投稿時間:2022-02-07 13:17:42 RSSフィード2022-02-07 13:00 分まとめ(26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	サムスン、今後のGalaxyに廃棄された漁網を再利用	https://japanese.engadget.com/samsung-ocean-bound-plastic-033013358.html	galaxy	2022-02-07 03:30:13
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] セブン、「アジアングルメフェア」開催　「バターチキンカレーおむすび」など全13種	https://www.itmedia.co.jp/business/articles/2202/07/news079.html	itmedia	2022-02-07 12:45:00
IT	ITmedia 総合記事一覧	[ITmedia PC USER] ASUS、モバイルRyzenを搭載したミニデスクトップベアボーン　3画面出力もサポート	https://www.itmedia.co.jp/pcuser/articles/2202/07/news078.html	asusjapan	2022-02-07 12:14:00
TECH	Techable（テッカブル）	SBIユーザーは無料で利用可！ 2000銘柄登録できる国内株式の取引情報ツール「カブ板」	https://techable.jp/archives/172979	取引情報	2022-02-07 03:00:56
Google	Google Developer Japan Blog	Google Ads API の 2022 年のリリースと提供終了の更新版スケジュール	http://developers-jp.googleblog.com/feeds/8383755496819796678/comments/default	デベロッパーの皆さんがAdWordsAPIから移行することをサポートするために、年のGoogleAdsAPIのリリースと提供終了のスケジュールを更新したことをお知らせします。	2022-02-07 13:00:00
Ruby	Rubyタグが付けられた新着投稿 - Qiita	paizaレベルアップ問題を紐解く②　アルファベット探し (paizaランク C 相当)	https://qiita.com/yuhi_taka/items/cd690fea2c6b470074c4	自分の解答まずは自分の回答をまとめます回答の方針としては①まず行の標準出力を変数に格納するその際にordメソッドで文字コードに変換②行目と行目の間の全ての文字をeach文で出力する③もしも行目の文字が含まれていた場合countする。	2022-02-07 12:22:39
Azure	Azureタグが付けられた新着投稿 - Qiita	【Azure】 Application GatewayとAPI Managementの統合構成	https://qiita.com/hikaru_motomiya/items/36a003ad33fe8bff0691	作成できたら、利用しているプライベートIPをメモしておきます。	2022-02-07 12:43:16
Ruby	Railsタグが付けられた新着投稿 - Qiita	Rails x Reactでapiモードを使うべき理由	https://qiita.com/mario-qiita/items/0277263f1d29379d06f0	RailsxReactでapiモードを使うべき理由なぜapiモードがいいのか結論フロントエンドとバックエンドを完全に分離することができるから。	2022-02-07 12:22:16
技術ブログ	Developers.IO	AWS再入門ブログリレー2022 Terraform Registry Module (AWS VPC Terraform module) 編	https://dev.classmethod.jp/articles/re-introducation-2022-aws-terraform-registry-module/	regis	2022-02-07 03:00:53
海外TECH	DEV Community	Industrial IoT Architecture Patterns | AWS White Paper Summary	https://dev.to/awsmenacommunity/industrial-iot-architecturepatterns-aws-white-paper-summary-4b6g	Industrial IoT ArchitecturePatterns AWS White Paper SummaryToday industrial companies want to ingest store and analyze IoT data closer to the point where data is generated to enable predictive maintenance improve quality control enhance worker safety and more Industrial companies can greatly benefit from the industrial edge s ability to solve for use cases which require low latency optimized bandwidth utilization need for offline or autonomous operation and adherence to regulatory guidelines This whitepaper outlines the design considerations for industrial IoT architectures which use the industrial edge IntroductionIndustrial Edge computing involves hardware and software technologies that enable storage computing processing and networking close to the industrial devices that generates or consumes data within a factory or industrial environment While Edge computing moves compute closer to the data generation source the edge can range from device hardware to edge gateways to local nodes to cell tower nodes to local data centers This whitepaper focuses on industrial IoT use cases where edge gateways are placed in a stationary location in an industrial environment and play the role of intermediary between on premise Operational Technology OT systems and the cloud and catalog common industrial edge architecture patterns to provide prescriptive guidance to customers implementing industrial IoT systems Edge gateways fill the critical role of intermediary processing nodes and integrator between industrial assets and the Amazon Web Services AWS Cloud and is heavily influenced by edge computing imperatives In cases where OT systems are not capable of supporting authentication authorization and encryption techniques the edge gateway can act as a guardian to locally interface with these less capable systems bridging them to cloud services with strong security patterns The following section reviews edge computing imperatives Edge computing imperativesUse cases have emerged across various industries that need to combine cloud resources with local processing and storage of data under certain conditions described as edge computing imperatives Edge computing moves processing and analysis closer to endpoints where data is generated delivering real time responsiveness and reducing costs associated with transferring large amounts of information Industrial edge computing imperatives are as follows •Data volume bandwidth considerations•A need for autonomous or disconnected operation•Privacy security and data sovereignty concerns•Low latency requirements•Network cost considerationsEdge architecture influenced by edge computing imperativesIndustrial IoT deployments consist of a combination of plant and local Operational Technology OT plant local Information Technology IT and remote IT resources which may be in the public cloud or an enterprise datacenter The benefit of splitting workloads between local and remote processing is to balance the timeliness and high bandwidth of local resources with the scale and elasticity of remote resources This introduces architectural complexity around managing the different properties of local and remote resources An Edge Gateway enables you to extend cloud capabilities into industrial environments and help monitor data flows between networks with different properties where direct connectivity between all participants is not recommended Some of these differences might include network performance latency and throughput or security and administrative domain For example it is common in global deployments to use an Edge Gateway between a low latency local area network LAN and resources on the high latency wide area network WAN Another example is an Edge Gateway might mediate between security and administrative domains such as in a Perdue Enterprise Network Architecture PERA and ANSI ISA network segmentation Industrial edge deployments are heavily influenced by what AWS calls the Three Laws of distributed computing the law of physics which constrain the latency throughput and availability of network connectivity the law of economics which determine the cost effectiveness of transferring ever increasing volumes of data and the law of the land which regulates how data is handled and where it can be stored In addition to understanding the network properties that need to be mediated and how the three laws effect the deployment industrial edge architectures must account for the properties and requirements of the data flows involved In AWS experience the most important aspects to consider are the type of data flow the direction of data flow and the quality of data flow While there are many variants within these axes AWS has identified useful architecture patterns as a starting point for architectural discussions This document describes how to navigate the combinations of network properties and data flow types to get the optimal outcomes subject to the constraints of the Three Laws and provide common industrial edge architecture patterns Industrial edge design considerations Data flow typesThere are three primary types of data flows in industrial edge environments system telemetry and object data System data is information such as system state configuration and critical alerts It is relatively small less than a gigabyte even in large installations but it is critical that the data is consistent and highly available within the local environment this means that the law of physics prevents this data from residing primarily in the cloud Changes to the system data should be propagated quickly when the WAN allows it and must not be dropped if the WAN is down Most Industrial IoT systems include at least some system data flow even if the primary purpose of the system is to support other data flows However since it is unsafe to have critical control loops depend on WAN connectivity these flows are low traffic such as ANSI ISA Level and Level MES ERP System data flows typically support traffic rates up to around kb per second although actual usage is typically much lower Inbound traffic such as from the remote resource to the edge gateway may happen at any time so polling architectures is not recommended and care must be taken to coordinate with local Network Address Translation NAT and firewall policies Session protocols that originate in the local facility and create a bidirectional connection such as MQTT or AMQP are ideal for this type of data With AWS IoT Greengrass for example the MQTT spooler performs this task on system data Telemetry data is structured time series information about the performance and actions taken by local devices and is often formatted specifically to fit into existing monitoring and alarming infrastructure Because these are time series data they can grow without bounds and are often much larger than system data Individual telemetry streams are usually fairly small in the range of s to s of kilobytes per second but the sum of all the telemetry streams in a facility can be quite large Unlike system data passing telemetry data to remote resources can tolerate high latencies ranging from seconds to hours in some applications In architectures where the source is capable enough and the network segmentation allows telemetry data can be moved directly from the source to the remote resource after receiving authentication and authorization often in the form of short term credentials from the edge gateway However most telemetry sources cannot do this and some enterprise network security policies disallow it In those cases telemetry data can be routed through the edge gateway itself When doing so gateways support the higher data rates by taking advantage of lax latency requirements This allows the gateways to aggregate telemetry data to reduce the number of round trip transactions to remote resources This aggregation may include policies on data quality such as allowing data to be dropped to maintain freshness or queuing data to prevent loss at the cost of freshness With AWS IoT Greengrass for example the Streams Manager component performs this task Object data is unstructured time series data such as video feeds or analogue sensor streams The format and contents of this data is specific to the application or sensor and it is common to apply special algorithms to post process the data into a more structured metric data For example vibration data is a high resolution audio signal usually analyzed by Fourier or Wavelet analysis a computationally expensive task Video and LIDAR sensors are even more data and compute intensive These object data flows are generally hundreds of Kbs to dozens of Mbs and in plants with large numbers of sensors the aggregate data bandwidth can be terabits per second The edge gateway can t process this data and the WAN can t usually support more than a small fraction of it As a result the edge gateway s role in managing object data is as a director understanding the inventory and purpose of the sensors and using telemetry and system data to inform local processors how to manage it The edge gateway may also at times direct some useful subset of the object data through the WAN for example to provide remote debugging capabilities The processing application and data flows for object data are not generalized and few standards exist meaning custom application development is necessary Data flow directionDirectional analogy is used for data flows around the edge gateway where separate data flows into North South flows as shown in the following figure across the boundaries of different networks such as from LAN to WAN and East West flows within the local area network While an edge gateway is not necessary to manage East West flows it is often convenient to have them manage these data flows in cases where they are already in place to support north south flows When both are present it is called a North South East West gateway which places additional resource load on the edge gateway As data volume grows it is common to need multiple gateways with specialized roles increasing architectural complexity to achieve the correct performance In the early stages of cloud adoption it is common for data flows to be primarily northbound meaning that data is moving from the local plant to a remote centralized data lake for asynchronous processing Data Flow Direction Data flow qualityData flow quality has several dimensions latency ordering and loss In most situations the Three Laws force difficult tradeoffs in data flow quality The laws of physics and economics often prevent you from having the ideal latency and ordering properties and the law of the land may impact whether data loss is acceptable It is important not to confuse the abstract concept of data flow quality with protocol level concerns such as MQTT QoS AMQP QoS TCP retransmission TLS retransmission or OPC UA metric quality values It s important to define the abstract data quality needs for the use case such as data must arrive in order or data loss cannot be tolerated It s also important to understand the protocols already in place to determine how to achieve the data quality requirements within the constraints of the network protocols A key concern for data flow quality is the appropriate behavior in exceptional circumstances such as long term network disruption Because edge gateways are installed at connection points between networks it is often not cost effective or physically feasible to provide fully redundant connections The Edge Gateway architecture must ensure that system requirements are met even in the face of hours or days long disruptions Performance considerationsIndustrial IoT IIoT systems consist of a mix of general purpose IT components such as relational databases and message brokers and specialized applications which are purpose built for a particular task The performance of specialized applications is recommended rather than attempting the same task with general purpose components but assembling general purpose components is often faster and cheaper For example a purpose build packet handling pipeline written in C and running in the operating system kernel can easily move GBs on a common Intel class PC whereas a general purpose message broker applied to the same task may only be able to move MBs on the same hardware The following architecture patterns can be used as is but it is common to need to modify them to accommodate specialist components for signals processing computer vision machine learning or high data rate workloads Protocol considerationsIIoT deployments typically implement a number of communications protocols which creates complexity In general consolidating on a small number of protocols helps reduce that complexity However the security and performance differences between the LAN and the WAN may require the use of different protocols especially in cases where the WAN is the public internet For example while it is widely deployed inside controlled local area networks OPC UA and OPC DA are not safe to expose to the internet and when used in a LAN environment its recommended to use the newer version of OPC with security features enabled and implement strong perimeter security Another example synchronous communications such as MQTT in QoS or QoS modes have low performance as network latency increases One of the key roles of the edge gateway is to mediate between the protocols that are suitable for each environment For example OPC UA messages need to be proxied through secure tunnel to provide appropriate authentication and flow control Another example an edge gateway can perform application level message delivery validation for messages sent over QoS achieving high performance on high latency links while still achieving the delivery guarantees of QoS Mapping to the ISA ModelANSI ISA provides a common view of industrial IT systems which can be helpful for understanding the role of edge gateways and hybrid cloud IIoT environments Because of the latency and availability characteristics of the WAN it is not recommended to take a dependency on remote resources for Level systems Critical Level systems should also be local but additional remote monitoring may be layered on so that operations staff can observe global trends It is recommended that data delays and gaps for these remote Level systems can cause only observability failures and not production impact The ANSI ISA Pyramid Showing Expected System Response Times Level and Level systems can benefit from the properties of remote computing including the ability to aggregate data from multiple sites and the ability to perform compute intensive analytics tasks Edge gateways are generally found in layer and OI IT Gateways responsible for industrial protocol conversion are often found in layer of the Purdue model Common IIoT Edge scenarios and use cases Telemetry exportThe most common type of IIoT use case and the place where most IIoT initiatives start is with a one way transfer of telemetry data from the local site to a remote data lake where the data from multiple industrial sites is made available for analytics and monitoring workloads These workloads include a control channel that is mostly used for managing the edge gateway itself such as configuring data export and security policies This system data is real time when the WAN link is available and uses asynchronous state management through device shadows to guard against link failure Typically the telemetry data is aggregated on the edge gateway and sent northbound in batches with acknowledgement and retry to guard against data loss The following architecture shows system flow messages up to around per second and telemetry messages up to around per second with enough local storage to avoid data loss for several hours of link failure Telemetry export through edge gatewayThere are some implementation choices to make for this workload as the gateway needs to adapt to the specifics of the telemetry flows Low traffic telemetry may be sent directly through the system channel and managed by the IoT control systems though depending on WAN latency this will create performance bottlenecks around messages per second For higher throughput data flows the gateway will need to pre process the data in transit There are a variety of techniques for this Where firewall rules allow multiple northbound connections parallelizing the data flow can overcome the effects of network latency and allow high throughput Where firewall rules do not allow parallelism the gateway must aggregate telemetry into batches that will efficiently utilize the high latency northbound link AWS IoT Greengrass supports this batching through its Stream Manager component The following sections discuss industrial edge architecture variants for other IIoT use cases Variant Adding East West Telemetry RoutingVariant Critical telemetryVariant Object DataVariant Adding remote controlVariant Edge analytics MLVariant Nested GatewaysVariant Edge Gateway high availabilityVariant Edge Gateway running a soft PLC Replacing traditional PLC s Variant Modern PLC s acting as Edge GatewayVariant Cluster computing at the edgeVariant Secondary sensing use caseMore Details about industrial edge architecture variants can be found here ConclusionIndustrial customers can greatly benefit from the industrial edge s unique ability to solve for use cases which require reduced latency optimized bandwidth utilization offline or autonomous operation and adherence to regulatory or security guidelines based on the physical placement of applications and data in an explicit location such as a province or country Since industrial IoT workloads can be diverse and complex it is important to understand the use case requirements customer s industrial landscape and desired business outcomes before identifying the edge gateway architecture pattern which best fits the project Selecting the right edge architecture pattern is an important step towards building a secure high performing resilient reliable and cost effective industrial IoT solution While single edge gateway implementations for a proof of concept or pilot project can be straightforward industrial customers need to plan for implementing such a system at scale including enterprise grade security orchestration life cycle management and governance ReferenceOriginal paper	2022-02-07 03:36:23
海外TECH	DEV Community	5 tools for k8s every developer should have	https://dev.to/painhardcore/5-tools-for-k8s-every-developer-should-have-5cfn	tools for ks every developer should haveAfter working very closely with Kubernetes I created a list of tools used every day Of course you can use raw kubectl but let s be honest we like comfort and user friendly tools for the most part Lens The Kubernetes IDELens IDE for Kubernetes The only system you ll ever need to take control of your Kubernetes clusters It s all in easy to use desktop UI tool for managing your ks resources Ks ーKubernetes CLI To Manage Your Clusters In StyleKs provides a terminal UI to interact with your Kubernetes clusters The aim of this project is to make it easier to navigate observe and manage your applications in the wild Ks continually watches Kubernetes for changes and offers subsequent commands to interact with your observed resources It s something similar to Lens but built for terminal use Also my favorite one over the Lens In my workflow I split my terminal st part is ks nd part is helm apply smth Kubectx and KubensA faster way to switch between clusters and namespaces in kubectl It s something you ll need when you have multiple environments Boosts your productivity when you are constantly back and forth switching environments kube ps Kubernetes prompt for bash and zshA script that lets you add the current Kubernetes context and namespace configured on kubectl to your Bash Zsh prompt strings i e the PS For multiple environment workflow so you not mess everything up For zsh there is a simple plugin superbrothers zsh kubectl prompt which you can also use kubefwd Kube Forward kubefwd is a command line utility built to port forward multiple services within one or more namespaces on one or more Kubernetes clusters kubefwd uses the same port exposed by the service and forwards it from a loopback IP address on your local workstation kubefwd temporally adds domain entries to your etc hosts file with the service names it forwards When working on our local workstation my team and I often build applications that access services through their service names and ports within a Kubernetes namespace kubefwd allows us to develop locally with services available as they would be in the cluster P S As I mentioned before I ve used these tools for some time while working with the ks environment There are a lot of helpful tools for ks but I suggest keeping your tooling tight and minimal	2022-02-07 03:04:41
医療系	医療介護 CBnews	「適切なケアマネジメント手法」委員の動画公開-厚労省	https://www.cbnews.jp/news/entry/20220204175815	厚生労働省	2022-02-07 13:00:00
海外ニュース	Japan Times latest articles	Afghanistan’s health care system is collapsing under stress	https://www.japantimes.co.jp/news/2022/02/07/world/afghanistan-health-care/	Afghanistan s health care system is collapsing under stressThe funding necessary for Afghanistan s health system to survive has dried up due to sanctions imposed on the Taliban leading to overburdened hospitals in danger	2022-02-07 12:10:06
ニュース	BBC News - Home	GB's Dodds & Mouat beat USA to warm up for curling semi-finals	https://www.bbc.co.uk/sport/winter-olympics/60283849?at_medium=RSS&at_campaign=KARANGA	GB x s Dodds amp Mouat beat USA to warm up for curling semi finalsGreat Britain s curling mixed doubles pair beat the USA in their final group match as they warmed up for their Winter Olympics semi final against Norway	2022-02-07 03:24:27
GCP	Google Cloud Platform Japan 公式ブログ	Newsweek、Recommendations AI によって 1 回のアクセスあたりの総収益を 10% 増加	https://cloud.google.com/blog/ja/products/ai-machine-learning/how-newsweek-increased-total-revenue-with-recommendations-ai/	NewsweekとGoogleCloudが期待したのは、RecommendationsAIが提供する高度にパーソナライズされたレコメンデーションによって、読者が関心の高い記事を見つけやすくなり、表示されるおすすめ記事のクリック率CTRが大幅に向上することでした。	2022-02-07 04:00:00
GCP	Google Cloud Platform Japan 公式ブログ	Google Cloud、EU 向け Assured Workloads で欧州のデータ主権機能を強化	https://cloud.google.com/blog/ja/products/identity-security/meet-data-sovereignty-requirements-with-assured-workloads-for-eu-on-google-cloud/	データ所在地が任意のEU内のGoogleCloudのリージョン内データへのアクセスとカスタマーサポートは、EUの国籍を持ちEUに在住する担当者に限定顧客管理の暗号鍵など、データアクセスの暗号化を制御GoogleCloudConsoleを使用して、こうした管理機能を持つCloudワークロードを構成する方法を、以下で見ていきましょうEU向けAssuredWorkloadsの構成AssuredWorkloadsは、組織のフォルダレベルで機能し、データ主権の要件を満たす必要があるGoogleCloudワークロードに、特定の設定のみを選択して適用、施行できます。	2022-02-07 04:00:00
北海道	北海道新聞	旭川で凍死した中２の母を中傷　侮辱罪で略式起訴	https://www.hokkaido-np.co.jp/article/642747/	北海道旭川市	2022-02-07 12:08:00
北海道	北海道新聞	【五輪コラム】自分らしさを表現すること　「平野歩夢の独創性」	https://www.hokkaido-np.co.jp/article/642753/	平野歩夢	2022-02-07 12:01:00
IT	週刊アスキー	ミクシィ、位置精度とバッテリー容量が強化された子ども用GPSサービス「みてねみまもりGPS」第2世代モデルを販売開始	https://weekly.ascii.jp/elem/000/004/082/4082710/	vantage	2022-02-07 12:50:00
IT	週刊アスキー	セブンイレブン「アジアングルメフェア」全国でスタート「ルーロー飯」「グリーンカレー」など計13品登場	https://weekly.ascii.jp/elem/000/004/082/4082724/	登場	2022-02-07 12:50:00
IT	週刊アスキー	LINE WORKSの過去と未来、バージョン3.3の新機能が披露	https://weekly.ascii.jp/elem/000/004/082/4082666/	lineworks	2022-02-07 12:30:00
IT	週刊アスキー	ケンタ「30％オフパック」人気チキンの詰め合わせが最大650円おトク	https://weekly.ascii.jp/elem/000/004/082/4082723/	期間限定	2022-02-07 12:20:00
マーケティング	AdverTimes	ESG経営の理想と現実、9割が「なにから始めたらいいのか」	https://www.advertimes.com/20220207/article376224/	三井物産	2022-02-07 03:44:19
海外TECH	reddit	[2022 Winter Olympic Games] Team Event - Women's Free Skate Live Discussion Thread	https://www.reddit.com/r/FigureSkating/comments/sma9ha/2022_winter_olympic_games_team_event_womens_free/	Winter Olympic Games Team Event Women x s Free Skate Live Discussion ThreadDiscuss the Team Event Women s Free Skate here Monday February All times in Beijing China GMT time Team Pairs Free Skate Live Discussion Thread Team Ice Dance Free Dance Live Discussion Thread Team Women s Free Skate Time and Date Converter FS Skating Times Twitter has time zone conversion charts for the Team Event Detailed Colour Schedule ISU Page Official Beijing Olympic Website Entries Live Results Starting Order HOW TO WATCH Olympic broadcasting rights in your nation may be very different from the rest of the ISU figure skating season Make sure that you have verified how you will be able to watch the Olympics in your location before the events begin The Official Olympic Where to Watch Guide contains information on the broadcast rights for each nation in the world So You Want To Watch Figure Skating has a post providing direct links to livestreams in many nations as well as possible fan streams and unblocked restreams The Olympics YouTube Channel will livestream all events but is heavily geo restricted to only a few nations without other broadcasters Some are reporting that VPNs are not successfully bypassing the georestrictions USA viewers Livestreams available on Peacock Premium mo all events and some practice sessions will be livestreamed Canadian viewers CBC will livestream all events Russian viewers Channel One will livestream all events as will Telesport European viewers the Eurosport Player will livestream the events but is only available in certain locations depending on national broadcast rights check your local schedule to verify British Viewers BBC iPlayer will livestream the events Australian Viewers Channel will carry the livestreams Korean Viewers SBS will carry some of the events live Team Event Day Three Post Event Discussion Thread In order to keep the sub from getting too cluttered with multiple posts covering much of the same ground please use the Post Event Discussion Threads to discuss the event after it concludes Things like scoring analysis opinions speculation about the free skate next competition general cheering appreciation for skaters and video links should all go in the post discussion threads Solo posts which cover these general topics especially low effort low content posts will be removed and discussion will be redirected to the Post Discussion Thread You can also discuss the events on the events on the r FigureSkating discord more information on the server and its rules is here Winter Olympic Games Masterpost submitted by u CountyKildare to r FigureSkating link comments	2022-02-07 03:24:32
GCP	Cloud Blog JA	Newsweek、Recommendations AI によって 1 回のアクセスあたりの総収益を 10% 増加	https://cloud.google.com/blog/ja/products/ai-machine-learning/how-newsweek-increased-total-revenue-with-recommendations-ai/	NewsweekとGoogleCloudが期待したのは、RecommendationsAIが提供する高度にパーソナライズされたレコメンデーションによって、読者が関心の高い記事を見つけやすくなり、表示されるおすすめ記事のクリック率CTRが大幅に向上することでした。	2022-02-07 04:00:00
GCP	Cloud Blog JA	Google Cloud、EU 向け Assured Workloads で欧州のデータ主権機能を強化	https://cloud.google.com/blog/ja/products/identity-security/meet-data-sovereignty-requirements-with-assured-workloads-for-eu-on-google-cloud/	データ所在地が任意のEU内のGoogleCloudのリージョン内データへのアクセスとカスタマーサポートは、EUの国籍を持ちEUに在住する担当者に限定顧客管理の暗号鍵など、データアクセスの暗号化を制御GoogleCloudConsoleを使用して、こうした管理機能を持つCloudワークロードを構成する方法を、以下で見ていきましょうEU向けAssuredWorkloadsの構成AssuredWorkloadsは、組織のフォルダレベルで機能し、データ主権の要件を満たす必要があるGoogleCloudワークロードに、特定の設定のみを選択して適用、施行できます。	2022-02-07 04:00:00