts First understand the dead simple basics O is the most immediate time complexity you can have If you simply set a variable and then at some later point you access the value in that same variable this is O It basically means that you have immediate access to the value stored in memory O n is a loop n represents the number of times you need to traverse the loop So if you re just creating a single loop you are writing something of O n complexity Also if you have a loop nested inside another loop and both loops are dependent upon the same variable your algorithm will typically be O n squared Most of the built in sorting mechanisms we use are of O log n complexity There are many different ways to do sorts But typically when you re using a language s native sort functions you re employing O log n complexity You can go deeeeeep down a rabbit hole trying to master all of the edge cases in Big O Notation But if you understand these dead simple concepts you re already on your way to at least being able to hold your own in a Big O conversation Second you don t necessarily need to know Big O Notation in order to understand the concepts That s because Big O is basically a shorthand way of explaining how many hoops will my code need to jump through before it can finish its calculation For example const myBigHairyArray thousandsUponThousandsOfValues const newArray myBigHairyArray map item gt tranformation logic here This kinda logic is rarely problematic Because even if myBigHairyArray is incredibly large you re only looping through the values once And modern browsers can loop through an array even a large array very fast But you should immediately start thinking about your approach if you re tempted to write something like this const myBigHairyArray thousandsUponThousandsOfValues const newArray myBigHairyArray map outerItem gt return myBigHairyArray map innerItem gt do inner tranformation logic comparing outerItem to innerItem This is a nested loop And to be clear sometimes nested loops are absolutely necessary but your time complexity grows exponentially when you choose this approach In the example above if myBigHairArray contains only values the logic will need to iterate through them one million times x Generally speaking even if you haven t the faintest clue about even the simplest aspects of Big O Notation you should always strive to avoid nesting anything Sure sometimes it can t be avoided But you should always be thinking very carefully about whether there s any way to avoid it Hidden LoopsYou should also be aware of the gotchas that can arise when using native functions Yes native functions are generally a good thing But when you use a native function it can be easy to forget that many of those functions are doing their magic with loops under the covers For example imagine in the examples above that you are then utilizing reduce There s nothing inherently wrong with using reduce But reduce is also a loop So if your code only appears to use one top level loop but you have a reduce happening inside every iteration of that loop you are in fact writing logic with a nested loop Readability MaintainabilityThe problem with performance discussions is that they often focus on micro optimization at the expense of readability maintainability And I m a firm believer that maintainability almost always trumps performance I was working for a large health insurance provider in town and I wrote a function that had to do some complex transformations of large data sets When I finished the first pass of the code it worked But it was rather obtuse So before committing the code I refactored it so that during the interim steps I was saving the data set into different temp variables The purpose of this approach was to illustrate to anyone reading the code what had happened to the data at that point In other words I was writing self documenting code By assigning self explanatory names to each of the temp variables I was making it painfully clear to all future coders exactly what was happening after each step When I submitted the pull request the dev manager who BTW was a complete idiot told me to yank out all the temp variables His logic was that those temp variables each represented an unnecessary allocation of memory And you know what He wasn t wrong But his approach was ignorant Because the temp variables were going to make absolutely no discernible difference to the user but they were going to make future maintenance on that code sooooo much easier You may have already guessed that I didn t stick around that gig for too long If your micro optimization actually makes the code more difficult for other coders to understand it s almost always a poor choice What To Do I can confidently tell you that performance is something that you should be thinking about Almost constantly Even on frontend apps But you also need to be realistic about the fact that your code is almost always running in an environment where there are tons of unused resources You should also remember that the most efficient algorithm isn t always the best algorithm especially if it looks like gobbledygook to all future coders Thinking about code performance is a valuable exercise One that any serious programmer should probably have almost always in the back of their mind It s incredibly healthy to continually challenge yourself and others about the relative performance of code In doing so you can vastly improve your own skills But performance alone should never be the end all be all of your work And this is especially true if you re a frontend developer	2022-02-27 18:31:29
海外TECH	Engadget	Watch Huawei's MWC 2022 keynote in under 10 minutes	https://www.engadget.com/huawei-mwc-2022-supercut-183530500.html?src=rss	Watch Huawei x s MWC keynote in under minutesWith everything that s going on in the world right now you may have glossed over the fact there s a big tech conference underway in Spain After the pandemic sidelined Mobile World Congress in and pushed it to June in the trade show returned to its usual timeslot as one of the first major tech events of the year Huawei was one of the first manufacturers to present at the conference announcing the MatePad Paper and a refresh of its MateBook X Pro ultraportable laptop If you missed the keynote fret not we ve condensed the company s entire presentation into a video you can watch in under minutes Catch up on all of the news from MWC right here	2022-02-27 18:35:30
ニュース	BBC News - Home	Chelsea trustees have not agreed to run club after Roman Abramovich move	https://www.bbc.co.uk/sport/football/60549390?at_medium=RSS&at_campaign=KARANGA	sport	2022-02-27 18:06:04
ニュース	BBC News - Home	How badly will Russia be hit by new sanctions?	https://www.bbc.co.uk/news/business-60543995?at_medium=RSS&at_campaign=KARANGA	ukraine	2022-02-27 18:22:36
ビジネス	ダイヤモンド・オンライン - 新着記事	おばちゃん社長の工場が 倒産寸前から蘇った理由、 「安全」にこだわると儲かった!? - なぜ、おばちゃん社長は「絶対安全」で利益爆発の儲かる工場にできたのか？	https://diamond.jp/articles/-/296809	安全第一	2022-02-28 03:50:00
ビジネス	ダイヤモンド・オンライン - 新着記事	ウクライナ問題、国際サッカーと露「20年来友好」に影 - WSJ PickUp	https://diamond.jp/articles/-/297395	wsjpickup	2022-02-28 03:45:00
ビジネス	ダイヤモンド・オンライン - 新着記事	幻のキノコで現実のマーケットをつくり出せ！ - Virtical Analysis	https://diamond.jp/articles/-/297387	幻のキノコで現実のマーケットをつくり出せVirticalAnalysis「幻のキノコ」とされるハナビラタケの生産体制作りに成功した大井川電機製作所だったが、販路開拓の戦略はほぼ全くの白紙だった第回。	2022-02-28 03:42:00
ビジネス	ダイヤモンド・オンライン - 新着記事	ひろゆきが呆れる「民族や家柄を自慢げに話す人」の残念な特徴 - 1％の努力	https://diamond.jp/articles/-/296993	youtube	2022-02-28 03:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	景気は一時的に持ち直すも雇用に改善は見られず、労働時間増と生産性上昇が背景 - 数字は語る	https://diamond.jp/articles/-/296473	労働時間	2022-02-28 03:35:00
ビジネス	ダイヤモンド・オンライン - 新着記事	日本生命が営業職員制度改革へ始動、清水博社長に聞く新制度「ニッセイまごころマイスター認定制度」の中身 - ダイヤモンド保険ラボ	https://diamond.jp/articles/-/297398	日本生命	2022-02-28 03:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	プーチン氏最大の賭け、ロシア復活に執念 - WSJ PickUp	https://diamond.jp/articles/-/297396	wsjpickup	2022-02-28 03:25:00
ビジネス	ダイヤモンド・オンライン - 新着記事	グーグルのモバイル広告技術、サイト運営者に敬遠の動き - WSJ PickUp	https://diamond.jp/articles/-/297397	wsjpickup	2022-02-28 03:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「もうすぐ上昇しそうな株」を発見するシンプルなコツ - 株トレ	https://diamond.jp/articles/-/292032	運用	2022-02-28 03:15:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「勉強しなくちゃいけないこと」が多すぎるとき、やるべき習慣 - 起業家の思考法	https://diamond.jp/articles/-/297274	問題解決	2022-02-28 03:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【精神科医が教える】 恋愛で失敗しないたった1つのポイント - 精神科医Tomyが教える 心の荷物の手放し方	https://diamond.jp/articles/-/297059	voicy	2022-02-28 03:05:00