投稿時間:2021-12-03 20:45:53 RSSフィード2021-12-03 20:00 分まとめ(49件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
TECH	Engadget Japanese	【折り畳み傘 2.0】ワンプッシュ1秒開閉、リバース構造で濡れないハイテク傘「nurenu」	https://japanese.engadget.com/high-tec-umbrella-nurenu-104036535.html	【折り畳み傘】ワンプッシュ秒開閉、リバース構造で濡れないハイテク傘「nurenu」折り畳み傘の進化系quotnurenuquot片手でワンプッシュ秒開閉リバース構造で超撥水手も濡れずに簡単収納台風級の暴風にも負けない新世代のハイテク折り畳み傘そんな悩みから解放すべく誕生したquotnurenuquotポイント新世代のリバース傘リバース構造のここが凄い濡れた傘布による二次被害を防ぐことができます。	2021-12-03 10:40:36
TECH	Engadget Japanese	Officeのビジュアルアップデートが配信開始　Windowsテーマの自動反映や一部ツールバーを変更	https://japanese.engadget.com/office-visual-update-100015036.html	office	2021-12-03 10:00:15
IT	ITmedia 総合記事一覧	[ITmedia Mobile] ソフトウェア更新に失敗した「Galaxy Z Flip3 5G」が回復するまでのヒストリー	https://www.itmedia.co.jp/mobile/articles/2112/03/news162.html	galaxyzflipg	2021-12-03 19:45:00
IT	ITmedia 総合記事一覧	[ITmedia News] 楽天銀行、アプリ決済でエラー表示も引き落とす不具合　楽天ペイ以外にも一部影響（復旧済み）	https://www.itmedia.co.jp/news/articles/2112/03/news161.html	itmedia	2021-12-03 19:44:00
IT	ITmedia 総合記事一覧	[ITmedia News] 「d払い」で障害、通知の誤配信でアクセス集中　復旧は未定	https://www.itmedia.co.jp/news/articles/2112/03/news160.html	itmedia	2021-12-03 19:15:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 「アニメイト池袋本店」がリニューアル　世界有数のアニメショップ誕生へ	https://www.itmedia.co.jp/business/articles/2112/03/news158.html	itmedia	2021-12-03 19:08:00
python	Pythonタグが付けられた新着投稿 - Qiita	Tkinterだってアンチエイリアスしたい。	https://qiita.com/sugarflower/items/3dc3efee6c4a62711d61	試しに一度Canvasに仕込んでみたのですが普通にラインを描くだけなら良いのですけれどもその他諸々をしようとすると何かと不便があったのでここでは別の方法を使います。	2021-12-03 19:23:53
python	Pythonタグが付けられた新着投稿 - Qiita	【Python】Tポイントカンタンくじを自動で引く＋１円寄付するスクリプト【Selenium】	https://qiita.com/ampm/items/33231b096fc71bd90792	【Python】Tポイントカンタンくじを自動で引く円寄付するスクリプト【Selenium】やりたいこと↑のくじを毎日引いて、翌日にどこかでTポイントを使いましょうこの記事では円寄付してます動作環境OSWindowsGoogleChromeバージョンOfficialBuildビットPythonSeleniumWebdriverchromedriverexe※スクリプトと同じフォルダにchromedriverexeを置いてください。	2021-12-03 19:08:03
js	JavaScriptタグが付けられた新着投稿 - Qiita	【p5.js】p5.Geometryであのドーナツをつくる	https://qiita.com/_sayo_y/items/78b7f4dbae267d562e4b	頂点番号x座標y座標z座標pGeometryはpjsライブラリで定義されているクラスであり、この頂点バッファとインデックスバッファのもととなる頂点データやインデックス配列をクラス変数としてまとめて定義することができます。	2021-12-03 19:52:39
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	確率勾配降下法について	https://teratail.com/questions/372143?rss=all	降下	2021-12-03 19:55:02
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	(mac)ターミナル variable inspectorインストールできない	https://teratail.com/questions/372142?rss=all	macターミナルvariableinspectorインストールできないjupyterlabでvariablenbspinspectorを使用したくてインストールするコマンドを実行したのですがエラーが起きてしましました。	2021-12-03 19:53:46
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ハンバーガーメニューが非表示にならない。	https://teratail.com/questions/372141?rss=all	ハンバーガーメニューを見様見真似で作ったのですが、思う挙動になりません。	2021-12-03 19:52:51
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	画像の表示方法について・フェードイン	https://teratail.com/questions/372140?rss=all	画像の表示方法について・フェードイン理想は、なのですが、自身のコードでは、このような表示になります。	2021-12-03 19:33:28
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	モデルの読み込みがうまくいきません	https://teratail.com/questions/372139?rss=all		2021-12-03 19:31:21
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	半分全列挙による処理の高速化	https://teratail.com/questions/372138?rss=all	半分全列挙による処理の高速化半分全列挙についてABCDから数を一つずつ選ぶとき、ABCDnbspgtnbspABCDkを満たす組み合わせの個数を数える問題を実装しましたが、nが大きくなるとタイムエラーが起きてしまします。	2021-12-03 19:26:52
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	renderしたはずのページが表示されない	https://teratail.com/questions/372137?rss=all	renderしたはずのページが表示されない環境RubynbsponnbspRailsnbspAmazonnbspLinuxAmazonnbspEC問題が起こった経緯動画サイトでの検索→検索結果画面表示の途中で問題が起きました。	2021-12-03 19:24:18
Ruby	Rubyタグが付けられた新着投稿 - Qiita	マンダラートを作りたい #1	https://qiita.com/divclass123/items/9224d6c3ad3648708bca	ltftextareatextvaluemandalarttextgtとすることで、すでにあるオブジェクトのテキストが、フォームの中にある状態にはなったが、submitを押すと、また新しいオブジェクトが生成されて、フォームの中にあるテキストは、変わっていない。	2021-12-03 20:00:00
Ruby	Railsタグが付けられた新着投稿 - Qiita	マンダラートを作りたい #1	https://qiita.com/divclass123/items/9224d6c3ad3648708bca	ltftextareatextvaluemandalarttextgtとすることで、すでにあるオブジェクトのテキストが、フォームの中にある状態にはなったが、submitを押すと、また新しいオブジェクトが生成されて、フォームの中にあるテキストは、変わっていない。	2021-12-03 20:00:00
Ruby	Railsタグが付けられた新着投稿 - Qiita	【Rails】gmailを使ってメールを送信しようとすると、Net::SMTPAuthenticationError (535-5.7.8 Username and Password not accepted.とかいう地獄の対処法【Mailer】	https://qiita.com/GalaxyNeko/items/06b6035c655da0079114	ENVEMAILADDRESSexamplegmailcomEMAILPASSWORDアプリパスワードすべてのメールでPOPを有効にする以下のサイトを参考にして、POP設定を有効にしたものの変化なし。	2021-12-03 19:25:08
Ruby	Railsタグが付けられた新着投稿 - Qiita	【Rails】redirect_toとrenderの処理の違いについて【初学者の疑問点を簡潔に解説】	https://qiita.com/P-man_Brown/items/1ace8e7be305c92a2fd3	先ほども申し上げた通り、render処理の際にはindexアクションは実行されないので、上記の記述のまま、処理をしてもcreateアクション内ではbooksBookallが定義されていないため、Viewがデータを取得できずにエラーとなります。	2021-12-03 19:22:10
技術ブログ	Developers.IO	[レポート]トランスフォーメーションを加速させるトレーニング #reinvent #TNC201-L-AM	https://dev.classmethod.jp/articles/reinvent-2021-report-tnc201-l-am/	reinvent	2021-12-03 10:49:57
技術ブログ	Developers.IO	[アップデート] AWS Compute OptimizerでEC2とAutoScalingのメトリクス分析のルックバック期間を最大3ヶ月まで延長可能になりました	https://dev.classmethod.jp/articles/compute-optimizer-update-ec2-enhanced-infrastructure-metrics/	autoscaling	2021-12-03 10:45:20
海外TECH	MakeUseOf	Why You'll Soon See More Crypto Ads on Facebook and Instagram	https://www.makeuseof.com/crypto-ads-on-facebook-instagram/	Why You x ll Soon See More Crypto Ads on Facebook and InstagramThey ve been banned for a long time but Meta is bringing crypto ads back to Facebook and Instagram But why the sudden change of heart	2021-12-03 10:35:11
海外TECH	DEV Community	Give more Attention to your README file	https://dev.to/harishash/give-more-attention-to-your-readme-file-3c76	Give more Attention to your README fileStarting out as a Web Developer can be quite overwhelming You are bombarded with so many different technologies to choose from But one thing that can make you stand out from all the other people starting out is the discipline you put into your projects And one of the best ways to add it in your projects is to write proper documentation of your process README mdReadme is a text file that is used by developers to explain and introduce their projects to the external users It contains the information that is needed to get acquainted with the corresponding project It s used as a way to answer all the frequent questions that other developers might have regarding the project such as identifying the technology stack or installing it for personal use Why should I write ReadmeReadme is usually ignored while adding projects to your repositories As a newbie it seems unnecessary to write long lines that probably no one is going to read But you might come back to your code after a while and that readme file is going to help you a lot in identifying what was what A good readme file should be as good as the project itself Readme is very important in growthAdding a readme file might seem as a small step as it is often ignored but this one small step can go a long way in your development career Your projects on GitHub are basically your portfolio It s very rare that you start landing big clients after starting out so until you make a name for yourself adding your projects in a presentable way to your repositories is the best way to showcase your talents to your possible clients If you re in a learning phase and trying to code on different test projects then it s best to add them to your repositories with a good description The best part about these descriptions is that even a non technical person maybe a recruiter can get an idea of your talents from these files Tips on writing a good Description Essentials Title Make sure to add specific and to the point titles that describe what the project is about The project s aim Mention what you want to achieve by making this project It s good to start developing with deliverables in mind Tech Stack Add what framework or library you re using and it d be super awesome if you add why you used it in the first place InstallationIf your project is a software or an app make sure that you add proper instructions on how to install it on whatever platform you re providing support for Really Stand Out If you re feeling a wee bit fancy and really want to make a good impression by going the extra mile consider adding these sections as well Table of contentsGIFs of project in actionScope of functionalities Project status SourcesOther informationLet me know what you guys think about Readme files Happy Developing	2021-12-03 10:28:57
海外TECH	DEV Community	Development and Test on Amazon Web Services | AWS White Paper Summary	https://dev.to/awsmenacommunity/development-and-test-onamazon-web-services-aws-white-paper-summary-48c9	Development and Test onAmazon Web Services AWS White Paper Summary IntroductionOrganizations write software for various reasons ranging from core business needs when the organization is a software vendor to customizing or integrating software Organizations also create different types of software web applications standalone applications automated agents and so on In all such cases development teams are pushed to deliver software of high quality as quickly as possible to reduce the time to market or time to production In this document “development and test refers to the various tools and practices applied when producing software Regardless of the type of software to be developed a proper set of development and test practices is key to success However producing applications not only requires software engineers but also IT resources which are subject to constraints like time money and expertise The software lifecycle typically consists of the following main elements This whitepaper covers aspects of the development build and test phases For each of these phases you need different types of IT infrastructure AWS provides multiple benefits to software development teams AWS offers on demand access to a wide range of cloud infrastructure services charging only for the resources that are used AWS helps eliminate both the need for costly hardware and the administrative pain that goes with owning and operating it Owning hardware and IT infrastructure usually involves a capital expenditure for a year period where most development and test teams need compute or storage for hours days weeks or months This difference in timescales can cause friction due to the difficulty for IT operations to satisfy simultaneous requests from project teams even as they are constrained by a fixed set of resources The result is that project teams spend a lot of time justifying sourcing and holding on to resources This time could be spent focusing on the main job By provisioning only the resources needed for the duration of development phases test runs or complete test campaigns your company can achieve important savings compared to investing up front in traditional hardware With the right level of granularity you can allocate resources depending on each project s needs and budget In addition to those economic benefits AWS also offers significant operational advantages such as the ability to set up a development and test infrastructure in a matter of minutes rather than weeks or months and to scale capacity up and down to provide the IT resources needed only when they are needed This document highlights some of the best practices and recommendations around development and test on AWS For example for the development phase this document discusses how to securely and durably set up tools and processes such as version control collaboration environments and automated build processes For the testing phase this document discusses how to set up test environments in an automated fashion and how to run various types of tests including side by side tests load tests stress tests resilience tests and more Development phaseRegardless of team size software type being developed or project duration development tools are mandatory to rationalize the process coordinate efforts and centralize production Like any IT system development tools require proper administration and maintenance Operating such tools on AWS not only relieves your development team from low level system maintenance tasks such as network configuration hardware setup and so on but also facilitates the completion of more complex tasks The following sections describe how to operate the main components of development tools on AWS Source code repositoryThe source code repository is a key tool for development teams As such it needs to be available and the data it contains source files under version control needs to be durably stored with proper backup policies Ensuring these two characteristicsーavailability and durabilityーrequires resources expertise and time investment that typically aren t a core competency of a software development team Building a source code repository on AWS involves creating an AWS CodeCommit repository AWS CodeCommit is a secure highly scalable managed source control service that hosts private GitHub repositories It eliminates the need for you to operate your own source control system and there is no hardware to provision and scale or software to install configure and operate Project management toolsIn addition to the source code repository teams often use additional tools such as issue tracking project tracking code quality analysis collaboration content sharing and so on Most of the time those tools are provided as web applications Like any other classic web application they require a server to run and frequently a relational database The web components can be installed on Amazon Elastic Compute Cloud Amazon EC with the database using Amazon Relational Database Service Amazon RDS for data storage Within minutes you can create Amazon EC instances which are virtual machines over which you have complete control A variety of different operating systems and distributions are available as Amazon Machine Images AMIs An AMI is a template that contains a software configuration operating system application server and applications that you can run on Amazon EC After you ve properly installed and configured the project management tool AWS recommends you create an AMI from this setup so you can quickly recreate that instance without having to reinstall and reconfigure the software Project management tools have the same needs as source code repositories they need to be available and data has to be durably stored While you can mitigate the loss of code analysis reports by recreating them against the desired repository version losing project or issue tracking information might have more serious consequences You can address the availability of the project management web application service by using AMIs to create replacement Amazon EC instances in case of failure You can store the application s data separately from the host system to simplify maintenance or migration operations Amazon Elastic Block Store Amazon EBS provides off instance storage volumes that persist independently from the life of an instance After you create a volume you can attach it to a running Amazon EC instance As such an Amazon EBS volume is provisioned and attached to the instance to store the data of the version control repository You achieve durability by taking point in time snapshots of the EBS volume containing the repository data EBS snapshots are stored in Amazon Simple Storage Service Amazon S a highly durable and scalable data store Objects in Amazon S are redundantly stored on multiple devices across multiple facilities in an AWS Region You can automate the creation and management of snapshots using Amazon Data Lifecycle Manager These snapshots can be used as the starting point for new Amazon EBS volumes and can protect your data for long term durability In case of a failure you can recreate the application data volume from the snapshots and recreate the application instance from an AMI To facilitate proper durability and restoration Amazon Relational Database Service Amazon RDS offers an easy way to set up operate and scale a relational database in AWS It provides cost efficient and resizable capacity while managing time consuming database administration tasks freeing the project team from this responsibility Amazon RDS Database instances DB instances can be provisioned in a matter of minutes Optionally Amazon RDS will ensure that the relational database software stays up to date with the latest patches The automated backup feature of Amazon RDS enables point in time recovery for DB instances allowing restoration of a DB instance to any point in time within the backup retention period An Elastic IP address provides a static endpoint to an Amazon EC instance and can be used in combination with DNS for example behind a DNS CNAME This helps teams to access their hosted services such as the project management tool in a consistent way even if infrastructure is changed underneath for example when scaling up or down or when a replacement instance is provisioned An Elastic IP Address provides a static endpoint to an Amazon EC instance As your development team grows or adds more tools to the project management instance you might require extra capacity for both the web application instance and the DB instance In AWS scaling instances vertically is an easy and straightforward operation You simply stop the EC instance change the instance type and start the instance Alternatively you can create a new web application server from the AMI on a more powerful Amazon EC instance type and replace the previous server You can use horizontal scaling by using Elastic Load Balancing adding more instances to the system by using AWS Auto Scaling In this case as you have more than one node you can use Elastic Load Balancing to distribute the load across all application nodes Amazon RDS DB instances can scale compute and memory resources with a few clicks on the AWS Management Console Use Elastic Load Balancing to distribute the load across all application nodesWhen you want to quickly set up a software development project on AWS and don t want to configure custom project management tools on EC you can use AWS CodeStar AWS CodeStar comes with a unified project dashboard and integration with Atlassian JIRA software a third party issue tracking and project management tool With the AWS CodeStar project dashboard you can easily track your entire software development process from a backlog work item to production code deployment On demand development environmentsDevelopers primarily use their local laptops or desktops to run their development environments This is typically where the integrated development environment IDE is installed where unit tests are run where source code is checked in and so on However there are a few cases where on demand development environments hosted in AWS are helpful AWS Cloud is a cloud based IDE that enables you to write run and debug your code with just a browser It includes a code editor debugger and terminal AWS Cloud comes prepackaged with essential tools for popular programming languages including JavaScript Python PHP Ruby Go C and more so you don t need to install files or configure your development machine to start new projects Because your AWS Cloud IDE is cloud based you can work on your projects from your office home or anywhere using an internet connected machine With AWS Cloud you can quickly share your development environment with your team enabling you to pair program and track each other s inputs in real time Stopping vs ending Amazon EC instancesWhenever development environments are not used for example during the hours when you are not working or when a specific project is on hold you can easily shut them down to save resources and cost There are two possibilities Stopping the instances which is roughly equivalent to hibernating the operating systemEnding the instances which is roughly equivalent to discarding the operating system When you stop an instance possible for Amazon EBS backed AMIs the compute resources are released and no further hourly charges for the instance apply The Amazon EBS volume stores the state and next time you start the instance it will have the working data as it did before you stopped it Integrating with AWS APIs and IDE enhancementsWith AWS you can now code against and control IT infrastructure either if the target platform of your project is AWS or if the project is about orchestrating resources in AWS The AWS SDK tools are available for multiple languages C Go JavaScript Node js Python Java Net PHP Ruby and for mobile platforms Android and iOS For developing and building Serverless applications AWS offers the Serverless Application Model AWS SAM open source framework which can be used with the AWS toolkits mentioned previously Build phaseThe process of building an application involves many steps including compilation resource generation and packaging For large applications each step involves multiple dependencies such as building internal libraries using helper applications generating resources in different formats generating the documentation and so on Some projects might require building the deliverables for multiple CPU architectures platforms or operating systems The complete build process can take many hours which has a direct impact on the agility of the software development team This impact is even stronger on teams adopting approaches like continuous integration where every commit to the source repository triggers an automated build followed by test suites Schedule buildsTo mitigate this problem teams working on projects with lengthy build times often adopt the “nightly build or neutral build approach or break the project into smaller sub projects or a combination of both Doing nightly builds involves a build machine checking out the latest source code from the repository and building the project deliverables overnight On demand buildsA more practical solution is to use more computational power for the build process On traditional environments where the build server runs on hardware acquired by the organization this option might not be viable due to economic constraints or provisioning delays A build server running on an Amazon EC instance can be scaled up vertically in a matter of minutes reducing build time by providing more CPU or memory capacity when needed A solution would be to take advantage of the on demand and pay as you go nature of AWS CodeBuild to run multiple builds in parallel You can run separate builds concurrently without waiting in a queue This also enables you to schedule automated builds at a specific time window If you use a build tool on EC instances running as a fleet of worker nodes the task distribution to the worker nodes can be done using a queue holding all the builds to process Worker nodes pick the next build to process as they are free To implement this system Amazon Simple Queue Service Amazon SQS offers a reliable highly scalable hosted queue service Amazon SQS makes it easy to create an automated build workflow working in close conjunction with Amazon EC and other AWS infrastructure services In this setup developers commit code to the source code repository which in turn pushes a build message into an Amazon SQS queue The worker nodes poll this queue to pull a message and run the build locally according to the parameters contained in the message for example the branch or source version to use You can further enhance this setup by dynamically adjusting the pool of worker nodes consuming the queue Auto Scaling is a service that makes it easy to scale the number of worker nodes up or down automatically according to predefined conditions With Auto Scaling worker nodes capacity can increase seamlessly during demand spikes to maintain quick build generation and decrease automatically during demand lulls to minimize costs You can define scaling conditions using Amazon CloudWatch a monitoring service for AWS Cloud resources For example Amazon CloudWatch can monitor the number of messages in the build queue and notify Auto Scaling that more or less capacity is needed depending on the number of messages in the queue The following diagram summarizes this scenario Amazon CloudWatch can monitor the number of messages in the build queue and notify Auto Scaling that more or less capacity is needed Storing build artifactsEvery time you produce a build you need to store the output somewhere Amazon S is an appropriate service for this Initially the amount of data to be stored for a given project is small but it grows over time as you produce more builds Here the pay as you go and capacity characteristics of S are particularly attractive When you no longer need the build output you can delete it or use S s lifecycle policies to delete or archive the objects to Amazon S Glacier storage class AWS CodeBuild by default uses S buckets to store the build outputs To distribute the build output for example to be deployed in test staging or production or to be downloaded to clients AWS offers several options You can distribute build output packages directly out of S by configuring bucket policies and or ACLs to restrict the distribution You can also share the output object using an S presigned URL Another option is to use Amazon CloudFront a web service for content delivery which makes it easy to distribute packages to end users with low latency and high data transfer speeds thereby improving the end user experience This can be helpful for example when a large number of clients are downloading install packages or updates Amazon CloudFront offers several options for example to authorize and or restrict access though a full discussion of this is out of scope for this document Testing phaseTests are a critical part of software development They ensure software quality but more importantly they help find issues early in the development phase lowering the cost of fixing them later during the project Tests come in many forms unit tests performance tests user acceptance tests integration tests and so on and all require IT resources to run Test teams face the same challenges as development teams the need for enough IT resources but only during the limited duration of the test runs Test environments change frequently and are different from project to project and may require different IT infrastructure or have varying capacity needs The AWS on demand and pay as you go value propositions are well adapted to those constraints AWS enables your test teams to eliminate both the need for costly hardware and the administrative pain that goes along with owning and operating it AWS also offers significant operational advantages for testers Test environments can be set up in minutes rather than weeks or months and a variety of resources including different instance types are available to run tests whenever they are needed Automating test environmentsThere are many software tools and frameworks available for automating the process of running tests but proper infrastructure must be in place This involves provisioning infrastructure resources initializing the resources with a sample dataset deploying the software to be tested orchestrating the test runs and collecting results The challenge is not only to have enough resources to deploy the complete application with all the different servers or services it might require but to be able to initialize the test environment with the right software and the right data over and over Test environments should be identical between test runs otherwise it is more difficult to compare results Another important benefit of running tests on AWS is the ability to automate them in various ways You can create and manage test environments programmatically using the AWS APIs CLI tools or AWS SDKs Tasks that require human intervention in classic environments allocating a new server allocating and attaching storage allocating a database and so on can be fully automated on AWS using AWS CodePipeline and AWS CloudFormation For testers designing tests suites on AWS means being able to automate a test down to the operation of the components which are traditionally static hardware devices Automation makes test teams more efficient by removing the effort of creating and initializing test environments and less error prone by limiting human intervention during the creation of those environments An automated test environment can be linked to the build process following continuous integration principles Every time a successful build is produced a test environment can be provisioned and automated tests run on it The following sections describe how to automatically provision Amazon EC instances databases and complete environments Provisioning instancesYou can easily provision Amazon EC instances from AMIs An AMI encapsulates the operating system and any other software or configuration files pre installed on the instance When you launch the instance all the applications are already loaded from the AMI and ready to run For information about creating AMIs refer to the Amazon EC documentation The challenge with AMI based deployments is that each time you need to upgrade software you have to create a new AMI Although the process of creating a new AMI and deleting an old one can be completely automated using EC Image Builder you must define a strategy for managing and maintaining multiple versions of AMIs An alternative approach is to include only components into the AMI that don t change often operating system language platform and low level libraries application server and so on More volatile components like the application under development can be fetched and deployed to the instance at runtime For more details on how to create self bootstrapped instances see Bootstrapping Provisioning databasesTest databases can be efficiently implemented as Amazon RDS database instances Your test teams can instantiate a fully operational database easily and load a test dataset from a snapshot To create this test dataset you first provision an Amazon RDS instance After injecting the dataset you create a snapshot of the instance From that time every time you need a test database for a test environment you can create one as an Amazon RDS instance from that initial snapshot See Restoring from a DB snapshot Each Amazon RDS instance started from the same snapshot will contain the same dataset which helps ensure that your tests are consistent Provisioning complete environmentsWhile you can create complex test environments containing multiple instances using the AWS APIs command line tools or the AWS Management Console AWS CloudFormation makes it even easier to create a collection of related AWS resources and provision them in an orderly and predictable fashion AWS CloudFormation uses templates to create and delete a collection of resources together as a single unit a stack A complete test environment running on AWS can be described in a template which is a text file in JSON or YAML format Because templates are just text files you can edit and manage them in the same source code repository you use for your software development project That way the template will mirror the status of the project and test environments matching older source versions can be easily provisioned This is particularly useful when dealing with regression bugs In just a few steps you can provision the full test environment enabling developers and testers to simulate a bug detected in older versions of the software AWS CloudFormation templates also support parameters that can be used to specify a specific software version to be loaded the Amazon EC instance sizes for the test environment the dataset to be used for the databases and so on Provisioning cloud applications can be a challenging process that requires you to perform manual actions write custom scripts maintain templates or learn domain specific languages You can now use the AWS Cloud Development Kit AWS CDK an open source software development framework for defining cloud infrastructure as code with modern programming languages and deploying it through AWS CloudFormation AWS CDK uses familiar programming languages such as TypeScript JavaScript Python Java C Net and Go for modeling your applications For more information about how to create and automate deployments on AWS using AWS CloudFormation see AWS CloudFormation Resources Load testingFunctionality tests running in controlled environments are valuable tools to ensure software quality but they give little information on how an application or a complete deployment will perform under heavy load For example some websites are specifically created to provide a service for a limited time ticket sales for sports events special sales limited edition launches and so on Such websites must be developed and architected to perform efficiently during peak usage periods In some cases the project requirements clearly state the minimum performance metrics to be met under heavy load conditions for example search results must be returned in under milliseconds ms for up to concurrent requests and load tests are exercised to ensure that the system can sustain the load within those limits For other cases it is not possible or practical to specify the load a system should sustain In such cases load tests are performed to measure the behavior under heavy load conditions The objective is to gradually increase the load of a system to determine the point where the performance degrades in such a way that the system cannot operate anymore Load tests simulate heavy inputs that exercise and stress a system Depending on the project inputs can be a large number of concurrent incoming requests a huge dataset to process and so on One of the main difficulties in load testing is generating large enough amounts of inputs to push the tested system to its limits Typically you need large amounts of IT resources to deploy the system to test and to generate the test input which requires further infrastructure Because load tests generally don t run for more than a couple of hours the AWS pay as you go model nicely fits this use case In Serverless architectures using AWS services such as AWS Lambda Amazon API Gateway AWS Step Functions and so on load testing can help identify custom code in Lambda functions that may not run efficiently as traffic scales up It also helps to determine an optimum timeout value by analyzing your functions running duration to identify problems with a dependency service One of the most popular tools to perform this task is Artillery Community Edition which is an open source tool for testing serverless APIs You can also use Distributed Load Testing on AWS to automate application testing understand how it performs at scale and fix bottlenecks before releasing your application Network load testingTesting an application or service for network load involves sending large numbers of requests to the system being tested There are many software solutions available to simulate request scenarios but using multiple Amazon EC instances may be necessary to generate enough traffic Amazon EC instances are available on demand and are charged by the hour which makes them well suited for network load testing scenarios Keep in mind the characteristics of different instance types Generally larger instance types provide more input output I O network capacity the primary resource consumed during network load tests With AWS test teams can also perform network load testing on applications that run outside of AWS Having load test agents dispersed in different Regions of AWS enables testing from different geographies for example to get a better understanding of the end user experience In that scenario it makes sense to collect log information from the instances that simulate the load Those logs contain important information such as response times from the tested system By running the load agents from different Regions the response time of the tested application can be measured for different geographies This can help you understand the worldwide user experience Because you can end load testing Amazon EC instances right after the test you should transfer log data to S for storage and later analysis When you plan to run high volume network load tests directly from your EC instances to other EC instances follow the Amazon EC Testing Policy Load testing for AWSLoad testing an application running on AWS is useful to make sure that elasticity features are correctly implemented Testing a system for network load is important to make sure that for web front ends Auto Scaling and Elastic Load Balancing configurations are correct Auto Scaling offers many parameters and can use multiple conditions defined with Amazon CloudWatch to scale the number of front end instances up or down These parameters and conditions influence how fast an Auto Scaling group will add or remove instances An Amazon EC instance s post provisioning time might also affect an application s ability to scale up quickly enough After initialization of the operating system running on Amazon EC instances additional services are initialized such as web servers application servers memory caches middleware services and so on The initialization time of these different services affects the scale up delay especially when additional software packages need to be pulled down from a repository Load testing provides valuable metrics on how fast additional capacity can be added into a particular system Auto Scaling is not only used for front end systems You might also use it for scaling internal groups of instances such as consumers polling an Amazon SQS queue or workers and deciders participating in an Amazon Simple Workflow Service Amazon SWF workflow In both cases load testing the system can help ensure you ve correctly implemented and configured Auto Scaling groups or other automated scaling techniques to make your final application as cost effective and scalable as possible Cost optimization with Spot instancesLoad testing can require many instances especially when exercising systems that are designed to support a high amount of load While you can provision Amazon EC instances on demand and discard them when the test is completed while only paying by the hour there is an even more cost effective way to perform those tests using Amazon EC Spot Instances Spot Instances enable customers to bid for unused Amazon EC capacity Instances are charged the Spot Price set by Amazon EC which fluctuates depending on the supply of and demand for Spot Instance capacity To use Spot Instances place a Spot Instance request specifying the instance type the desired Availability Zone the number of Spot Instances to run and the maximum price to pay per instance hour The Spot Price history for the past days is available via the Amazon EC API or the AWS Management Console If the maximum price bid exceeds the current Spot Price the request is fulfilled and instances are started The instances run until either they are ended or the Spot Price increases above the maximum price whichever is sooner User acceptance testingThe objective of user acceptance testing is to present the current release to a testing team representing the final user base to determine if the project requirements and specification are met When users can test the software earlier they can spot conceptual weaknesses that have been introduced during the analysis phase or clarify gray areas in the project requirements By testing the software more frequently users can identify functional implementation errors and user interface or application flow misconceptions earlier lowering the cost and impact of correcting them Flaws detected by user acceptance testing may be very difficult to detect by other means The more often you conduct acceptance tests the better for the project because end users provide valuable feedback to development teams as requirements evolve However like any other test practice acceptance tests require resources to run the environment where the application to be tested will be deployed As described in previous sections AWS provides on demand capacity as needed in a cost effective way which is also appropriate for acceptance testing Using some of the techniques described previously AWS enables complete automation of the process of provisioning new test environments and of disposing environments no longer needed Test environments can be provided for certain times only or continuously from the latest source code version or for every major release By deploying the acceptance test environment within Amazon VPC internal users can transparently access the application to be tested Such an application can also be integrated with other production services inside the company such as LDAP email servers and so on offering a test environment to the end users that is even closer to the real and final production environment Side by side testingSide by side testing is a method used to compare a control system to a test system The goal is to assess whether changes applied to the test system improve a desired metric compared to the control system You can use this technique to optimize the performance of complex systems where a multitude of different parameters can potentially affect the overall efficiency Knowing which parameter will have the desired effect is not always obvious especially when multiple components are used together and influence the performance of each other You can also use this technique when introducing important changes to a project such as new algorithms caches different database engines or third party software In such cases the objective is to ensure your changes positively affect the global performance of the system After you ve deployed the test and control systems send the same input to both using load testing techniques or simple test inputs Finally collect performance metrics and logs from both systems and compare them to determine if the changes you introduced in the test system present an improvement over the control system By provisioning complete test environments on demand you can perform side by side tests efficiently While you can do side by side testing without automated environment provisioning using the automation techniques described above makes it easier to perform those tests whenever needed taking advantage of the pay as you go model of AWS In contrast with traditional hardware it may not be possible to run multiple test environments for multiple projects simultaneously Side by side tests are also valuable from a cost optimization point of view By comparing two environments in different AWS accounts you can easily come up with cost performance ratios to compare both environments By continuously testing architecture changes for cost performance you can optimize your architectures for efficiency Fault tolerance testingWhen AWS is the target production environment for the application you ve developed some specific test practices provide insights into how the system will handle corner cases such as component failures AWS offers many options for building fault tolerant systems Some services are inherently fault tolerant for example Amazon S Amazon DynamoDB Amazon SimpleDB Amazon SQS Amazon Route Amazon CloudFront and so on Other services such as Amazon EC Amazon EBS and Amazon RDS provide features that help architect fault tolerant and highly available systems For example Amazon RDS offers the Multi Availability Zone option that enhances database availability by automatically provisioning and managing a replica in a different Availability Zone Many AWS customers run mission critical applications on AWS and they need to make sure their architecture is fault tolerant As a result an important practice for all systems is to test their fault tolerance capability While a test scenario exercises the system using similar techniques to load testing some components are taken down on purpose to check if the system is able to recover from such simulated failure You can use the AWS Management Console or the CLI to interact with the test environment For example you might end Amazon EC instances and then test whether an Auto Scaling group is working as expected and a replacement instance automatically provisioned You can also automate this kind of test by integrating AWS Fault Injection Simulator with your CI CD pipeline It is a best practice is to use automated tools that for example occasionally and randomly disrupt Amazon EC instances With Fault Injection Simulator you can stress an application by creating disruptive events such as a sudden increase in CPU or memory consumption to observe how the system responds and implement improvements Resource managementWith AWS your development and test teams can have their own resources scaled according to their own needs Provisioning complex environments or platforms composed of multiple resources can be done using AWS CloudFormation stacks or some of the other automation techniques described in this whitepaper In large organizations comprising multiple teams it is a good practice to create an internal role or service responsible for centralizing and managing IT resources running on AWS This role typically consists of Promoting the internal development and test practices described hereDeveloping and maintaining template AMIs and template AWS CloudFormation stacks with the different tools and platforms used in your organizationCollecting resource requests from project teams and provisioning resources on AWS according to your organization s policies including network configuration such as Amazon VPC and security configurations such as Security Groups and IAM credentials Monitoring resource usage and charges using AWS Cost Explorer and allocating these to team budgetsYou can use the AWS Service Catalog to achieve the tasks above or you might want to develop your own internal provisioning and management portal for a tighter integration with internal processes You can do this by using one of the AWS SDKs which allow programmatic access to resources running on AWS Cost allocation and multiple AWS accountsSome customers have found it helpful to create specific accounts for development and test activities This can be important when your production environment also runs on AWS and you need to separate teams and responsibilities Separate accounts are isolated from each other by default so that for example development and test users do not interfere with production resources To enable collaboration AWS offers a number of features that enable sharing of resources across accounts such as Amazon S objects AMIs and Amazon EBS snapshots To separate out and allocate the cost for the various activities and phases of the development and test cycle AWS offers various options One option is to use separate accounts for example for development testing staging and production and each account will have its own bill You can also consolidate multiple accounts using consolidated billing for AWS Organizations to simplify costs and take advantage of quantity discounts with a single bill Another option is to make use of the monthly cost allocation report which enables you to organize and track your AWS costs by using resource tagging In the context of development and test tags can represent the various stages or teams of the development cycle though you are free to choose the dimensions you find most helpful ConclusionDevelopment and test practices require certain resources at certain times for the development cycle In traditional environments those resources might not be available at all or not in the necessary timeframe When those resources are available they provide a fixed amount of capacity that is either insufficient especially in variable activities like testing or wasted but paid for when the resources are not used AWS offers a cost effective alternative to traditional development and test infrastructures Instead of waiting weeks or even months for hardware you can instantly provision resources scale up as the workload grows and release resources when they are no longer needed Whether development and test environments consist of a few instances or hundreds whether they are needed for a few hours or you still pay only for what you use AWS is a programming language and operating system agnostic platform and you can choose the development platform or programming model used in your business This flexibility enables you to focus on your project not on operating and maintaining your infrastructure AWS also enables possibilities that are difficult to realize with traditional hardware You can fully automate resources on AWS so that environments can be provisioned and decommissioned without human intervention You can start development environments on demand kick off builds when needed unconstrained by the availability of resources provision test resources and automatically orchestrate entire test runs or campaigns AWS offers you the ability to experiment and iterate with a rapidly changeable infrastructure Your project teams are free to use inexpensive capacity to perform any kind of tests or to experiment with new ideas with no upfront expenses or long term commitments making AWS a platform of choice for development and test ReferenceOriginal paper	2021-12-03 10:11:57
海外TECH	DEV Community	AWS Sagemaker Best Practices Packt Book Review	https://dev.to/aws-heroes/aws-sagemaker-best-practices-packt-book-review-1hjh	AWS Sagemaker Best Practices Packt Book Review weeks ago I was invited from Packt publishing team to review on the awesome books about AWS Sagemaker best practices as I am AWS ML hero Book chapters Sagemaker OverviewThis chapter provides an overview of whole ML pipeline preparing building training tuning deployment and monitoring It also provides a data preparation capabilities such as Sagemaker Ground Truth SageMaker Data Wrangler Sagemaker processing Feature store and Clarify It also provides a feature tour about model building capabilities such as Sagemaker studio Sagemaker notebook instances Built in algorithms Bring your own container BYOC scripts and algorithms It also provides an overview for training and tuningcapabilities such as SageMaker training jobs Autopilot Hyperparameter Optimization HPO SageMaker Debugger SageMaker Experiments ML phases on Sagemaker For data preparation For operationsFor model training Data Science EnvironmentsThis chapter provides an overview of how to create managed data science environments to scale and create repeatable environments for your model building activities using IaC or CaC It also provides an overview for Cloudformation importance and capabilities ConsistencyImproved managementReducing manual approvals Reducing hand offs in siloed teams Providing centralized governance By ensuring environments are provisioned across teams using only approved configurations AWS Service Catalog and its importance in such approach You will get a brief overview of the machine learning ML use case ML use case mentioned is prediction of a value for a particular type of air quality measurement for example pm given location weather station and date that s can be treated using regression XGBoost model Data Labeling with Amazon SageMaker Ground TruthThis chapter provides an review of labeling data using SageMaker Ground Truth and its challenges such as Challenges with labeling data at scaleAddressing unique labeling requirements with custom labeling workflowsUsing active learning to reduce labeling timeSecurity and permissions private workforces Data Preparation at Scale Using AWS SageMaker Data Wrangler and ProcessingIn this chapter the following topics are covered Visual data preparation with Data WranglerBias detection and explainability with Data WranglerData preparation at scale with SageMaker ProcessingDifference between Data Wrangler and Spark in EMR according to dataset size My personal feedback on this chapter is that it needs more clarification and examples Centralized Feature Repository with AWS SageMaker Feature StoreThis chapter we are going to cover the following main topics Basic concepts of SageMaker Feature Store Creating reusable features to reduce feature inconsistencies and inference latency Designing solutions for near real time ML predictions Training and Tuning at ScaleThis chapter covers the following topics ML training at scale with SageMaker distributed libraries Difference between data parallelism and model parallelism Some considerations to be taken before choosing between data amp model parallelism Automated model tuning with SageMaker hyperparameter tuning Organizing and tracking training jobs with SageMaker Experiments Best practices to consider while configuring hyperparameter jobs on Amazon SageMaker Profile Training Jobs with Amazon SageMaker DebuggerThis chapter covers the following main topics Amazon SageMaker Debugger essentialsReal time monitoring of training jobs using built in and custom rulesGain insight into the training infrastructure and training framework by Analyzing and visualizing the system and framework metrics generated by the profiler Analyzing the profiler report generated by SageMaker Debugger Managing Models at Scale Using a Model RegistryA model registry is a central repository for metadata related to a certain model version It contains details about how the model was created how it performed and where and how it was deployed Additional features such as approval workflows and notifications are frequently included in model registry services or solutions This chapter covers the following topics Using a model registryChoosing a model registry solutionManaging models using the Amazon SageMaker model registry Updating Production Models Using SageMaker Endpoint Production VariantsThis chapter covers the following main topics Basic concepts of Amazon SageMaker Endpoint Production VariantsDeployment strategies for updating ML models with Amazon SageMaker Endpoint Production VariantsSelecting an appropriate deployment strategy Optimizing Model Hosting and Inference CostsThis chapter covers the following topics Real time inference versus batch inferenceDeploying multiple models behind a single inference endpointScaling inference endpoints to meet inference traffic demandsUsing Elastic Inference for deep learning modelsOptimizing models with SageMaker Neo Monitoring Production Models with Amazon SageMaker Model Monitor and ClarifyThis chapter covers the following main topics Basic concepts of Amazon SageMaker Model Monitor and AmazonSageMaker ClarifyEnd to end architectures for monitoring ML modelsBest practices for monitoring ML models Machine Learning Automated WorkflowsThis chapter covers the following topics Considerations for automating your SageMaker ML workflowsBuilding ML workflows with Amazon SageMaker PipelinesCreating CI CD ML pipelines using Amazon SageMaker projects Well Architected Machine Learning with Amazon SageMakerThis chapter covers the following main topics Best practices for operationalizing ML workloadsBest practices for securing ML workloadsBest practices for building reliable ML workloadsBest practices for building performant ML workloadsBest practices for building cost optimized ML workloads Managing SageMaker Features across AccountsThis chapter discusses the following topics as they relate to managing SageMaker features across multiple AWS accounts Examining an overview of the AWS multi account environmentUnderstanding the benefits of using multiple AWS accounts with Amazon SageMakerExamining multi account considerations with Amazon SageMaker ConclusionI really enjoyed reading this article and my personal rate for it is because it gives a very good overview for best practices for implementing ML on AWS Sagemaker Happy reading	2021-12-03 10:09:01
海外TECH	DEV Community	Project 2:JavaScript Clock	https://dev.to/prachigarg19/project-2javascript-clock-5a0c	Project JavaScript ClockWelcome to my Build Js Projects in Days Series This is day and project If you haven t read the other articles in this series please check them out first I ll list them at the end of this article As mentioned in my previous article This is the Day challenge of Wes Bos Javascript course Here is the final result As always before starting download the starter files from here I ve made a separate article on how to download starter files you can check it out here PART HTML lt DOCTYPE html gt lt html lang en gt lt head gt lt meta charset UTF gt lt meta http equiv X UA Compatible content IE edge gt lt meta name viewport content width device width initial scale gt lt title gt Clock lt title gt lt link rel stylesheet href style css gt lt head gt lt body gt lt div class container gt lt div class hand hour hand id hour gt lt div gt lt div class hand min hand id min gt lt div gt lt div class hand sec hand id sec gt lt div gt lt div gt lt script src script js gt lt script gt lt body gt lt html gt PART CSSNow we are going to style our project margin padding body background color rgb display flex justify content center container border px solid white border radius position absolute margin top rem height vw width vw transition ease in out hand position relative top width left height rem background color white transform rotate deg transform origin hour hand sec hand min hand position absolute Let s look at the styling part for hand class hand position relative top width left height rem background color white transform rotate deg transform origin Position has been set to relative so that hands can be positioned with respect to container that is the clock boundary Then we can easily set top and width accordingly to center the hands Hand class will be a common class to all hour min and sec hand We have used transform deg to start all the hands from o clock as div content is horizontal by default Here transform origin has been used as on applying transform rotate hands will be rotated from center by default hence we set origin to to rotate it from the end One issue that we will face is that our hands will appear in block format as div is a block property by default To solve this we will use position absolute at individual hand classes hour hand sec hand min hand position absolute Refer to this for more details on stacking divs part PART JAVASCRIPTNow we will make our project interactive Here the idea is to change transform rotate property for each hand class as per change in hours min and sec and calling each function again and again every sec using setInterval function Let s look at the function for hour hand function changeHour let hour document getElementById hour let hangle if date getHours lt hangle date getHours else hangle date getHours hour style transform rotate hangle deg Here we will take two cases If our hour is less than then we will simply multiply it by deg as hour hand moves deg after every hour and we will add it to deg as initially our hand is at deg If our hour is gt then we will subtract them by Here s an example If hour returned by getHours is am then our hour hand will be at degrees If is returned pm then will give degrees Same logic goes for min and sec function changeMin date new Date let min document getElementById min let mangle date getMinutes min style transform rotate mangle deg function changeSec date new Date let sec document getElementById sec let sangle date getSeconds sangle sec style transform rotate sangle deg Now we have to call these function every second Here we will use setInterval function time interval in milisecond which will keep on calling function passed as parameter after time interval passed as second parameter until closeInterval is closed which we won t call since we want our function to keep on running setInterval changeSec setInterval changeMin setInterval changeHour Previous article from this series Project Day Things learnt Stacking divs transform origin Source CodeFeel free to suggest changes ConclusionThat s it for today s project Next project will be on CSS variables If you have any doubts or suggestions please do let me know in the comment section I ll be more than happy to interact with you If you like this series and want to be a part of it do consider following me at prachigargThanks for reading	2021-12-03 10:08:51
海外TECH	Engadget	Facebook allowed ads that promoted anti-vaccine messages	https://www.engadget.com/facebook-allowed-ads-that-promoted-an-anti-vaccine-message-104008203.html?src=rss	Facebook allowed ads that promoted anti vaccine messagesFacebook said that it s cracking down on anti vaccine messages but it recently allowed multiple anti vaccine ads to run on its site CNN nbsp has reported One ad compared the rollout of vaccines to the Holocaust and another promoted T shirts with the message quot I m originally from America but I currently reside in Germany quot The ads were run by merchandise companies including one called quot Ride the wave quot that spent with Facebook s parent Meta Another company called quot Next Level Goods quot spent on ads for items like anti vaccine T shirts according to the report Facebook now under parent company Meta recently vowed to remove claims that COVID vaccines can harm children among others It also said that it deleted more than million pieces of content as part of its fight against misinformation in an ongoing partnership with the CDC WHO and other health authorities nbsp Meta said that the ads comparing COVID policies to Nazi German or calling the vaccines poison went against its misinformation policies However it still allowed them to slip through in part because it doesn t review all ads manually researcher Laura Edelson told CNN It also has a weaker moderation approach to commercial pages compared to those associated with political campaigns she added nbsp Facebook is already under heavy pressure for the US and other governments over privacy misinformation and other issues A trove of documents revealed recently by whistleblower Frances Haugen showed that the company was aware that harmful content increased engagement yet failed to deploy countermeasures recommended in its own studies quot Facebook over and over again has shown it chooses profit over safety quot she said nbsp	2021-12-03 10:40:08
海外TECH	Engadget	Nintendo is adding the original 'Paper Mario' to the Switch Online Expansion Pack	https://www.engadget.com/nintendo-paper-mario-switch-online-expansion-pack-101657918.html?src=rss	Nintendo is adding the original x Paper Mario x to the Switch Online Expansion PackNintendo launched its paid Switch Online Expansion Pack tier with a very limited number of N games in October And according to Kotaku they were plagued with various technical issues such as wonky layouts poor graphics quality and bugs that cause crashes Soon though the gaming giant will add a Nintendo classic to the list of titles you can access with the subscription service The original Paper Mario game that was released over years ago nbsp The base Switch Online subscription which gives you access to NES and SNES titles costs a year If you want to play the N games the expansion pack offers you ll have pony up a year or for a family plan In addition to getting access to N games the more expensive tier also include retro SEGA Genesis games and the Animal Crossing Happy Home Paradise DLC There s still a huge jump from to though and the addition of Paper Mario could convince fans of the series to subscribe nbsp Here s a summary of what the turn based game is about quot After Bowser steals the Star Rod and kidnaps Princess Peach Mario plots to rescue the seven Star Spirits and free the Mushroom Kingdom from the Koopa s rule As Mario travels from the tropical jungles of Lavalava Island to the frosty heights of Shiver Mountain he ll need all the help he can get Master the abilities of the seven Star Spirits and the other allies joining the adventure to aid our hero on the battlefield quot Paper Mario for the N will be available to Expansion Pack subscribers starting on December th nbsp nbsp	2021-12-03 10:16:57
海外TECH	CodeProject Latest Articles	ARC4 Encryption Library	https://www.codeproject.com/Articles/5319044/ARC4-Encryption-Library	class	2021-12-03 10:42:00
海外科学	BBC News - Science & Environment	Gene edited sex selection may spare animal suffering	https://www.bbc.co.uk/news/science-environment-59505112?at_medium=RSS&at_campaign=KARANGA	industry	2021-12-03 10:01:11
医療系	医療介護 CBnews	新型コロナ特例評価は継続、中医協で一致-感染防止加算、診療側が施設基準緩和を主張	https://www.cbnews.jp/news/entry/20211203191743	中央社会保険医療協議会	2021-12-03 19:40:00
医療系	医療介護 CBnews	基本的施策にケアラーの早期発見・相談の場確保も-北海道が支援条例の素案公表	https://www.cbnews.jp/news/entry/20211203191955	素案	2021-12-03 19:35:00
医療系	医療介護 CBnews	看護の賃上げ「診療報酬で」公的価格委員会-来年10月以降、実効性担保など課題	https://www.cbnews.jp/news/entry/20211203184836	診療報酬	2021-12-03 19:05:00
ニュース	BBC News - Home	Gene edited sex selection may spare animal suffering	https://www.bbc.co.uk/news/science-environment-59505112?at_medium=RSS&at_campaign=KARANGA	industry	2021-12-03 10:01:11
ニュース	BBC News - Home	Storm Arwen: Army called in after a week without power	https://www.bbc.co.uk/news/uk-england-tyne-59516192?at_medium=RSS&at_campaign=KARANGA	arwen	2021-12-03 10:42:53
ニュース	BBC News - Home	Selfridges set for £4bn sale to Thai retail giant	https://www.bbc.co.uk/news/business-59517819?at_medium=RSS&at_campaign=KARANGA	central	2021-12-03 10:04:58
ニュース	BBC News - Home	Retailers make shocking petrol profit, says RAC	https://www.bbc.co.uk/news/business-59508286?at_medium=RSS&at_campaign=KARANGA	prices	2021-12-03 10:32:31
LifeHuck	ライフハッカー［日本版］	幸せな社員は創造性が3倍、生産性は31％、売上は37％高い	https://www.lifehacker.jp/2021/12/245162great_place_to_work.html	前野隆司	2021-12-03 20:00:00
北海道	北海道新聞	ちゃんこ店員宅に現金２０００万　日大、田中容疑者の理事を解任	https://www.hokkaido-np.co.jp/article/618876/	所得税法	2021-12-03 19:18:00
北海道	北海道新聞	コープ農業賞、清水の「あすなろ」最高賞　高品質生乳を評価	https://www.hokkaido-np.co.jp/article/618845/	販売会社	2021-12-03 19:12:33
北海道	北海道新聞	倉庫侵入のヒグマ、体重４２５キロ　羅臼で過去最大　別に２頭、警戒続く	https://www.hokkaido-np.co.jp/article/618850/	駆除	2021-12-03 19:11:13
北海道	北海道新聞	「もっと冷えて」　阿寒湖畔スキー場、コース整備急ピッチ　月内に合宿４００人	https://www.hokkaido-np.co.jp/article/618838/	急ピッチ	2021-12-03 19:07:18
北海道	北海道新聞	＜並行在来線　迫る存廃　有識者に聞く＞４　試される住民の本気度　いすみ鉄道元社長・鳥塚亮さん（６１）	https://www.hokkaido-np.co.jp/article/618848/	第三セクター	2021-12-03 19:05:19
北海道	北海道新聞	運輸局と道東バス事業者７社がサイト開設　空港、観光地結ぶバス路線一目で	https://www.hokkaido-np.co.jp/article/618813/	北海道運輸局	2021-12-03 19:02:33
IT	週刊アスキー	「PlayStation Partner Awards 2021 Japan Asia」の「GRAND AWARD」受賞3タイトルが発表	https://weekly.ascii.jp/elem/000/004/077/4077049/	「PlayStationPartnerAwardsJapanAsia」の「GRANDAWARD」受賞タイトルが発表ソニー・インタラクティブエンタテインメントは、ここ年でヒットしたPlayStationPlayStationフォーマットのタイトルを表彰する「PlayStationPartnerAwardsJapanAsia」を開催。	2021-12-03 19:10:00
IT	週刊アスキー	『三國志 覇道』でゲーミングスマートフォン「ROG Phone 5s」が当たるキャンペーンを実施中！	https://weekly.ascii.jp/elem/000/004/077/4077051/	rogphones	2021-12-03 19:10:00
マーケティング	AdverTimes	アサヒグループHD、サステナブル関連事業の新会社を設立	https://www.advertimes.com/20211203/article370520/	株式会社	2021-12-03 10:51:41
海外TECH	reddit	【クソスレ】誕生日なので盛大に飲む！	https://www.reddit.com/r/newsokunomoral/comments/r7w5ic/クソスレ誕生日なので盛大に飲む/	ewsokunomorallinkcomments	2021-12-03 10:24:59