投稿時間:2023-08-10 18:23:44 RSSフィード2023-08-10 18:00 分まとめ(28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
IT	気になる、記になる…	PayPayギフトカード、一部のiOS搭載端末でチャージ画面に自動遷移しない事象があることを案内	https://taisy0.com/2023/08/10/175191.html	paypay	2023-08-10 08:50:20
IT	気になる、記になる…	povo2.0、期間限定トッピング｢データ追加1GB (180日間)｣を提供開始 ｰ 1,260円/回	https://taisy0.com/2023/08/10/175188.html	提供開始	2023-08-10 08:33:58
IT	ITmedia 総合記事一覧	[ITmedia News] ロッキン、NHK報道に抗議　「約束を台無しにするリーク報道は迷惑」　総合Pが怒りの声明	https://www.itmedia.co.jp/news/articles/2308/10/news155.html	itmedia	2023-08-10 17:45:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 「SHIBUYA TSUTAYA」全面改修、どうなる？	https://www.itmedia.co.jp/business/articles/2308/10/news138.html	itmedia	2023-08-10 17:16:00
AWS	AWS Japan Blog	【開催報告】AWS re:Inforce 2023 re:Cap Online Seminar – 昼の部	https://aws.amazon.com/jp/blogs/news/aws-reinforce-2023-recap-seminar/	inforcerecaponlineseminar	2023-08-10 08:13:02
python	Pythonタグが付けられた新着投稿 - Qiita	Minecraftサーバーを起動させるDiscord BotをPythonで	https://qiita.com/insane_catt/items/f8cc4053a65334a8c9c4	discordbot	2023-08-10 17:55:39
python	Pythonタグが付けられた新着投稿 - Qiita	【Python】最小の差	https://qiita.com/Takuya__/items/ad8958e601d4f926a8e6	defsmallestdifferenc	2023-08-10 17:50:13
GCP	gcpタグが付けられた新着投稿 - Qiita	IBM Cloud(VPC) x Google Cloud IPsecVPN接続	https://qiita.com/khoshina/items/d75e25d492c7b83ccca4	cloud	2023-08-10 17:42:04
技術ブログ	Developers.IO	RustのValidator Libraryのgardeを使ってみる	https://dev.classmethod.jp/articles/rust-garde/	garde	2023-08-10 08:54:00
技術ブログ	Developers.IO	Alteryx のログの情報を使用して条件付きでワークフローを実行する方法	https://dev.classmethod.jp/articles/logs-execute-conditional-workflow-jp/	alteryx	2023-08-10 08:50:51
技術ブログ	Developers.IO	How to use log data to execute a workflow conditionally in Alteryx	https://dev.classmethod.jp/articles/logs-execute-conditional-workflow-en/	etoextractthelogsfromthe	2023-08-10 08:49:19
海外TECH	DEV Community	7 GitHub Repositories to help you Master Flutter in no time! 🚀	https://dev.to/yatendra2001/7-github-repositories-to-help-you-master-flutter-in-no-time-pi0	GitHub Repositories to help you Master Flutter in no time Wassup guys Did you know that a whopping of developers turn to GitHub for learning If you re part of this statistic and have a keen interest in diving into Flutter Google s fantastic UI toolkit then you re in for a treat In this blog post we re going to walk you through the top Flutter GitHub repositories that will set you on the path to becoming a Flutter pro So let s dive right in Flutter s Official RepositoryThis is the heart of Flutter Here you ll find its source code comprehensive documentation ongoing issues and pull requests What s more you can actively contribute and immerse yourself in the ever growing community of Flutter enthusiasts Dive in and feel the Flutter love GitHub Repo Flutter SamplesLooking for hands on examples This repository is a treasure trove of Flutter demos highlighting different facets of the framework From widgets and animations to state management techniques it s all here for you to explore GitHub Repo Flutter Widget Examples RepositoryCurated by the talented Pawan Kumar this repository is a goldmine of live example apps Whether you re into e commerce chat apps music platforms or news outlets there s something here for everyone GitHub Repo Flutter GalleryWant to see Flutter s potential This repository showcases top notch Flutter UIs flaunting both material design and Cupertino styles Plus you can run the gallery app on your device or even in your browser to see it in action GitHub Repo Flutter AwesomeAs the name suggests this repository is genuinely awesome It s a curated list of top tier Flutter resources from libraries and tools to articles videos and podcasts It s your one stop shop for all things Flutter GitHub Repo Flutter CommunityWant to feel the pulse of the Flutter community This repository is your gateway Discover projects events articles podcasts and more Plus connect with fellow Flutter fans on platforms like Discord Medium and YouTube GitHub Repo Awesome Flutter UIIf you re seeking inspiration look no further This repository is brimming with stunning Flutter UI templates Whether you re designing for e commerce social media travel or food delivery there s a template here to spark your creativity GitHub Repo Wrapping UpAnd there you have it I hope this guide has given you a clearer roadmap to mastering Flutter using GitHub If you found this post helpful drop a like and do share it with friends and fellow developers Before we go Thanks for reading Consider following me for more insights and tips I share insights on flutter open source amp software development to help you become a x developer Got any doubt or wanna chat React out to me on twitter or linkedin	2023-08-10 08:41:41
海外TECH	DEV Community	The Role of Queues in Building Efficient Distributed Applications	https://dev.to/amplication/the-role-of-queues-in-building-efficient-distributed-applications-1i6e	The Role of Queues in Building Efficient Distributed Applications IntroductionWhen building mission critical applications that manage large workloads you must ensure our systems can handle the workloads In some use cases we can handle the demand with autoscaling policies on the infrastructure so that our infrastructure can scale up or down based on the demand However there are certain use cases where this just isn t enough For example consider the following use case A user wishes to manage a content portfolio of all the articles a person has written This user then inputs a set of URLs URLs onto the system The system then visits these URLs and scrapes certain information needed to build the portfolio This can include the Article Name Published Date Outline Reading Time and Banner Image The system then stores it in an internal database A simple flowchart of this process is depicted below Figure A flowchart of the content portfolio workflowOn its own this process seems quite simple But this can cause a lot of issues on a large scale The system cannot simultaneously handle thousands or millions of requests when each request may include hundreds of URLs We cannot predict if a URL is working or broken Therefore there s a high chance of system errors which may break the entire process and makes it very hard to manage retries The URL we visit may have high latency slowing the overall process This approach will not scale and is not resilient enough to handle high demand How do queues work and help the system scale This is where messaging queues come into the picture A queue is a linear data structure that can process requests on a first in first out basis Queues play a huge role when we are working in distributed systems Queues enable asynchronous communication within a distributed system For example consider the scenario shown below Figure A synchronous workflow of the web scraperThe system will implement a linear scaling model if we build the portfolio import scenario we discussed before using a synchronous process This means that if URLInputLambda processes invocations at the same time the ScraperLambda will then be invoked synchronously to scrape the data one after the other We wrongly assume that all requests will take the same time and succeed But when running into an error for a single URL handling retries for that URL will be tough To resolve that we should distribute the workflow and use a message queue to handle each task separately and asynchronously It will look something like this Figure Refactoring the architecture with a messaging queueAs shown above we are using Apache Kafka as the messaging queue Each URL will be pushed into the queue as a single event from the URLInputLambda Next the ScraperLambdaget each event from the queue to be processed By bringing this architectural change we immediately gain these benefits The system is now responsive and highly scalable Once the messages are fed into the queue the URLInputLambda can complete the request processing and return a status code to the user indicating that the messages have been accepted into the system The queue can then take its own time and process the messages asynchronously This means the forward facing services can handle millions of requests without issues as the workflow is done asynchronously The system is now decoupled By bringing the messaging queue we have decoupled the system services The two Lambda functions don t scale linearly as the queue can manage the flow of requests If needed we can use more instances of the processor while keeping using minimal instances of other services The system is now resilient with improved fault tolerance We can handle errors of broken URLs and set up a Dead Letter Queue and push messages to the dead letter queue after X number of retries This ensures no data is lost and one failure does not disrupt the entire system improving resiliency What are the different queueing strategies that are available for developers Well now that we ve got a rough idea of how powerful a queue is in a distributed system it s essential to understand the different types of queues that we can use in our system Messaging QueuesWe may use these standard queues for simple and linear use cases Its responsibility is to store messages in a queue based structure and let components send and receive messages from it Task QueuesA task queue is a specialized form of message queue that explicitly handles task distribution and processing Consumers pick up tasks from the queue and execute them independently This lets us integrate proper flow control ensure our system scales non linearly and is often powered by event sourcing Publisher SubscriberThis type of queueing strategy is sometimes treated as a building block of an event driven architecture It consists of a central publisher that pushes data onto subscribers who subscribe to it through an event streaming based approach To learn more about using Pub Sub models in microservices look into this in depth article The Pub Sub strategy relies on event driven architectures where publishers publish events for subscribers to process One of the pitfalls of this approach is that it operates on a fire and forget basis meaning that if a subscriber fails to process an event that event gets lost forever However we can build a fault tolerance system around the subscriber to handle such errors When should we use queues in distributed applications This is one of our most important questions when working with a queue When should we use it We should typically use a queue to accomplish some flow control or asynchronous processing in our application while enhancing application scalability reliability and resiliency Below are some best practices we should consider when using a queue Asynchronous processingQueues let parts of our application perform operations asynchronously For example as discussed before if you were to pass URLs at a given time and users performed this operation simultaneously the system resources would be exhausted in one go as all of your time consuming requests are immediately processed However by introducing a queue we can acknowledge back to the user with an OK message while the system can take its time processing each request in an asynchronous nature without linearly scaling its resources This lets you adopt architectural patterns such as Queue Based Load Leveling Event based communicationsQueues are sometimes treated as event hubs as components can push data onto a queue and other services can subscribe to it poll for data and begin processing This lets us decouple parts of the application and enforce isolated independent processing Decoupling microservicesQueues are used in microservices to decouple different services from each other So services can communicate through queues rather than calling each service directly This ensures better scalability of each service and reduces coupling between each service thus making it easier to modify or replace individual services without affecting others Improving fault tolerance and retriesAnother reason to use a message queue is to ensure that messages are not lost By default queues can retry or store failed messages through Dead Letter Queues You can configure the Dead Letter Queue to let your system automatically push a failed message onto a special queue after X number of failed retries Delayed processingCertain queueing services like Amazon SQS support delayed processing This lets your queue send messages to its consumers by enforcing a delay of a set number of seconds This is beneficial when you want your consumers to cope up with the demand What are the common pitfalls and architectural challenges of queues But messaging queues are not always the right soltuion for our application It has its own set of pitfalls and challenges Fault Tolerance and RetriesThough we said fault tolerance is offered in queues using it correctly can often be challenging Most of the time we will have to create a separate queue that will act as a dead letter queue and we will have to configure it to work as we wish manually Idempotent ActionsAnother challenge with queues is ensuring that a message is only processed once By default most queues use at least once delivery with a potential for some messages to be handled more than once So it s essential to implement message deduplication using a deduplication ID that lets the queue prevent the message with the same deduplication ID from being pushed to a consumer over a certain period What are some queueing services that we can use Below are some popular queue services and technologies we can use RabbitMQRabbitMQ is a robust and highly configurable open source message broker that implements the Advanced Message Queuing Protocol AMQP Pros Supports various messaging patterns including point to point publish subscribe request reply and more Rich feature set with advanced routing message acknowledgment message durability and priority queues High reliability and fault tolerance with support for clustering and message replication Integrates well with multiple programming languages and platforms Cons Slightly complex setup and configuration compared to other queuing systems Apache Kafka Apache Kafka is a distributed event streaming platform designed for high throughput real time data processing and event driven architectures Pros Scalable and high throughput with support for parallel processing and partitioning Provides strong durability and fault tolerance through data replication across brokers Real time data streaming and processing capabilities Supports event replay allowing consumers to go back and reprocess past events Efficiently handles large scale data streams and has low latency characteristics Cons Slightly more complex to set up and manage compared to traditional message queues It may not be the best fit for point to point messaging or request reply patterns Amazon SQSAmazon SQS is a fully managed message queue service that provides a reliable and scalable solution for asynchronous messaging between distributed components and microservices Pros Fully managed service with high availability durability and automatic scaling Supports two types of queues Standard Queue for high throughput and FIFO Queue for ordered exactly once processing Google Pub Sub Google Pub Sub is a fully managed highly scalable messaging service that enables real time messaging and event driven architectures Pros Scales automatically based on demand and offers low latency message delivery Offers fine grained access controls for securing messages and topics Cons Limited features compared to more advanced event streaming platforms like Apache Kafka Wrapping upMessaging queues have become the industry standard for building highly scalable reliable available and resilient distributed systems Their ability to decouple components handle asynchronous processing and provide fault tolerance has made them vital to modern application architectures However it s essential to understand the challenges associated with messaging queues Proper handling of fault tolerance idempotent actions and message deduplication is crucial to avoid potential pitfalls Considering these aspects we can build systems that efficiently handle complex and demanding workloads How Amplication Fits inAdopting asynchronous communication models can improve your microservices architecture s scalability reliability and performance But building a scalable microservice architecture requires a lot of planning and boilerplate scaffolding and repetitive coding Amplication is a code generator for backend services that generates all the repetitive parts of microservices architecture including communication between services using message brokers with all the best practices and industry standards You can build the foundation of your backend services with Amplication in minutes and focus on the business value of your product	2023-08-10 08:33:05
ニュース	BBC News - Home	Halifax joins rivals in cutting mortgage rates	https://www.bbc.co.uk/news/business-66459129?at_medium=RSS&at_campaign=KARANGA	market	2023-08-10 08:47:22
ニュース	BBC News - Home	Hawaii fires: At least 36 killed as wildfires tear through Maui island	https://www.bbc.co.uk/news/world-us-canada-66460401?at_medium=RSS&at_campaign=KARANGA	hawaii	2023-08-10 08:47:14
ニュース	BBC News - Home	Candidate in Ecuador's presidential election Fernando Villavicencio shot dead	https://www.bbc.co.uk/news/world-latin-america-66457472?at_medium=RSS&at_campaign=KARANGA	quito	2023-08-10 08:00:49
ニュース	BBC News - Home	Oxford Street: Suella Braverman tells police to hunt down culprits	https://www.bbc.co.uk/news/uk-england-london-66459233?at_medium=RSS&at_campaign=KARANGA	cities	2023-08-10 08:06:53
ニュース	BBC News - Home	Last-minute summer holiday bookings rise as Brits flee rain	https://www.bbc.co.uk/news/business-66453138?at_medium=RSS&at_campaign=KARANGA	agents	2023-08-10 08:44:08
ニュース	BBC News - Home	Surrey shop accused of racism removes image of tobacco plantation	https://www.bbc.co.uk/news/uk-england-surrey-66458711?at_medium=RSS&at_campaign=KARANGA	white	2023-08-10 08:29:34
ニュース	BBC News - Home	PSNI chief constable faces questions on data breaches	https://www.bbc.co.uk/news/uk-northern-ireland-66455475?at_medium=RSS&at_campaign=KARANGA	safety	2023-08-10 08:11:39
ニュース	BBC News - Home	Football referees: Why should I be abused for 90 minutes?	https://www.bbc.co.uk/news/uk-northern-ireland-66455176?at_medium=RSS&at_campaign=KARANGA	brien	2023-08-10 08:16:42
ニュース	BBC News - Home	Strictly contestants 2023: Annabel Croft and Nigel Harman join line-up	https://www.bbc.co.uk/news/entertainment-arts-66408141?at_medium=RSS&at_campaign=KARANGA	ellie	2023-08-10 08:41:19
ニュース	BBC News - Home	World Cup 2023 build-up: France v Scotland - Jamie Ritchie in Gregor Townsend's side	https://www.bbc.co.uk/sport/rugby-union/66459832?at_medium=RSS&at_campaign=KARANGA	World Cup build up France v Scotland Jamie Ritchie in Gregor Townsend x s sideCaptain Jamie Ritchie returns in one of six changes to the Scotland team for the second of the back to back World Cup warm up games against France	2023-08-10 08:29:16
ニュース	Newsweek	女性を襲った悲劇...トイレの便器からヘビがニョロニョロ...絶体絶命の瞬間	https://www.newsweekjapan.jp/stories/world/2023/08/post-102402.php	結局、ラバーカップを何度か入れると、これ以上水が飛び散るのを避けたかったのか、便器から飛び出してきた」「彼は全くの無傷で、床の隙間から外に出ていった」メキシコのコスメル島でウマの保護施設を運営するボニーラは、自宅のトイレでヘビに遭遇したのは初めてではないと話している。	2023-08-10 17:30:00
IT	週刊アスキー	新幹線の「ワゴン販売」は消えゆく運命だった	https://weekly.ascii.jp/elem/000/004/149/4149394/	東海旅客鉄道	2023-08-10 17:25:00
IT	週刊アスキー	かっこいい！ Contieaks × 福岡ソフトバンクホークスのコラボゲーミングチェアが登場	https://weekly.ascii.jp/elem/000/004/149/4149516/	contieaks	2023-08-10 17:45:00
IT	週刊アスキー	“パープル”カラーの優雅なスイーツに心ときめく！ 「プリンセスアフタヌーンティー～Elegant Purple～」	https://weekly.ascii.jp/elem/000/004/149/4149517/	elegantpurple	2023-08-10 17:45:00
IT	週刊アスキー	Stability AI、日本語に特化した汎用言語モデル「Japanese StableLM Alpha」を発表	https://weekly.ascii.jp/elem/000/004/149/4149520/	japanese	2023-08-10 17:30:00