投稿時間:2021-12-08 16:43:03 RSSフィード2021-12-08 16:00 分まとめ(61件)

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TECH	Engadget Japanese	Kindle 50％ポイント還元セール。「ベルセルク」「3月のライオン」「先輩がうざい後輩の話」など人気作品も多数！	https://japanese.engadget.com/kindle-point-back-sale-065547393.html	amazon	2021-12-08 06:55:47
TECH	Engadget Japanese	ローソン、Apple Pay決済で＋16%還元　2月28日まで実施中	https://japanese.engadget.com/ponta-065039017.html	applepay	2021-12-08 06:50:39
TECH	Engadget Japanese	12/8 23:59まで：サムソナイトのビジネスバッグやリュック、スーツケースがタイムセール中！	https://japanese.engadget.com/sale-samsonite-bags-063514276.html	amazon	2021-12-08 06:35:14
TECH	Engadget Japanese	Twitter、センシティブな画像や動画に警告を付加できる機能をテスト中	https://japanese.engadget.com/twitter-sensitive-media-warning-062015315.html	twitter	2021-12-08 06:20:15
ROBOT	ロボスタ	AWS「ローカル5G」提供サービスに参入　「re:Invent」基調講演で「デジタルツインやコネクテッドカー自動運転」支援も発表	https://robotstart.info/2021/12/08/reinvent-keynote.html	reinvent	2021-12-08 06:22:32
ROBOT	ロボスタ	AIとの会話で誤認識エピソードを募集した「第2回大ごにんしき大賞」結果発表　大賞「Hey,Siri 暇なんだけどどうしたらいい？」AIの回答は	https://robotstart.info/2021/12/08/goninshiki-2nd.html	heysiri	2021-12-08 06:05:22
ROBOT	ロボスタ	HICityの自動運転バスがついに公道へ！「NAVYA ARMA」がHICityと羽田空港間の公道走行　一般の利用者が乗車可能	https://robotstart.info/2021/12/08/hicity-navya-arma-public-road.html	hanedainnovationcity	2021-12-08 06:03:25
IT	ITmedia 総合記事一覧	[ITmedia PC USER] 障がいのある人もより快適なPCライフを――日本マイクロソフトがSurface用「アダプティブキット」を12月14日発売　税込み1870円	https://www.itmedia.co.jp/pcuser/articles/2112/08/news119.html	itmediapcuser	2021-12-08 15:55:00
IT	ITmedia 総合記事一覧	[ITmedia PC USER] 慶洋エンジニアリング、VAパネルを採用した湾曲34型ウルトラワイドゲーミング液晶	https://www.itmedia.co.jp/pcuser/articles/2112/08/news116.html	itmediapcuser	2021-12-08 15:39:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 営業SaaS「Magic Moment Playbook」、コミュニケーションを自動化する「Playbook シーケンス」をリリース	https://www.itmedia.co.jp/business/articles/2112/08/news115.html	ITmediaビジネスオンライン営業SaaS「MagicMomentPlaybook」、コミュニケーションを自動化する「Playbookシーケンス」をリリース営業支援サービスを提供するMagicMoment東京都港区は月日、LTV経営を支援する営業SaaS「MagicMomentPlaybook」において、商談や顧客の状況に応じてコミュニケーションを自動化する新機能「Playbookシーケンス」をリリースしたと発表した。	2021-12-08 15:37:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] Sansan、メール署名を自動取り込み　新機能「スマート署名取り込み」	https://www.itmedia.co.jp/business/articles/2112/08/news114.html	itmedia	2021-12-08 15:34:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 中小企業の79％は「冬のボーナスを支給」、前年と比較してどう？	https://www.itmedia.co.jp/business/articles/2112/08/news117.html	itmedia	2021-12-08 15:32:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] サンマルクカフェ、関東初のテークアウト専門店　近隣店舗で製造し「できたて」を維持	https://www.itmedia.co.jp/business/articles/2112/08/news090.html	itmedia	2021-12-08 15:25:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 居酒屋で苦戦するワタミが「寿司」に初参入　逆転の一手となるか？	https://www.itmedia.co.jp/business/articles/2112/08/news113.html	itmedia	2021-12-08 15:13:00
TECH	Techable（テッカブル）	梅田の空にラピュタが！ スマホ片手に楽しめるARコンテンツに注目	https://techable.jp/archives/168338	osakaume	2021-12-08 06:00:22
python	Pythonタグが付けられた新着投稿 - Qiita	サイコロを振る	https://qiita.com/nmmg0031785/items/3288116aa095959da93f	必要なライブラリのインポートimportnumpyasnpimportmatplotlibpyplotaspltサイコロを振るサイコロをN回振って、出目のヒストグラムを作成する。	2021-12-08 15:27:06
python	Pythonタグが付けられた新着投稿 - Qiita	スマートなPythonistaになりましょう。	https://qiita.com/tasuren/items/2999f5c662c846260b36	これもまた以下のようにラップすることでできます。	2021-12-08 15:13:30
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	小数の範囲内での乱数生成方法	https://teratail.com/questions/372852?rss=all	xxxxxxxxxxxxxxxxxxxxxxxxx	2021-12-08 15:59:19
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Visual Studio 2022からプログラムの起動ができない	https://teratail.com/questions/372851?rss=all	VisualStudioからプログラムの起動ができない先程、MicrosoftnbspVisualnbspStudionbspから、MicrosoftnbspVisualnbspStudionbspに変えたのですが、デバッグとデバッグなしで開始がプロジェクトには、プロファイルを実行する方法がわかりませんとエラーメッセージが出て、できません。	2021-12-08 15:58:10
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	textareaに入力されたものをデータベースに登録する	https://teratail.com/questions/372850?rss=all	textareaに入力されたものをデータベースに登録する前提・実現したいことテキストエリアに入力された内容をデータベースに登録するシステムを作ろうとしたところ以下のようなエラーが出てしまいました。	2021-12-08 15:41:04
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ギズモによる可視化について	https://teratail.com/questions/372849?rss=all	しかし、ゲームを開始したら下の画像のように緑の線は消えてしまします。	2021-12-08 15:36:43
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	点群データの欠損部分を埋める方法　Python	https://teratail.com/questions/372848?rss=all		2021-12-08 15:35:14
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Laravel Authインポート時のエラー	https://teratail.com/questions/372847?rss=all	LaravelAuthインポート時のエラーLaravelでtodoリストの作成をしています。	2021-12-08 15:35:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Pythonで画像の明暗を判断したいです。	https://teratail.com/questions/372846?rss=all	Pythonで画像の明暗を判断したいです。	2021-12-08 15:30:25
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	複数機能での移動の実装	https://teratail.com/questions/372845?rss=all	複数機能での移動の実装前提・実現したいこと素朴な疑問なのですが、unityでUI入力による移動とその他、別のコントローラでの移動を同じオブジェクトに入れることは可能なんでしょうか発生している問題・エラーメッセージ問題的にはコントローラでの移動が優先されて、UIでの移動はできないエラーは出ないという感じです。	2021-12-08 15:27:59
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	python　要素を特定し、その要素より下の部分からスクレイピング	https://teratail.com/questions/372844?rss=all		2021-12-08 15:14:52
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	関数を引数に入れた場合	https://teratail.com/questions/372843?rss=all	ndtypesforfunctionandint	2021-12-08 15:14:19
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ファイルやディレクトリが見つからないとかで、Nginxが再起動できない。	https://teratail.com/questions/372842?rss=all	ファイルやディレクトリが見つからないとかで、Nginxが再起動できない。	2021-12-08 15:00:35
Linux	Ubuntuタグが付けられた新着投稿 - Qiita	Ubuntu DesktopでSELinuxを使う	https://qiita.com/cl0wn/items/ffd1920be4752eeffb86	上の例だと、systemdjournalというコマンドを実行している最中に、systemusystemrsyslogdtsというコンテキストのプロセスが、systemuobjectruserruntimeroottsというラベルがついているディレクトリにアクセスしようとしてポリシー違反として拒否されますただし、Permissiveモードで動作しているので動作の拒否は実際にはされませんでしたという読み方をします。	2021-12-08 15:52:24
Docker	dockerタグが付けられた新着投稿 - Qiita	TypeScriptを使った、Next.js + ExpressカスタムサーバーでSocket.ioのチャットアプリをDockerで実装	https://qiita.com/tronicboy/items/7969a77817d8f2706b52	ここには全てのCustomServerロジックを入れると、スッキリしていいと思います今回はindextsのみですが基本的なコードはNextのドキュメントを参考にしましょうしかし、Typeも入れんといけんので、こんな感じでいいです。	2021-12-08 15:02:52
技術ブログ	Developers.IO	Amazon Linux2 から pg_dump で RDS for PostgreSQL のダンプ作成時にハマったので調べてみた	https://dev.classmethod.jp/articles/amazon-linux2-pg_dump-rds-for-postgresql/	amazon	2021-12-08 06:20:15
技術ブログ	Developers.IO	Coc.nvimを触ってみようアドベントカレンダー 8日目 – coc-dot-complete	https://dev.classmethod.jp/articles/cocnvim-adventcalendar-day08/	adventcalendar	2021-12-08 06:00:53
海外TECH	DEV Community	Making digital currency; How to create a new cryptocurrency	https://dev.to/miachao7/making-digital-currency-how-to-create-a-new-cryptocurrency-15cg	Making digital currency How to create a new cryptocurrencyIn recent years many startups have made a lot of money by creating a digital currency and selling tokens in the initial public offering Creating a new digital currency may seem like an impossible process to most people While making digital currency is possible if you have enough knowledge in this field In this article we will introduce you to the methods of making a digital currency and at the end we will answer some common questions in this regard Why are new digital currencies being created Even if virtual money has been available to the public for a long time Bitcoin is the first known and most successful cryptocurrency in the cryptocurrency market Many cryptocurrencies have been created today the most popular of which are Bitcoin Ripple and Ethereum Some unique features make companies and individuals think about creating cryptocurrencies The most important features of digital currency are cryptography security and confidentiality no need to monitor a central institution transparency of transactions fast transactions and ease of transfer The difference between coins and digital currency tokensSome people mistakenly use tokens and quins as synonyms While Token and Quinn are different The most important thing that distinguishes a token from a quin is the lack of an independent blockchain Tokens are created on the platform of other blockchains But Quinn has an independent blockchain Another important difference between coins and tokens is that coins are used to buy and sell and are considered a method of payment While most tokens can be used for use in an application or as an asset Bitcoin Ethereum Ripple and LiteCoin are the most popular coins in the digital currency market Tetra Chainlink Dai and Avi are also in the category of tokens Digital currency making training Introducing methods Method one Create a new digital currency by creating tokensOne way to make digital currency is to create tokens As we have said a token is a digital currency that does not have its independent blockchain and has been created and launched in the context of another blockchain For this reason when a token is generated there is no need to work on the rules of consensus Making tokens is cost effective for blockchain developers because they do not need the astronomical cost of designing a blockchain to achieve their goals Of course it is also important to note that many digital currencies when in their infancy are implemented on another blockchain platform to save costs but once they have been sufficiently developed a dedicated blockchain for They are used to launch The token can be created on all blockchain platforms that use smart contracts Ethereum is one of the most popular token building platforms At the time of writing Ethereum has hosted more than of the tokens on the market Bainenschin Ias Kazmas Thezos and Theron are other common platforms for making tokens Ethereum s programming language is solidity Solidarity uses concepts that exist in other programming languages ​​such as PHP It is a high level programming language that has all the capabilities and capabilities needed for blockchain software Method Create digital currency by copying and modifying current blockchainsAnother way to build digital currency is to use open source blockchains Open source blocks are made available to the public with programming code after they are created Ethereum and Bitcoin programming codes are also open source and can be accessed by anyone on GitHub Many blockchains have been launched following the example of these two digital currencies For example by making a few changes to the Bitcoin blockchain the LiteCoin network is created Method Create a digital currency by creating a new blockchainBuild digital currency through the new blockchainBuilding and designing a blockchain network is another way to create a new digital currency In a blockchain data is stored in blocks and forms an interconnected chain This structure creates an immutable storage system The blocks are connected using hashes Creating a new blockchain requires deep programming knowledge and a lot of time In the following the steps of creating a new digital currency through making blockchain are outlined in general Select the consensus mechanismConsensus mechanisms are protocols for verifying transactions performed in blockchain without the need for a third party intermediary Proof of work and the stock proof is currently the most well known and basic blockchain consensus mechanisms Select the blockchain platformThe correct choice of blockchain platform depends on the consensus mechanism you have chosen The best blockchain operating systems are EthereumWaves WAVES Hyperledger FabricNEMIBM blockchainNxt NXT HydraChainBlockStarterBigChainDBEOSQuorumIOTACoinListMultiChainOpen chainChain CoreDesign the nodesYou need to decide how the blockchain works and design the nodes accordingly For example will the licenses be private or public Will the hosting be on premises web systems or cloud systems Specify the blockchain architectureBefore launching a digital currency you need to be sure of all aspects Because you can not change multiple blockchain parameters after startup For example you need to specify what address blockchain will follow to track exchanges of different cryptocurrencies Design the user interfaceIf your user interface is not good the cipher project will fail You need to make sure you are using the latest version of FTP servers databases etc Frequently Asked Questions about Making New Digital CurrenciesDoes making a digital currency always lead to profitability No More than a few hundred thousand digital currencies have been launched on various platforms many of which have failed For this reason all aspects of work must be well weighed before creating a digital currency What is the reason for the failure of some new digital currencies Unfortunately this perspective often causes us to become overwhelmed when it s time to start a new digital currency That s why we see so many teams being forgotten after spending so much money and energy to create a new digital currency without gaining popularity One of the main reasons for their failure is that they failed to do good marketing Therefore before any action the marketing system must be well defined What is the first step in building a new digital currency The first step in creating a new digital currency is to have a well defined digital currency white paper White paper in the world of digital currencies means a comprehensive and complete report of the problem that the introduced project seeks to solve Project objectives should be clearly defined within the white paper A standard and complete white paper include an abstract introduction problem definition product description technical details descriptions of the new digital currency details of the public offering and introduction of the development team How much does it cost to create a new digital currency Creating new passwords is not an easy task and will probably require some financial resources Unless you can handle things like development documentation and marketing The cost of building an encrypted currency depends on several factors and no specific number can be specified Concluding remarksCreating a new dedicated currency may seem like an attractive and profitable offer at first but we must not forget that there are many challenges in this direction For this reason sufficient market research must be done before any action is taken On the other hand the necessary capital must be provided for manufacturing and marketing Otherwise the digital currency project is likely to fail in its infancy	2021-12-08 06:20:35
海外TECH	DEV Community	10 Tools Python Programmers Can Learn in 2022	https://dev.to/javinpaul/10-tools-python-programmers-can-learn-in-2022-49ll	Tools Python Programmers Can Learn in Disclosure This post includes affiliate links I may receive compensation if you purchase products or services from the different links provided in this article Hello Devs If you want to become a better Python developer in and looking for the best Python tools libraries and best IDEs for Python development then you have come to the right place Earlier I have shared the best Python courses best Python books free python courses and Python frameworks and today I am going to share the best tools Python programmers can learn in Python is considered one of the most popular and powerful programming languages and its popularity and demand is growing every passing days I must say that Python is currently fueling a revolution to bringing more people into coding and programming It becomes much popular these couple last of years because of its simplicity and a hundred of thousands of what s known as libraries that make it multi purpose programming languages like creating data visualization GUI application web application artificial intelligence deep learning and much more Many reasons made python so popular such as its simplicity in creating complex codes with few lines of code another thing made Python so popular it is a high level programming language so you need to worry about memory management like C C do as well the huge community that support python so if you get stuck with something you will find someone can help you Because of its simplicity many developers have changed their careers to be python developers and since it s an open source programming language many programmers have created tools that facilitate the use of this language In this article I have shared may useful python tools libraries and IDEs that Python developers should know and use in their daily life while using this wonderful language This is a small introduction about Python and its capabilities and now you will see some of the development tools to help you create more efficient code and facilitate the process of programming as well as help you find your errors in the syntax Best Python Development Tools and Libraries to learn in There is no doubt that python nowadays is the most growing programming language among not only software engineers but as well the data scientist web developers just to name a few because it is the most beginner friendly programming language compared to other ones such as C or JavaScript but to become a Python master you not only need to master Python programming language but also tools and library which is essential for Python developers There is a common saying that a craftsman is as good as their tools and Python developers are no exception Knowing these tools will make you more productive in your coding life and help you in becoming a better Python developer in Without wasting any more of your time here is the list of tools Python developers should learn in PyCharm IDEThis integrated development environment IDE is probably the best one ever available online for a python developer created by JetBrains which is one of the best known company for creating developer tools and IDEs for many programming languages not just python This IDE lets you create your code efficiently and save you time by a feature called autocomplete which essentially suggests available keywords in python while you writing your code and it knows everything about your code link the intending when you write some keywords like the if statement and highlighting your code syntax and much more that you can explore Also it tells you where the error is when you make a typo or forget something inside your program and as well as the installation of the packages made easy when you consider using PyCharm as your default IDE If you want to learn Python development using PyCharm then I highly recommend you to join Complete Python Developer in Zero to Mastery course by Andrei Negaoie which will teach you how to set up your professional workspace with Jupyter Notebooks PyCharm VS Code the best IDEs and Editors for Python developers In short PyCharm from JetBrains is the most used and favorite integrated development environment IDE for python developers since it has many tools to help you make clean code and the autocomplete feature that makes it the best choice among the developers Jupyter notebookJupyter notebook is an IDE that is famous among data scientist and machine learning engineer since it facilitates the creation and execution of your code and you only have to execute one cell to test the code instead of running the whole program like the other IDEs The IDE works on the browser and you can add notes to your code and titles and export them as pdf or ipynp files as well it is a good option if you are going to make D visualization In short one of the best Python tools for code collaboration If you want to learn Python coding with Jupytor notebook Andrei Negaoi s Complete Python Developer in Zero to Mastery course on Udemy is a great resource KerasKeras is an artificial intelligence tool or an API built in top of TensorFlow and many other libraries such as Theano and CNTK to create a deep neural network and mimic the human brain in some way and simplify the creation of these deep neural networks Since Keras is open source it attracts the contributors to develop it more and making the creation of neural networks as easy as typing some commands and stacking layers If you want to learn more about Keras and other deep learning concepts I highly recommend you to check out Deep Learning with Python and Keras course by Jose Portilla on Udemy Pip PackageLet s say that you have learned the Python programming language and you want to be a specialist in one of the fields like data science artificial intelligence or data analysis At that time you have to install some packages to do that and here comes a smart tool called Pip Pip is one of the most useful python tools and every developer should have since it used to install any python package that you want to use in your python program All you have to do is type pip and then the name of that package and this smart tool will download it and install it for you so it needs an internet connection in order to do that also you have to keep it updated always to make sure it works in a more efficient way If you want to learn more about the Pip package and how to use Pip to install and uninstall python modules and packages then you can also check the Learn to Code with Python course on Udemy which has a couple of lectures on Pip pancakes Python AnywhereLet s say that you have read an article about python and you want to give it a try but also you don t want to download python and trying different ideas to see which one is the best Instead you can host and run your code on an online service called python anywhere So if you are new and you didn t decide yet whether python is right for you or not you can create a code by this service right away from your browser It give you free access to their platform but if you need more power you have to upgrade your plan which will code you each month Alternatively you can also join an interactive course like Learn Python from CodeCademy which allows you to practice Python from the browser itself Btw you would need a CodeCademy membership to access this course which costs around per month on the annual plan Scikit LearnScikit Learn is an open source machine learning library built on top of many other libraries such as matplotlib for data visualization NumPy for mathematic calculation and scipy for scientific computing and many more libraries to make Scikit Learn much powerful Let s assume that you have some knowledge of python and you want to be a specialist in data science or machine learning you can use a simple and efficient tool called Scikit learn This tool has some built is packages for performing machine learning algorithms on your data such as classification and linear regression and much more You can also use their built in data to perform your data science or analysis libraries on them without searching the web and downloading these data If you want to learn more about Scikit Learn and other Python Data Science libraries like NumPy Pandas Seaborn Matplotlib Plotly Tensorflow and more then I recommend you to join Python for Data Science and Machine Learning Bootcamp course by Jose Portilla on Udemy In short a fabulous tool for data scientists and machine learning engineers to perform many tasks related to data analysis and machine learning such as classification regression clustering and more This is a Python library that should be in the Python developers toolset SphinxOne such thing that makes Python so successful is the variety of codes that you can find online let s say in GitHub or the other hosting code websites Many developers build their own open source programs and let others use them and in order to do that you have to generate documentation for your code and here come the benefits of Sphinx Sphinx is the most useful tool when it comes to generating documentation for your programs it works on the terminal or cmd for windows and it begins asking you a bunch of questions about your name what your code does code name release date and much more question After that it will generate many different files like an HTML file that you can publish as a web page on your website or a pdf file that you can include alongside your open source code and many formats that are useful in such cases SeleniumSelenium is a tool or framework to experiment with a web application such as WordPress across various and multiple browsers Python also can be utilized to design a simple script or automation testing as well as many other languages such as java for instance Many reasons made this tool popular such as can be used with many programming languages like C Java Ruby and more as well it supports multiple platforms like Linux Mac Windows and many browsers such as chrome and Firefox and safari If you want to learn Python Automation from basic to advance with live projects then I highly recommend you to check out Selenium Webdriver with PYTHON from Scratch Frameworks course on Udemy This hour long course is perfect to learn Automation with Python and Selenium in Sublime TextThe last developer tool in this article is a lite text editor called sublime that can be used to create cleaning and nice python code just like the previous ones PyCharm and Jupyter notebook but very fast and supporting many languages not only python This code editor has something called plugins which is a small software that can be added to your editor and add some functionalities such as the autocomplete feature and much more BeautifulSoupBeautiful soup is a tool or python module for parsing HTML documents from websites as well as XML and it can be used also to extract data from HTML files so you can create a python script to do this job easily This tool is widely used among data scientists to create s simple script that can extract large data from websites than apply visualization or pass that data to machine learning programs for AI research If you want to learn more about BeautfiulSoup and web scrapping using python then Web Scraping with Python BeautifulSoup Requests amp Selenium course eon Udemy is a good course to start with That s all about the best tools IDEs and Libraeies for Python developers to learn in If you are learning Python or already know Python then learning these tools can improve your skills and productivity and make you a better Python Developer Many Python Programmers and Software Engineers are using these tools and libraries to make their code faster and cleaner than ever before and can make your job easy such as auto completing your code or downloading large data and organizing it for your research or development Other Python Articles and tutorials you may like Best Websites to learn Python for FREE Python vs Java Which is better to start with Reasons to learn Python in Data Science and Machine Learning course in Python Top Course to Learn Python for Beginners Free Python Programming Books for Programmers Free Courses to learn Python in depth Why Python is the best Programming Language for Data Science Top Web Development Frameworks for Python Developers Python vs JavaScript Which is better to start with Free Online courses to learn Python in depth Data Science Courses from Harvard and IBM Top Python libraries for Data Science and Machine Learning Python vs Java Which Programming language Beginners should learn Top Books to learn Python for Data Science in Thanks for reading this article so far If you find these best Python tools IDES and libraries useful then please share them with your friends and colleagues If you have any questions or feedback then please drop a note P S If you are new to Python and looking for a comprehensive course to learn Python in depth then I also recommend you check out The Complete Python Bootcamp course by Jose Portilla on Udemy This course is trusted by more than million python developers and it s one of the best courses to learn Python online	2021-12-08 06:14:13
海外TECH	DEV Community	Fail-Fast Reliable Software Strategy. Debug Failures Effectively	https://dev.to/codenameone/fail-fast-reliable-software-strategy-debug-failures-effectively-3162	Fail Fast Reliable Software Strategy Debug Failures EffectivelyA broken kitchen appliance leads me down the path of intelligent failure downside risk exponential growth and cloud computing I love cooking and use my Thermomix a lot If you hadn t heard about that amazing innovation it s a kitchen robot…Well it s a magical super cooking machine When designing the Thermomix its designers took the approach of fail safe instead of fail fast This is a smart choice in this case but it has its drawbacks E g my machine tried to recover from a failure which sent it into an infinite recovery loop I literally couldn t pull out the food from the lid that was sealed shut But normally it s one of the most reliable devices I own Which approach should we take and how does that impact our long term reliability Fail Fast vs Fail Safe ApproachIn case you aren t familiar with the terms fail fast means a system that would quickly fail in an unexpected condition A fail safe system will try to recover and proceed even with bad input Java tries to take the fail fast approach whereas JavaScript leans a bit more towards the fail safe approach A good example of fail fast behavior would be their respective approaches to null In Java a null produces a NullPointerException which fails the code instantly and clearly JavaScript uses “undefined which can propagate through the system Which one Should we Pick This is hard to tell There s very little research and I can t think of a way to apply the scientific method objectively to measure this sort of methodology It has both technical aspects and core business aspects It s pretty hard to determine something conclusively What I can say for sure is that this shouldn t be a senior executive decision alone This is a sort of policy that management should integrate with engineering to mitigate the downside risk This applies to you whether you re an engineer or a business leader Whether you re a Silicon Valley startup Amazon or a bank These principles are universal Companies using Microservices are probably more committed to some form of fail safe Resiliency is a common trait of Microservices that s in the fail safe camp Modern approaches to fail safe try to avoid some pitfalls of the approach by using thresholds to limit failure A good example of this is a circuit breaker both the physical one and software based A circuit breaker disconnects functionality that fails so it doesn t produce a cascading failure Companies who pick the fail fast approach take some risks but reap some big rewards When you pick that approach the failure can be painful if a bug reaches production but there are two significant advantages It s easier to catch bugs in fail fast systems during the development debugging cycleThese bugs are usually easier to fixThe fail fast approach handles such bugs better since there s a lower risk of cascading effect A fail safe environment can try to recover from an error and postpone it As a result the developer will see an error at a much later stage and might miss the root cause of the error Historically I prefer fail fast I believe it makes systems more stable when we reach production But this is anecdotal and very hard to prove empirically I think a fail fast system requires some appetite for risk both from engineering and from the executives Maybe even more so from the executives Notice that despite that opinion I said that the Thermomix was smart to pick fail safe Thermomix is hardware running in an unknown and volatile environment This means a fix in production would be nearly impossible and very expensive to deploy Systems like that must survive the worst scenarios We need to learn from previous failure Successful companies use both approaches so it s very hard to pick the best approach Hybrid Environment in the CloudA more common strategy for handling failure is to combine the best aspects of both worlds Fail fast when invoking local code or services e g DBFail safe when depending on remote resource e g remote web serviceThe core assumptions behind this direction is that we can control our local environment and test it well Businesses can t rely on a random service in the cloud They can build fault tolerant systems by avoiding external risks but taking the calculated risks of a fail fast system Defining FailureWhen discussing failure the assumptions we make focus around a error page crash etc Those are serious P failures But by no means are they the only type of failures or even the worst types of failure A crash usually marks a problem we can fix and even workaround by spinning up a new server instance automatically This is actually a failure we can handle relatively elegantly A far more sinister failure is data corruption A bug can cause bad data making its way into the database and potentially causing long term problems Even security risks and crashes can result from corrupted data and those will be much harder to fix A fail fast system can sometimes nip such issues in the bud With cloud computing we re seeing a rise in defensive programming such as circuit breakers retries etc This is unavoidable as the assumptions behind this is that everything in the cloud can fail We need to develop core knowledge on the failures we can expect One approach I found useful is to review logs from long running integration tests nightly tests An important part of a good QA process is long running tests that take hours to run and stress the system When reviewing the logs of these tests we can sometimes notice issues that didn t fail but conflict with our assumptions about the system This can help find the insidious bugs that went through Don t Fix the BugNot right away Well unless it s in production obviously We should understand bugs before we fix them Why didn t the testing process find it Is it a cascading effect or is it missing test coverage How did we miss that When developers resolve a bug they should be able to answer that question on the issue tracker Then comes the hard problem find the root cause of the failure and fix the process so such issues won t happen again This is obviously an extreme approach to take on every bug so we need to apply some discretion when we pick the bugs to focus on But this must always apply to a bug in production We must investigate bugs in production thoroughly since failure in the cloud can be very problematic to the business especially when experiencing exponential growth Debugging FailureNow that we have a general sense of the subject let s get into the more practical aspects of a blog focused on debugging There s no special innovation here Debugging a fail fast system is pretty darn easy But there are some gotchas tips and tricks we can use to promote fail fast There are other strategies we can use to debug a fail safe system Ensuring we Fail FastUse the following strategies Throw exceptions define the contract of every API in the documentation and fail immediately if the API is invoked with out of bounds state values etc Enforce this strategy with unit tests go over every statement made in the documentation for every API Write a test that enforces that behaviorIf you rely on external sources create tests for unavailable situations low performance and sudden unavailabilityDefine low timeouts never retryThe core idea is to fail quickly Say we need to invoke an Amazon web service A networking issue can trigger a failure A fail fast system will expect a failure and present an error to the user Intelligent Failure for Fail SafeThe core idea isn t so much to avoid failure it s unavoidable The core idea is to soften the blow of a failure E g if we take the Amazon web service example from above A fail safe environment could cache responses from Amazon and would try to show an older response The problem here is that users might get out of date information and this might cause a cascading effect It might mean it will take us longer to find the problem and fix it since the system might seem in order The obvious tip here is to log and alert on every failure and mitigation so we can address them But there s another hybrid approach that isn t as common but might be interesting to some Hybrid Fail SafeA hybrid fail safe environment starts as a fail fast environment This is also true for the testing environment and staging The core innovation is wrappers that enclose individual components and provide a failsafe layer This can be very similar to CloudFlare or Amazon cloud front providing a cached version of the website But how can we apply this in the code or the OPS layer When the system is nearing production we need to review the fault points within the system focusing on external dependencies but also on internal components A simplistic example like the Amazon example from above will include a quick failure by default The failsafe wrapper can retry the operation and can implement various policies There s some ready made software tools that let us define failsafe strategy after the fact e g failsafe spring retry and many other such tools Some of these tools are at the SaaS API levels and can mitigate availability networking issues This has the downside of adding a production component that s mostly missing in development and QA But it includes many of the advantages of fail fast and keeps the code relatively clean Additional Best Practices for allHere are some best practices you should keep in mind regardless of the strategy you pick Run the software in the debugger with exception breakpoints turned on Exclude APIs that use exceptions to control flow ugh please fix those APIs from the breakpoint This lets you challenge your assumptions about the reliability of the applicationMake sure the environment is random If you use native code randomize memory locations Always randomize test execution to promote failureProper code review I can t stress this enough I love code reviews I despise nitpicking When I get a response on variable naming code styling etc it pushes my buttons Sometimes comments like that ignore an actual bug People hate code review because of that type of nitpicking Companies should train developers in substantive processes and evaluation TL DRFailure can come in many shapes and forms We should accept that failure happens It happens to Amazon Facebook and Google despite all their efforts to avoid it We need to decide on a strategy Make assumptions and get support from senior management all the way through engineering We need to make choices Do we fail more often and recover quickly Do we fail rarely but take time to recover Software reliability is still a function of QA testing But ultimately failure is inevitable and we need to make strategic choices I believe most startups should focus on fail fast since the growth mindset makes it very hard to keep fail safe strategies functional Since we have QA and testing most of these issues are outliers and they are very hard to optimize for	2021-12-08 06:09:40
医療系	医療介護 CBnews	参考症例に妊婦など「特定の背景を有する患者」も-副作用報告で厚労省医薬安全対策課長が通知	https://www.cbnews.jp/news/entry/20211208153638	厚生労働省	2021-12-08 15:40:00
医療系	医療介護 CBnews	認知症に携わる医療・介護などの多職種連携を強化-神戸市が新西市民病院整備基本構想を公表	https://www.cbnews.jp/news/entry/20211208144820	基本計画	2021-12-08 15:25:00
金融	JPX マーケットニュース	[OSE]TOPIX先物取引に係る中心限月取引の変更	https://www.jpx.co.jp/news/2020/20211208-02.html	限月	2021-12-08 15:20:00
金融	ニッセイ基礎研究所	2021～2023年度経済見通し－21年7-9月期ＧＤＰ2次速報後改定	https://www.nli-research.co.jp/topics_detail1/id=69569?site=nli	年月期の成長率は下方修正されたが、新型コロナウイルスの感染状況が想定よりも落ち着いており、消費が上振れする可能性が高まったことを受け、年月期の成長率見通しを前期比年率から同へ上方修正した。	2021-12-08 15:39:38
金融	ニッセイ基礎研究所	2022年欧州の焦点－メルケル後のドイツ、フランス大統領選、ドラギ効果の持続力	https://www.nli-research.co.jp/topics_detail1/id=69572?site=nli	nbsp目次・年は欧州の政治も変化の年、最大の変化は独メルケル首相の不在・独新政権はデジタル化、脱炭素化加速、債務ブレーキは維持・独新政権を構成する党は親EUの立場も一致、中国にはメルケル政権よりも厳しい立場・上半期にはドイツ、フランス、イタリアで大統領選挙が実施、最大の注目はフランス・仏は年上半期のEU議長国、独新政権とEUの戦略的自立を推進へ・月大統領選では支持率の低空飛行が続く、右派の票が割れればマクロン大統領再選・フランスは大統領選後に国民議会選挙も実施・ドラギ効果の持続力に影響するイタリアの大統領選挙年は米国の中間選挙、中国の共産党大会、日本でも参院選が予定されており、政治が注目を集める年となる。	2021-12-08 15:03:55
ニュース	ジェトロ ビジネスニュース（通商弘報）	2022年から公的な週末を土日に変更、金曜日は半日勤務に	https://www.jetro.go.jp/biznews/2021/12/a22c3c303e085a8b.html	金曜日	2021-12-08 06:15:00
海外ニュース	Japan Times latest articles	Why any war with Taiwan is a huge gamble for China’s Xi	https://www.japantimes.co.jp/news/2021/12/08/asia-pacific/politics-diplomacy-asia-pacific/xi-jinping-taiwan-war/	Why any war with Taiwan is a huge gamble for China s XiFor all the talk of Chinese President Xi Jinping s desire to invade Taiwan one counterpoint is often overlooked The domestic risks involved in starting a	2021-12-08 15:25:51
海外ニュース	Japan Times latest articles	U.S. remembers the day the world changed 80 years ago at Pearl Harbor	https://www.japantimes.co.jp/news/2021/12/08/national/history/pearl-harbor-80-anniversary/	europe	2021-12-08 15:19:19
ニュース	BBC News - Home	Downing Street party: No 10 staff joked about party amid lockdown restrictions	https://www.bbc.co.uk/news/uk-politics-59572149?at_medium=RSS&at_campaign=KARANGA	downing	2021-12-08 06:54:08
ニュース	BBC News - Home	Covid: Vaccines should work against Omicron variant, WHO says	https://www.bbc.co.uk/news/world-59573037?at_medium=RSS&at_campaign=KARANGA	pfizer	2021-12-08 06:45:55
ニュース	BBC News - Home	The Papers: No 10 'party clowns' and 'a sick joke'	https://www.bbc.co.uk/news/blogs-the-papers-59572976?at_medium=RSS&at_campaign=KARANGA	downing	2021-12-08 06:02:04
ニュース	BBC News - Home	Christmas dinner costs rise as inflation bites	https://www.bbc.co.uk/news/business-59562587?at_medium=RSS&at_campaign=KARANGA	research	2021-12-08 06:45:10
ニュース	BBC News - Home	Woeful England blown away on day one of Ashes series	https://www.bbc.co.uk/sport/cricket/59574617?at_medium=RSS&at_campaign=KARANGA	Woeful England blown away on day one of Ashes seriesEngland s Ashes campaign begins in depressingly familiar fashion as the tourists are skittled for just by Australia on the opening day of the series	2021-12-08 06:54:01
ニュース	BBC News - Home	Hamilton v Verstappen - the key moments of a thrilling season	https://www.bbc.co.uk/sport/formula1/59557655?at_medium=RSS&at_campaign=KARANGA	finale	2021-12-08 06:13:01
ニュース	BBC News - Home	Will Musiala justify hype and become Muller's successor at Bayern?	https://www.bbc.co.uk/sport/football/59570050?at_medium=RSS&at_campaign=KARANGA	Will Musiala justify hype and become Muller x s successor at Bayern Jamal Musiala has racked up goals assists and minutes since joining Bayern Munich here s a detailed look at what the teenager offers	2021-12-08 06:34:06
ビジネス	ダイヤモンド・オンライン - 新着記事	脱グローバル化の潮流、インフレに拍車か - WSJ発	https://diamond.jp/articles/-/290077	潮流	2021-12-08 15:03:00
GCP	Google Cloud Platform Japan 公式ブログ	Anthos が新しい API と Azure のサポートによりマルチクラウドをより簡単に	https://cloud.google.com/blog/ja/products/containers-kubernetes/google-cloud-anthos-multicloud-api-and-gke-on-azure-ga/	ConnectGatewayを使用してAWSおよびAzureのAnthosクラスタに接続ConnectGatewayを使用することで、Anthosクラスタと安全にやりとりでき、今回、AWSやAzure上で動作するAnthosクラスタでも機能するようになりました。	2021-12-08 07:00:00
北海道	北海道新聞	＜速報＞道内ガソリン、１円４０銭値下がり　灯油はほぼ横ばい	https://www.hokkaido-np.co.jp/article/620460/	値下がり	2021-12-08 15:11:48
北海道	北海道新聞	車両不具合１１本運休 ＪＲ函館線	https://www.hokkaido-np.co.jp/article/620432/	札幌市北区	2021-12-08 15:14:17
北海道	北海道新聞	ガザ囲む鉄製フェンス強化　イスラエル、対ハマスで	https://www.hokkaido-np.co.jp/article/620459/	鉄製	2021-12-08 15:01:00
北海道	北海道新聞	米与野党、債務上限問題で合意　不履行回避へ前進	https://www.hokkaido-np.co.jp/article/620458/	連邦政府	2021-12-08 15:01:00
IT	週刊アスキー	『リネージュ2M』のダンジョン「激戦の島」「破壊された城砦」にレベル60が実装！	https://weekly.ascii.jp/elem/000/004/077/4077480/	ncsoft	2021-12-08 15:35:00
IT	週刊アスキー	「黒毛和牛ハンバーグドリア」って間違いない！ ビッグボーイで豪華ハンバーグフェア	https://weekly.ascii.jp/elem/000/004/077/4077449/	一部店舗	2021-12-08 15:30:00
IT	週刊アスキー	国産大豆の豆乳ドリンクや豆乳スープを味わおう！ 「SOiSPACE（ソイスペース）みなとみらい」が12月9日にオープン	https://weekly.ascii.jp/elem/000/004/077/4077471/	soispace	2021-12-08 15:30:00
IT	週刊アスキー	『LOST ARK』新クラス「ガンスリンガー」の事前登録キャンペーンが開催！	https://weekly.ascii.jp/elem/000/004/077/4077477/	lostark	2021-12-08 15:10:00
GCP	Cloud Blog JA	Anthos が新しい API と Azure のサポートによりマルチクラウドをより簡単に	https://cloud.google.com/blog/ja/products/containers-kubernetes/google-cloud-anthos-multicloud-api-and-gke-on-azure-ga/	ConnectGatewayを使用してAWSおよびAzureのAnthosクラスタに接続ConnectGatewayを使用することで、Anthosクラスタと安全にやりとりでき、今回、AWSやAzure上で動作するAnthosクラスタでも機能するようになりました。	2021-12-08 07:00:00