投稿時間:2023-04-15 15:12:58 RSSフィード2023-04-15 15:00 分まとめ(17件)

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IT	InfoQ	Amazon VPC Lattice Now GA with New Capabilities for Service-to-Service Connectivity	https://www.infoq.com/news/2023/04/aws-vpc-lattice-ga/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global	Amazon VPC Lattice Now GA with New Capabilities for Service to Service ConnectivityAnnounced in preview at the latest re Invent conference Amazon VPC Lattice is now generally available with new capabilities for service to service connectivity security and monitoring The pricing model raised some concerns in the community By Renato Losio	2023-04-15 05:32:00
python	Pythonタグが付けられた新着投稿 - Qiita	カタカナ単語リストを使ってpythonでしりとりプログラムを作る	https://qiita.com/miumiu___co/items/cce187cfb1800fe669e7	長音	2023-04-15 14:52:19
Ruby	Rubyタグが付けられた新着投稿 - Qiita	RubyでAtCoder ABC280(A, B, C)を解いてみた	https://qiita.com/shoya15/items/21daa7efc047f3695849	atcoder	2023-04-15 14:02:10
Git	Gitタグが付けられた新着投稿 - Qiita	Git-基本的な使い方　健忘録	https://qiita.com/SEKI211/items/cf47c0500951b4bd64d5	概要	2023-04-15 14:48:11
Git	Gitタグが付けられた新着投稿 - Qiita	[Git]コマンド備忘録（一部）	https://qiita.com/momozo_trademen/items/be29f661efa1d85180ff	gtgitstatus	2023-04-15 14:12:16
技術ブログ	Developers.IO	【オフライン@福岡】俺たちのフロントエンド”大”自慢大会に参加してきたので現地の様子をご紹介します！	https://dev.classmethod.jp/articles/20230414-findy-classmethod-frontend-event/	高橋	2023-04-15 05:55:34
海外TECH	DEV Community	Blazor WebAssembly vs. Blazor Server: Which One Should You Choose?	https://dev.to/bhavin9920/blazor-webassembly-vs-blazor-server-which-one-should-you-choose-350d	Blazor WebAssembly vs Blazor Server Which One Should You Choose Blazor the open source web framework from Microsoft allows developers to build web applications using C and NET instead of JavaScript Blazor supports two deployment models WebAssembly and Server While both models share the same programming model there are significant differences between them In this post we ll explore the differences between Blazor WebAssembly and Blazor Server and help you decide which one is right for your project Blazor WebAssemblyBlazor WebAssembly allows you to run the entire application in the client s web browser When the user requests the application the application s code is downloaded to the client s machine compiled and executed inside the browser s sandbox This means that the application can run offline and the user can continue to use the app even when they re not connected to the internet Blazor ServerBlazor Server on the other hand runs the application on the server and uses SignalR to provide real time communication between the client and the server When the user requests the application the server sends the HTML CSS and JavaScript to the client The user interacts with the app and the app sends the user s input to the server for processing The server then sends the updated HTML CSS and JavaScript to the client and the process repeats Which One Should You Choose The choice between Blazor WebAssembly and Blazor Server depends on your project s requirements If your application needs to run offline or you need to take advantage of client side processing power then Blazor WebAssembly is the better option On the other hand if your application requires real time communication or you have performance concerns then Blazor Server is the way to go In this post we explored the differences between Blazor WebAssembly and Blazor Server and helped you decide which one is right for your project Remember both models share the same programming model so whichever one you choose you ll still be able to leverage the power of C and NET to build your web application	2023-04-15 05:51:55
海外TECH	DEV Community	How to Optimize Costs in AWS: Best Practices and Strategies	https://dev.to/prasadkpd/how-to-optimize-costs-in-aws-best-practices-and-strategies-1apn	How to Optimize Costs in AWS Best Practices and StrategiesAssume you re running a small online business on AWS And your monthly cloud fee is steadily increasing You re not sure what s causing the cost increase and you re worried about how much it ll cost you in the long run You understand that cost optimization is crucial to the success of your company but you re not sure where to begin In this article I ll tackle best practices and strategies for optimizing costs in AWS Using AWS Cost ExploreAWS Cost Explorer is one of the first tools you should utilize to optimize your AWS charges This tool is free for all AWS customers and gives a detailed breakdown of your AWS usage and expenses You may use Cost Explorer to discover where your costs are coming from And also uncover cost drivers including unused resources data transmission and storage charges You can also use Cost Explorer to generate custom reports to track your expenditure over time For example you could develop a report indicating how much money you re spending on a specific service or region and then utilize that information to identify cost cutting opportunities Right Sizing InstancesAnother option to reduce AWS costs is to right size your instances AWS has a variety of instance types and determining which one is best for your workload can be difficult You are squandering money on unused resources if you use an instance that is too large for your workload On the other side if you use a too small instance you will sacrifice performance and efficiency You can use a tool like AWS Trusted Advisor to right size your instances This tool recommends ways to optimize your AWS infrastructure such as detecting unused instances that can be reduced to a lower instance type Using AWS Spot InstancesAWS Spot Instances are yet another option to reduce your AWS charges Spot Instances enable you to place bids on unused EC capacity and execute workloads at a significantly lower cost Using Spot Instances instead of on demand or Reserved Instances can save you up to on your EC charges Spot instances are best suited for workloads that can withstand interruptions such as batch processing processes or non critical workloads Spot instances can be configured to automatically scale up and down based on demand and you just pay for the time your instances are running Implementing Auto ScalingAnother option to reduce AWS expenses is to use auto scaling which automatically adjusts your resources based on demand You can use auto scaling to ensure that you have enough capacity to handle your workload without over provisioning This can assist you in avoiding unused capacity and costs To enable auto scaling you must first create policies that define when and how your resources should scale You could for example create a policy that adds extra instances when CPU consumption hits a particular threshold and removes instances when CPU usage falls below a specific level Using AWS Reserved InstancesFinally if you have consistent consumption patterns AWS Reserved Instances might be a cost effective option to execute your applications Reserved Instances allow you to pay for an instance once and obtain a big reduction off the hourly pricing When compared to On Demand Instances this can save you up to on instance fees Reserved Instances are best suited for workloads with a predictable usage pattern such as a database or web application Reserved Instances can be purchased for a specified instance type operating system and region and then used for a set period of time ConclusionOptimizing your AWS costs is crucial to your company s success You can keep your AWS prices under control and ensure that you re getting the most value from your cloud infrastructure by using tools like Cost Explorer right sizing your instances leveraging Spot Instances adopting auto scaling and using Reserved Instances So don t put it off any longer start minimizing your AWS costs today and reap the many benefits that AWS has to offer Remember that a penny saved is a penny earned and by reducing your AWS expenditures you re not only saving money but also freeing up resources to spend on new products features and growth prospects for your company You can ensure that your AWS expenditures are constantly under control with the correct cost optimization measures in place allowing you to focus on what really counts expanding your business and serving your customers	2023-04-15 05:47:32
海外TECH	DEV Community	AWS for Data Engineering Projects	https://dev.to/imsampro/aws-for-data-engineering-projects-c6a	AWS for Data Engineering ProjectsIn the era of big data organizations are constantly seeking new ways to manage and analyze massive amounts of information This has led to an increasing demand for professionals with data engineering skills who can build and maintain data processing systems that can handle large volumes of information Amazon Web Services AWS is a cloud computing platform that offers a variety of data engineering services and tools to help organizations build and manage their data infrastructure In this article we will explore the best practices for AWS data engineering projects the services and tools available for data processing and analysis and the strategies for optimizing cost and performance Additionally we will examine successful case studies that demonstrate how AWS can be leveraged for data engineering projects Introduction to AWS Data Engineering ProjectsAWS Data Engineering projects involve designing building and maintaining complex data processing systems that handle massive amounts of data With the growing need for businesses to manage large scale data sets AWS provides an extensive range of services and tools to help data architects and engineers develop secure reliable and scalable architectures What is AWS Data Engineering AWS Data Engineering involves the development of data integration processing and analysis systems that leverage AWS cloud services It includes a range of activities such as data ingestion transformation storage and analysis One of the main objectives of AWS Data Engineering is to build reliable and scalable data architectures that can efficiently process and manage growing data volumes Why Use AWS for Data Engineering Projects AWS provides a broad set of services and tools that can streamline data engineering projects making it more efficient and cost effective AWS is known for its scalability reliability and security making it an ideal platform for processing and managing data Additionally by leveraging AWS services developers can reduce infrastructure costs focusing more on solving business problems involving data Best Practices for AWS Data Engineering ProjectsDesigning Scalable and Resilient InfrastructureTo design scalable infrastructure it is essential to create a flexible and modular architecture One way to achieve this is by using services that allow automatic scaling such as Amazon EC Auto Scaling or AWS Lambda Building a resilient infrastructure requires implementing strategies to minimize downtime and ensure data integrity This can be achieved by using data replication backup and disaster recovery tools on AWS Ensuring Data Quality and ConsistencyData quality and consistency are crucial for data engineering projects Poor data quality can lead to incorrect business decisions and lost opportunities To ensure data quality it is essential to have robust data validation and cleansing processes in place AWS services such as AWS Glue and AWS Data Pipeline can help with this Implementing Efficient Data Processing and StorageEfficient data processing and storage are critical in managing large scale data sets AWS services such as Amazon S and Amazon Redshift can provide elastic and scalable storage solutions while tools such as AWS Kinesis and AWS EMR can offer efficient data processing capabilities AWS Data Engineering Services and ToolsAWS Data Services OverviewAWS provides a range of data services that enable businesses to build scalable and highly available architectures These services include Amazon S Amazon Redshift Amazon RDS Amazon DynamoDB and Amazon Aurora AWS Analytics and Visualization ToolsAWS Analytics and Visualization tools enable businesses to turn data into actionable insights These tools include Amazon QuickSight Amazon Elasticsearch and AWS Glue AWS Data Migration ServicesAWS Data Migration services enable businesses to move and manage data between different data stores These services include AWS Database Migration Service AWS Schema Conversion Tool and AWS Snowball Data Analytics and Visualization with AWSUsing Amazon Redshift for AnalyticsAmazon Redshift is a popular data warehouse service that enables businesses to analyze data at scale Redshift can handle massive amounts of data and provide fast query performance making it an ideal choice for businesses that require real time data analytics Visualizing Data with Amazon QuickSightAmazon QuickSight is an AWS service that enables businesses to create interactive dashboards and visualizations from multiple data sources It provides an easy to use interface that enables businesses to quickly gain insights from their data Real time Analytics with AWS LambdaAWS Lambda is a serverless compute service that enables businesses to run code in response to specific events such as data modifications This can be useful in building real time analytics pipelines that allow businesses to get insights from their data as it is generated Building Data Pipelines on AWSData engineering is a crucial part of any data driven organization AWS offers a suite of powerful services for designing and building data pipelines that can collect transform and store data from various sources In this section we will discuss some of the ways AWS can help you build robust data pipelines Designing Data Pipelines with AWS GlueAWS Glue is a fully managed extract transform and load ETL service that makes it easy to design scalable and secure data processing workflows Glue provides a flexible and easy to use console that allows you to create and run your ETL jobs with no infrastructure to manage Building ETL Pipelines with AWS Step FunctionsAWS Step Functions is a serverless workflow service that can help you build ETL pipelines with little to no coding With Step Functions you can define the steps of your workflow create a visual representation of the workflow and monitor the progress of your data pipeline Automating Data Pipelines with AWS Data PipelineAWS Data Pipeline is a fully managed service for moving data between different AWS services or on premises data sources It allows you to automate your data processing workflows monitor them for errors and automatically retry failed tasks Security and Compliance Considerations for AWS Data Engineering ProjectsWhen working with sensitive data it s essential to ensure that you re following best practices for security and compliance In this section we ll discuss how you can achieve security and compliance with AWS services AWS Security Best PracticesAWS provides a wide range of security services and features that help you protect your data and infrastructure These include identity and access management encryption and network security By following AWS security best practices you can ensure that your data is protected at all times Protecting Sensitive Data on AWSIf you re working with sensitive data AWS offers solutions for encrypting data at rest and in transit You can also use Amazon S bucket policies to restrict access to data to specific AWS accounts or IP addresses Achieving Compliance with AWS ServicesAWS offers compliance programs such as HIPAA PCI DSS and SOC which can help you achieve regulatory compliance By using AWS services that are compliant with these standards you can ensure that your data engineering projects are compliant as well Optimizing Cost and Performance in AWS Data EngineeringAWS offers a variety of tools and services that help you optimize the cost and performance of your data engineering projects In this section we ll discuss some of these tools Using AWS Cost Optimization ToolsAWS provides a suite of tools for optimizing costs such as AWS Cost Explorer and AWS Budgets By using these tools you can monitor your AWS usage and identify cost saving opportunities Scaling Resources for Optimal PerformanceAWS makes it easy to scale your resources up or down as needed You can use AWS Auto Scaling to automatically adjust the number of resources based on demand or set up alarms to trigger scaling manually Monitoring and Troubleshooting Data Engineering WorkloadsAWS provides a range of tools for monitoring and troubleshooting your data engineering workloads You can use AWS CloudWatch to monitor your resources and set up alarms to notify you of any issues AWS X Ray can help you troubleshoot issues with your applications or services Case Studies Successful AWS Data Engineering Projects ExamplesIn this section we ll discuss some examples of successful AWS data engineering projects and how they were implemented Case Study Building a Data Lake on AWSA company wanted to build a data lake to store and process large amounts of data They used AWS S for storage AWS Glue and AWS Step Functions for data processing and Amazon Redshift for data warehousing With this solution the company was able to store and process data more efficiently and make better data driven decisions Case Study Automating ETL Workflows with AWSA company had a manual process for extracting data from various sources and loading it into their data warehouse They used AWS Glue and AWS Data Pipeline to automate this process With this solution the company was able to reduce the time and effort required to perform ETL tasks and improve data quality Case Study Processing and Analyzing Streaming Data on AWSA company needed to process and analyze large volumes of streaming data in real time They used AWS Kinesis for data ingestion AWS Lambda for data processing and Amazon S for data storage With this solution the company was able to process and analyze data more efficiently and gain real time insights into their business AWS provides organizations with a powerful and flexible platform for data engineering projects With the right tools and strategies businesses can effectively manage and analyze large amounts of data in real time By implementing best practices for AWS data engineering organizations can build resilient and scalable data processing systems that meet their needs With AWS organizations have the ability to transform their data into a valuable resource for driving business growth and success FAQsWhat is AWS Data Engineering AWS Data Engineering involves building and managing data processing systems on the AWS cloud platform It involves designing and implementing solutions for large scale data ingestion storage processing and analysis What are some AWS data engineering services and tools AWS offers a variety of tools and services for data engineering including Amazon S AWS Glue AWS Lambda Amazon Kinesis Amazon Redshift Amazon EMR and more What are some best practices for AWS data engineering projects Some best practices for AWS data engineering projects include designing scalable and resilient infrastructure ensuring data quality and consistency implementing efficient data processing and storage and optimizing cost and performance How can organizations achieve compliance with AWS services AWS provides a range of compliance programs and services including HIPAA PCI DSS SOC and more Organizations can leverage these services to ensure that their data processing and storage systems comply with industry standards and regulations Thank you for reading Soumyadeep Mandal imsampro	2023-04-15 05:05:03
海外ニュース	Japan Times latest articles	Kishida evacuated safely after explosion at election event in western Japan	https://www.japantimes.co.jp/news/2023/04/15/national/politics-diplomacy/fumio-kishida-explosion-speech/	Kishida evacuated safely after explosion at election event in western JapanVideo footage showed people at a port in Wakayama running for shelter at around a m while a man was subdued first by what appeared	2023-04-15 14:38:53
海外ニュース	Japan Times latest articles	U.S., Japan and South Korea look to regularize missile defense exercises to deter North Korea	https://www.japantimes.co.jp/news/2023/04/15/national/us-japan-south-korea/	U S Japan and South Korea look to regularize missile defense exercises to deter North KoreaRepresentatives from the three countries met Friday for talks in Washington where they discussed the security environment on the Korean Peninsula and in the region	2023-04-15 14:39:04
海外ニュース	Japan Times latest articles	G7 leaders set to meet A-bomb survivors during summit	https://www.japantimes.co.jp/news/2023/04/15/national/politics-diplomacy/g7-leaders-meet-atomic-bomb-survivors/	memorial	2023-04-15 14:05:51
ニュース	BBC News - Home	Stakeknife: Who was Army's IRA spy Freddie Scappaticci?	https://www.bbc.co.uk/news/uk-northern-ireland-65264407?at_medium=RSS&at_campaign=KARANGA	agents	2023-04-15 05:42:02
ニュース	BBC News - Home	Snooker World Championship: Shaun Murphy says 'snooker is in best state it has ever been in'	https://www.bbc.co.uk/sport/snooker/65282129?at_medium=RSS&at_campaign=KARANGA	Snooker World Championship Shaun Murphy says x snooker is in best state it has ever been in x Shaun Murphy says snooker is in the best state it has ever been in with the World Championship set to start on Saturday in Sheffield	2023-04-15 05:32:04
ニュース	BBC News - Home	'I've been called murderer' - How Hillsborough tragedy chanting impacts fans	https://www.bbc.co.uk/sport/av/football/64878321?at_medium=RSS&at_campaign=KARANGA	chants	2023-04-15 05:07:31
IT	週刊アスキー	吉野家に「焼き鳥丼」が登場するよ！ にんにく醤油で食べる前からそそられる～	https://weekly.ascii.jp/elem/000/004/133/4133062/	焼き鳥	2023-04-15 14:30:00
ニュース	THE BRIDGE	イーロン・マスク氏、OpenAI対抗のAI企業を静かにスタートーーその名は「X.AI」。	https://thebridge.jp/2023/04/elon-musk-quietly-starts-x-ai-a-new-artificial-intelligence-company-to-challenge-openai	イーロン・マスク氏、OpenAI対抗のAI企業を静かにスタートーその名は「XAI」。	2023-04-15 05:21:19