投稿時間:2022-05-13 01:30:49 RSSフィード2022-05-13 01:00 分まとめ(38件)

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AWS	AWS Security Blog	Build a strong identity foundation that uses your existing on-premises Active Directory	https://aws.amazon.com/blogs/security/build-a-strong-identity-foundation-that-uses-your-existing-on-premises-active-directory/	Build a strong identity foundation that uses your existing on premises Active DirectoryThis blog post outlines how to use your existing Microsoft Active Directory AD to reliably authenticate access to your Amazon Web Services AWS accounts infrastructure running on AWS and third party applications The architecture we describe is designed to be highly available and extends access to your existing AD to AWS enabling your users to use …	2022-05-12 15:50:18
AWS	AWS Security Blog	Build a strong identity foundation that uses your existing on-premises Active Directory	https://aws.amazon.com/blogs/security/build-a-strong-identity-foundation-that-uses-your-existing-on-premises-active-directory/	Build a strong identity foundation that uses your existing on premises Active DirectoryThis blog post outlines how to use your existing Microsoft Active Directory AD to reliably authenticate access to your Amazon Web Services AWS accounts infrastructure running on AWS and third party applications The architecture we describe is designed to be highly available and extends access to your existing AD to AWS enabling your users to use …	2022-05-12 15:50:18
js	JavaScriptタグが付けられた新着投稿 - Qiita	forEachについて完全に理解した()	https://qiita.com/TakehiroKATO/items/b8144523e72e3efe283d	callback	2022-05-13 00:40:11
AWS	AWSタグが付けられた新着投稿 - Qiita	Unity:S3から複数の動画を選択しストリーミング再生する方法	https://qiita.com/Teru_3/items/aa848b9cc14a87fabc28	unitys	2022-05-13 00:10:35
Docker	dockerタグが付けられた新着投稿 - Qiita	DockerでnginxとPHPの環境を構築してみた	https://qiita.com/raysuke/items/ee4d03bb8d9f584b54c8	docker	2022-05-13 00:16:57
技術ブログ	Developers.IO	valtioで状態管理しながら、React Suspenseについて理解を深める	https://dev.classmethod.jp/articles/valtio-suspense/	reactsuspen	2022-05-12 15:31:34
海外TECH	Ars Technica	Microsoft looking at ways to “validate” Xbox discs for disc-drive-free consoles	https://arstechnica.com/?p=1853903	digital	2022-05-12 15:20:14
海外TECH	Ars Technica	Plants will grow in lunar regolith, but they don’t like it	https://arstechnica.com/?p=1853731	minerals	2022-05-12 15:00:59
海外TECH	MakeUseOf	Buying a New TV? The Basic Terms You Need to Know First	https://www.makeuseof.com/basic-tv-terms-shopping/	firsttake	2022-05-12 15:46:13
海外TECH	MakeUseOf	How to Order the New Sonos Ray (and How Much It Costs)	https://www.makeuseof.com/how-to-order-sonos-ray/	entry	2022-05-12 15:30:14
海外TECH	MakeUseOf	What Is Decentralized Social Media?	https://www.makeuseof.com/what-is-decentralized-social-media/	social	2022-05-12 15:30:13
海外TECH	MakeUseOf	3 Ways Airbnb Hopes to Get People Traveling Again in 2022	https://www.makeuseof.com/ways-airbnb-get-people-traveling-again/	features	2022-05-12 15:23:51
海外TECH	MakeUseOf	How to Fix Microsoft Teams Error Code 503 on Windows 11	https://www.makeuseof.com/windows-11-microsoft-teams-error-503/	fixes	2022-05-12 15:15:13
海外TECH	DEV Community	You Can Actually Build Your Own...	https://dev.to/hr21don/you-can-actually-build-your-own-1ilf	You Can Actually Build Your Own Alternatively you can fork this random quotes machine hosted on Netlify and then the job s done Deployed Version Control Documentation License This project is under the MIT License MIT See the LICENSE for more information Contributions Contributions are always welcome Fork the repositoryImprove current program byimproving functionalityadding a new featurebug fixesPush your work and Create a Pull Request	2022-05-12 15:45:35
海外TECH	DEV Community	What resources would you recommend to anyone looking to become a better software engineer?	https://dev.to/sloan/what-resources-would-you-recommend-to-anyone-looking-to-become-a-better-software-engineer-3akc	What resources would you recommend to anyone looking to become a better software engineer This is an anonymous post sent in by a member who does not want their name disclosed Please be thoughtful with your responses as these are usually tough posts to write Email sloan dev to if you d like to leave an anonymous comment or if you want to ask your own anonymous question I feel like I ve become a little stagnant in my growth as a developer Hitting a plateau is never fun and I really need some more options to go to whenever I want to learn a new skill Do you know of any good sites or places to go so I can become a better developer	2022-05-12 15:05:11
海外TECH	DEV Community	The DEV Analytical - More analytics on your posting	https://dev.to/surajondev/the-dev-analytical-more-analytics-on-your-posting-501i	The DEV Analytical More analytics on your posting IntroductionCoding Hackathons are a great way of improving your programming skill along with that you also get opportunities to work with new and different tools I think it is an essential thing for Tech Writers and non coding technical jobs for getting their hands dirty with code It will also inspire writers to create more content on tools and experience Recently I developed a habit of participating in at least one hackathon in a month It s not hard for finding a hackathon you can find almost one hackathon every month on dev to This month I saw Appwrite X dev to hackathon which got me excited I can learn the Appwrite tool and develop a project with it Here is my submission to the hackathon The DEV Analytical Let s find out more in the next section Overview of My SubmissionThe DEV Analytical application will help you in extending the existing analytical provided by dev to for your articles These projects I always wanted to build and during this hackathon they came into existence It uses the DEV API key to fetch the required data for analytical purposes You just need to enter the key the rest will be available to you on the dashboard page Right now it provides the following dataBasicPostFollowerReactionsAdvanceViews of Last Articles Line Graph Top tag Bar graph based on views Total CommentTotal reading time for all your articlesI would love to add more analytical to the apps such asThe best time for article postingFun FactsOther Appwrite AuthenticationI have used Appwrite to create authentication You can access the analytical without authentication too Authentication will let you store the key in the appwrite database This will help you as you don t have to enter the key every time Submission Category Web Wizard Link to CodeYou can find the code below surajondev devto analytics IntroductionThe DEV Analytical application will help you in extending the existing analytical provided by dev to for your articles These projects I always wanted to build and during this hackathon they came into existence It uses the DEV API key to fetch the required data for analytical purposes You just need to enter the key the rest will be available to you on the dashboard page Right now it provides the following dataBasicPostFollowerReactionsAdvanceViews of Last Articles Line Graph Top tag Bar graph based on views Total CommentTotal reading time for all your articlesI would love to add more analytical to the apps such asThe best time for article postingFun FactsOtherTech UsedAppwrite For Authentication and Database managmentChakra UI For creating User InterfaceExpressJS For backend server to make call to DEV APIRun on… View on GitHub Additional Screenshot Landing Page Register Page Login Page Dashboard Page What I learned During this Hackathon I was able to learn more about the backend process while working with Appwrite Before starting the hackathon I was having least idea about the Appwrite tool I learned Appwrite through video tutorials and docs I find it a very useful tool for managing all your backend in one place and with very ease ConclusionThis hackathon was fun in terms of learning and development I might go on adding more features and improving the project even after the hackathon I believe it will be useful for me to get more analytical out of my data In the future I will deploy the project to other users I will keep you updated about it I hope you like the post Thanks for reading the blog post	2022-05-12 15:02:16
Apple	AppleInsider - Frontpage News	What Google announced at I/O for Android - and how it compares to iOS	https://appleinsider.com/articles/22/05/12/what-google-announced-at-io-for-android---and-how-is-compares-to-ios?utm_medium=rss	What Google announced at I O for Android and how it compares to iOSGoogle announced a host of new Android features at its I O keynote on Wednesday While many of the capabilities are something Apple users already have on iOS others would be nice to get Google I OHere are some Android features that Google announced as well as how they compare to Apple s current software capabilities Read more	2022-05-12 15:23:37
海外TECH	Engadget	Mark Zuckerberg shows off what Meta's next headset can do	https://www.engadget.com/mark-zuckerberg-meta-vr-ar-mixed-reality-headset-project-cambria-demo-154831700.html?src=rss	Mark Zuckerberg shows off what Meta x s next headset can doMeta CEO Mark Zuckerberg has provided a first proper look at the company s next mixed reality headset codenamed Project Cambria in action The quot high end headset quot is scheduled for release later this year and it will support a new augmented reality experience called The World Beyond We see Zuckerberg playing with and petting a virtual creature that s superimposed onto the real world The clip also shows a user in front of a virtual workstation before looking down at a notepad and writing on it Reports suggested that Cambria s image quality would allow users to clearly read text and that seems to be the case In addition the demo shows a virtual workout instructor who appears to be in the same space as the headset wearer The World Beyond was built with Meta s Presence Platform which is designed to help developers create mixed reality experiences Project Cambria will support full color passthrough Its onboard cameras can seemingly provide wearers with a higher fidelity view of their surroundings for mixed reality purposes than existing Quest headsets can offer The World Beyond will be available on Quest soon through App Lab though you won t be able to access the full color passthrough experience just yet The new headset itself was blurred in the clip However it s not that hard to imagine roughly what it will look like especially given the teaser Meta released last year Project Cambria or whatever it will actually be called will reportedly cost over A recent report noted that Meta employees likened Project Cambria to a quot laptop for the face quot given that it s said to have similar specs to a Chromebook It s believed Meta is planning to release a more advanced version of the Cambria headset in as well as two new Quest models over the next few years However it seems Meta is scaling back some of its metaverse ambitions On Wednesday it was reported that the company is shutting down some projects at Reality Labs the hardware and metaverse division that lost billion last year and putting others on hold Meta is said to be hiring fewer staff than usual this year to reduce costs amid slowing revenue growth Meanwhile the company this week opened its first physical store for Reality Labs products	2022-05-12 15:48:31
海外TECH	Engadget	Ocasio-Cortez, Warren blast Amazon for 'wholly inadequate' warehouse safety	https://www.engadget.com/ocasio-cortez-warren-amazon-safety-letters-152056210.html?src=rss	Ocasio Cortez Warren blast Amazon for x wholly inadequate x warehouse safetyAmazon s handling of the deadly Edwardsville Illinois warehouse collapse in December is drawing criticism from key figures in Congress Motherboardreports that Senator Elizabeth Warren and representatives Alexandria Ocasio Cortez and Cori Bush have sent a follow up letter to Amazon CEO Andy Jassy and chairman Jeff Bezos criticizing the company s quot disappointing quot response to an initial series of questions about the Illinois warehouse s safety They said OSHA s findings described a quot wholly inadequate safety culture quot that may have played a role in the deaths of six facility workers The data pointed to quot serious concerns quot about safety training at the Edwardsville location the politicians wrote While OSHA didn t fine or otherwise punish Amazon its investigation contradicted the company s statements about preparedness Staff didn t participate in emergency drills that might have protected them from the tornado and some didn t even know the location of the designated shelter area And while Amazon claimed the warehouse had an Emergency Action Plan OSHA said the company neither customized it for the area nor followed it properly The investigation and Amazon s response suggested the firm only did the quot bare minimum quot or less to protect workers according to the politicians They added that there was evidence of injuries and exploitation elsewhere and urged Amazon to honor the House Oversight Committee s request for documents as part of its own inquiry We ve asked Amazon for comment The tech giant said in its response letter that safety was its quot top priority quot and defended its practices at the Edwardsville warehouse Bezos told shareholders roughly a year ago that Amazon needed to improve its treatment of employees but his focus was on reducing repetitive strain injuries and general safety projects not disaster preparedness The retailer acknowledged some of the calls for reform by permanently allowing cellphones on site Whatever Amazon s answer to this latest letter it s likely to face considerably more scrutiny On top of the House probe Amazon is dealing with multiple lawsuits accusing the company of negligence that led to deaths and injuries at the Illinois hub There s still plenty of pressure to change and Amazon might not succeed in resisting political demands	2022-05-12 15:20:56
Cisco	Cisco Blog	Enable Cisco Meeting Server & VQ Conference Manager sales through Black Belt Academy	https://blogs.cisco.com/partner/enable-cisco-meeting-server-vq-conference-manager-sales-through-black-belt-academy	Enable Cisco Meeting Server amp VQ Conference Manager sales through Black Belt AcademyFollowing on from the success of Black Belt Stages and VQ Communications Stage content for the Black Belt Academy program is now available	2022-05-12 15:00:44
海外科学	NYT > Science	The Milky Way’s Black Hole Comes to Light	https://www.nytimes.com/2022/05/12/science/black-hole-photo.html	event	2022-05-12 15:47:30
海外科学	NYT > Science	Biden Administration Cancels Oil Drilling Sales in Alaska and Gulf of Mexico	https://www.nytimes.com/2022/05/12/climate/biden-oil-gas-lease-sales.html	Biden Administration Cancels Oil Drilling Sales in Alaska and Gulf of MexicoRepublicans link the move to rising gas prices while the administration said it was a result of conflicting legal opinions and a lack of interest among bidders	2022-05-12 15:53:19
金融	RSS FILE - 日本証券業協会	株券等貸借取引状況（週間）	https://www.jsda.or.jp/shiryoshitsu/toukei/kabu-taiw/index.html	貸借	2022-05-12 16:13:00
金融	金融庁ホームページ	IOSCOによる「株式の流通市場におけるマーケットデータの論点と考慮事項に関する報告書」について掲載しました。	https://www.fsa.go.jp/inter/ios/20220512/20220512.html	iosco	2022-05-12 17:00:00
金融	金融庁ホームページ	資金決済法に基づく払戻手続実施中の商品券の発行者等一覧を更新しました。	https://www.fsa.go.jp/policy/prepaid/index.html	資金決済法	2022-05-12 16:00:00
ニュース	BBC News - Home	Natalie McGarry: Former SNP MP found guilty of embezzling £25,000	https://www.bbc.co.uk/news/uk-scotland-glasgow-west-61421280?at_medium=RSS&at_campaign=KARANGA	groups	2022-05-12 15:45:07
ニュース	BBC News - Home	Evgeny Lebedev: Ministers withhold security advice over appointment	https://www.bbc.co.uk/news/uk-politics-61427468?at_medium=RSS&at_campaign=KARANGA	lords	2022-05-12 15:31:34
ニュース	BBC News - Home	Brexit: What is the Northern Ireland Protocol?	https://www.bbc.co.uk/news/explainers-53724381?at_medium=RSS&at_campaign=KARANGA	brexit	2022-05-12 15:12:58
ニュース	BBC News - Home	Rugby World Cup 2025: England to host women's tournament	https://www.bbc.co.uk/sport/rugby-union/61424053?at_medium=RSS&at_campaign=KARANGA	future	2022-05-12 15:47:56
北海道	北海道新聞	ポーランド経由の天然ガス停止　ロシアが制裁、ドイツ向け	https://www.hokkaido-np.co.jp/article/680117/	天然ガス	2022-05-13 00:31:00
北海道	北海道新聞	コロナ収束へ３８００億円　首脳会議、接種促進へ	https://www.hokkaido-np.co.jp/article/680116/	新型コロナウイルス	2022-05-13 00:27:00
北海道	北海道新聞	ＮＹ株、続落	https://www.hokkaido-np.co.jp/article/680103/	続落	2022-05-13 00:06:05
北海道	北海道新聞	月の土でナズナ栽培に成功　アポロで採取、発育は遅く	https://www.hokkaido-np.co.jp/article/680114/	米国	2022-05-13 00:21:00
北海道	北海道新聞	発生から２０日目、１２人の手がかりなく　知床遭難事故	https://www.hokkaido-np.co.jp/article/680112/	手がかり	2022-05-13 00:11:00
北海道	北海道新聞	国外避難民６００万人超　ウクライナで国連機関	https://www.hokkaido-np.co.jp/article/680113/	unhcr	2022-05-13 00:11:00
北海道	北海道新聞	首相、コロナ対策支援５０億ドル　アフリカへは新たに２億ドル	https://www.hokkaido-np.co.jp/article/680110/	岸田文雄	2022-05-13 00:06:00
GCP	Cloud Blog	Previewing the power of BigQuery Remote Functions for drive time optimization	https://cloud.google.com/blog/products/data-analytics/bigquery-remote-functions-enrich-data-with-the-maps-api/	Previewing the power of BigQuery Remote Functions for drive time optimizationBigQuery s Remote Functions in preview make it possible to apply custom cloud functions to your warehouse without moving data or managing compute This flexibility unlocks many use cases including data enrichment In this post we demonstrate a pattern for combining BigQuery with the Google Maps API to add drive times to datasets containing origin and destination locations This enrichment pattern is easily adapted for address geocoding or adding Google Map s place descriptions to locations After enriching location data further spatial analysis is possible such as route and drive time optimization or geographic clustering and cohort analysisThere are three steps to using BigQuery Remote Functions Create a Cloud Function in your favorite language The function will be responsible for accepting a BigQuery request and returning an appropriate response Enable a BigQuery external connection and then register your remote function following these instructions This step establishes the connection between BigQuery and your function Write a SQL query that executes your remote function Behind the scenes BigQuery and Cloud Functions do the hard work of distributing your data running your function in parallel and returning your results Developers supply functions that SQL analysts can use and scale to large datasets Drive Time Optimization ExampleMany companies from retailers to delivery services face the daunting challenge of optimizing deliveries from warehouses to customers While many databases can compute the geographic distance between a warehouse and a customer a better metric to optimize is the driving distance or drive time between the two locations In this example we have a dataset with a table containing warehouse locations and a second table containing customer locations In order to conduct analysis with drive time we need to enrich our data by calculating the drive times between warehouses and customers This information is available through the Google Maps API and can be added to BigQuery by creating and calling a remote function The following Python code demonstrates an example implementation NOTE A real implementation will include input validation error handling and performance optimizations This code is functional but simplified to highlight the distinct requirements of a BigQuery remote function code block StructValue u code u Cloud functions can use existing libraries r nimport googlemaps r n r n The entrypoint function handles accepts a BQ request r n calls the python function that returns drivetime r n and formats the results into a response for BQ r n r ndef drivetime from latlon request r n initiate a googlemaps client using r n a runtime environment variable storing a cloud secret r n api key os environ get MAPS GEOCODE API KEY r n gmaps googlemaps Client key api key r n process the BQ request r n request json request get json r n rows request json calls r n iterate through rows with two columns origin destination r n return value r n for row in rows r n return value append get drivetime row row gmaps r n format the result as BQ expects r n replies float x for x in return value r n return json json dumps replies replies r n return return json r n A standard python function to return drivetime r n Other functions such as routes and places are available r n The function could be modified to call the googlemaps API r n with multiple values r ndef get drivetime origin destination gmaps r n results gmaps distance matrix origin destination r n drivetime sec results rows elements duration value r n return json dumps drivetime sec u language u The function is deployed as a Cloud Function and then connected to BigQuery To do so enable a BigQuery external connection and then register your remote function following these instructions This step establishes the connection between BigQuery and your function The remote function is displayed in BigQuery Once deployed we can use the function in a SQL query to calculate the drive times The SQL query can be executed on demand or scheduled This example query uses the prior Python function to calculate the drive time between customers in Tennessee and a set of distribution centers across the Southeast  NOTE To run this query you will need to create a dataset and register a remote function Replace my dataset drivetime with the appropriate name of your dataset and remote function code block StructValue u code u WITH shipping AS r n tSELECT r n t CONCAT users first name users last name AS destination name r n t CONCAT lat users latitude r n t t lng users longitude AS destination r n t dc name AS origin name r n t CONCAT lat dc latitude r n t t lng dc longitude AS origin r n FROM looker private demo thelook users r n tCROSS JOIN looker private demo thelook distribution centers AS dc r n tWHERE users state Tennessee r n r nSELECT r n my dataset drivetime shipping origin shipping destination AS drivetime r n shipping destination name r n shipping origin name r nFROM shipping r nORDER BY u language u This data can be used for further analysis such as Stocking distribution centers based on the number of customers best served by each warehouse Hiring drivers based on total required drive time at each warehouse Running what if scenarios to calculate drive time saved for new potential warehouse locations Next StepsThe Google Maps API is only one example of what is possible with BigQuery remote functions Review the preview documentation to get started or learn about other examples of spatial analysis powered by BigQuery Related ArticleLeveraging BigQuery Public Boundaries datasets for geospatial analyticsHere we ll show you how to join first party data onto the BigQuery Public Boundaries Datasets for comprehensive geospatial analyticsRead Article	2022-05-12 16:00:00
GCP	Cloud Blog	Our I/O 2022 announcements: In demo form	https://cloud.google.com/blog/topics/developers-practitioners/our-io-2022-announcements-demo-form/	Our I O announcements In demo formIn the Cloud PA Keynote at I O Aparna Sinha walked through the backend for an application that connects volunteers with volunteer opportunities in their area In this blog post we ll walk through each component of that application in a bit more detail explaining the new products that Google Cloud has released the pros and cons of the architecture we chose and other nerdy technical details we didn t have time for in the talk  But first some architecture diagrams The application we discussed in the keynote helps connect volunteers with opportunities to help In the keynote we highlighted two features of the backend for this application the comment processor and the geographical volunteer to opportunity matching functionality  The text processing feature takes free form feedback from users and uses ML and data analytics tools to route the feedback to the team that can best address that feedback Here s the architecture diagram for that backend  The opportunities near me feature allows us to help users find volunteer opportunities near a given location Here s the architecture diagram for that feature  Text Feedback Processing Let s start by diving into the text processing pipeline  The text feedback processing engine runs on a Machine Learning model more specifically a text classifier task part of the Natural Language Processing area As for many machine learning scenarios the first step was to collect users feedbacks and synthetize a dataset with those feedbacks and a label to define each feedback as part of a category of feedbacks Here were used feedback billing issues and bug as possible categories By the end of this dataset creation step the dataset structure looked like user review category lt gt Too much spam Stuff that I don t care for pops up on my screen all the time feedbackIt works okay But I did not consent to subscribing at year subscription billing issueI have bought it yet it displays ERROR IN VERIFYING MY ACCOUNT bug lt gt Having this dataset ready it was imported on Vertex AI datasets for details on how to create a text dataset on Vertex AI take a look in this guide The imported dataset could be seen on Vertex AI datasets including the available feedback categories and number of samples for each category inside the dataset Click to enlageThe next step once the dataset is ready to create the text classification model was to use Google AutoML AutoML allows us to train a model with no code just a few simple steps that can be started directly from the Vertex AI dataset page  We followed AutoML s default suggestions including using the default values for how to split the dataset for training for validation and for testing AutoML did all the model training and optimization automatically and notified us by email when the training was complete When training was complete we double checked the model in the Vertex AI console to make sure everything looked good  Click to enlargeTo enable other members of our team to use this model we deployed it as a Vertex AI endpoint The endpoint exposes the model via a REST API which made it simple to use for the members of our team that aren t experts in AI ML Once it is deployed it is ready to be used by following the directions from Get online predictions from AutoML models Once we had our model we could hook up the entire pipeline Text feedback is stored in the Firebase Realtime Database To do advanced analytics on this data we wanted to move it to BigQuery Luckily Firebase provides an easy code free way to do that the Stream Collections to BigQuery extension Once we had that installed I was able to see the text feedback data in BigQuery in real time  We wanted to classify this data directly from BigQuery To do this we built out a Cloud Function to call the Vertex AIendpoint we had just created and used BigQuery s remote function feature This Vertex AI endpoint contains a deployed model we previously trained to classify user feedback using AutoML Natural Language Processing We deployed the Cloud Function and then created a remote UDF definition on BigQuery allowing us to call the Cloud Function from BigQuery without having to move the data out of BigQuery or using additional tools The results were then sent back to BigQuery where it was displayed in the query result with the feedback data categorized code block StructValue u code u def predict classification calls r n Vertex AI endpoint details r n client aiplatform gapic PredictionServiceClient client options client options r n endpoint client endpoint path r n project project location location endpoint endpoint id r n r n Call the endpoint for each r n for call in calls r n content call r n instance predict instance TextClassificationPredictionInstance r n content content r n to value r n instances instance r n parameters dict r n parameters json format ParseDict parameters dict Value r n response client predict r n endpoint endpoint instances instances parameters parameters r n u language u Once the feedback data is categorized using our ML model we can then route the feedback to the correct people We used Cloud Run Jobs for this since it is designed for background tasks like this one Here s the code for a job that reads from BigQuery and creates a github issue for each piece of feedback labeled bug report code block StructValue u code u def create issue body timestamp r n title f User Report body r n response requests post r n f GITHUB REPO issues r n json title title body f Report Text body n Timestamp timestamp labels Mobile Bug Report bug r n headers r n Authorization f token GITHUB TOKEN r n Accept application vnd github v json r n r n r n response raise for status r n r nbq bigquery client Client r ntable bq get table TABLE NAME r n r nsql f SELECT timestamp raw text r nFROM io keynote demo mobile feedback tagged feedback r nWHERE category bug report r n r nquery bq query sql r n r nfor row in query result r n issue body row get raw text r n issue timestamp row get timestamp r n create issue issue body issue timestamp u language u To handle secrets like our GitHub token we used secrets manager and then we loaded the secrets into variables with code like this  code block StructValue u code u SECRET NAME github token r nSECRET ID f projects PROJECT NUMBER secrets SECRET NAME versions r nGITHUB TOKEN secretmanager SecretManagerServiceClient access secret version name SECRET ID payload data decode u language u Hooking up to CRM or a support ticket database is similar and lets us channel any support requests or pricing issues to the customer success team We can schedule the jobs to run when we want and as often as we want using Cloud Scheduler Since we didn t want to constantly create new bugs we ve set the job creating GitHub issues to run once a day using this configuration in cron notation Opportunities Near A Location  The second feature we showed in the Cloud Keynote would allow users to see opportunities near a specific location To do this we utilized the GIS features built into Postgres so we used Cloud SQL for PostgreSQL To query the Postgres database we used a Cloud Run service that our mobile app called as needed  At a certain point we outgrew the PostgreSQL on Cloud SQL solution as it was too slow We tried limiting the number of responses we returned but that wasn t a great user experience We needed something that was able to handle a large amount of GIS data in near real time  AlloyDB excels in situations like this where you need high throughput and real time performance on large amounts of data Luckily since AlloyDB is Postgres compatible it is a drop in replacement in our Cloud Run Service we simply needed to migrate the data from Cloud SQL and change the connection string our Cloud Run Service was using  Conclusion So that s a deeper dive into one of our I O demos and the products Google Cloud launched at Google I O this year Please come visit us in adventure and check out the codelabs and technical sessions at	2022-05-12 15:30:00