{"id":8581,"date":"2022-01-25T18:29:27","date_gmt":"2022-01-25T11:29:27","guid":{"rendered":"https:\/\/gcloudvn.com\/?p=8581"},"modified":"2023-09-13T16:36:08","modified_gmt":"2023-09-13T09:36:08","slug":"cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud","status":"publish","type":"post","link":"https:\/\/gcloudvn.com\/en\/kienthuc\/cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud\/","title":{"rendered":"How to migrate data warehouse on premises to BigQuery on Google Cloud"},"content":{"rendered":"<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Companies&#039; Data teams face ongoing challenges in consolidating, processing, and making data useful. They deal with challenges such as a mix of ETL jobs, on-premises data warehouses with long ETL capacity limits, and growing demand from users. They also need to ensure that the downstream requirements of the ML, reporting and analysis are met with the data processing. And they need to plan for the future \u2013 how will more data be handled and how will new downstream groups be supported?<\/span><\/p>\n<p><strong>&gt; Reference:<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/phan-tich-khoi-du-lieu-lon-voi-bigquery-va-google-sheets\/\">Analyze Big Data with BigQuery and Google Sheets<\/a><\/li>\n<li><a href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/introducing-datastream-for-bigquery\/\">Introducing Datastream for Google BigQuery<\/a><\/li>\n<li><a href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/toi-uu-bigquery-voi-nguon-du-lieu-trong-google-cloud-vmware-engine\/\">Optimizing BigQuery with data sources in Google Cloud VMware Engine<\/a><\/li>\n<\/ul>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_80 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud\/#Tai_sao_su_dung_BigQuery\" >Why use BigQuery?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud\/#Chien_luoc_di_chuyen_kho_du_lieu\" >Data warehouse migration strategy<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud\/#Di_chuyen_kho_du_lieu_Nhung_dieu_can_xem_xet\" >Data Warehouse Migration: Things to Consider<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/cach-di-chuyen-kho-du-lieu-on-premises-sang-bigquery-tren-google-cloud\/#Cac_vi_du_ve_kien_truc_di_chuyen_kho_du_lieu\" >Data warehouse migration architecture examples<\/a><\/li><\/ul><\/nav><\/div>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Tai_sao_su_dung_BigQuery\"><\/span><strong>Why use BigQuery?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">On premises data warehouses become difficult to scale so the biggest goal for most companies is to create a future system for secure, scalable and efficient data storage. cost. GCP&#039;s BigQuery is serverless, highly scalable, and cost-effective, and is a great fit for an EDW use case. It&#039;s a multi-cloud data warehouse designed for business agility. However, migrating a large, highly integrated data warehouse from an on-premise data warehouse to <\/span><a href=\"https:\/\/gcloudvn.com\/en\/bigquery\/\"><span style=\"font-weight: 400;\">BigQuery<\/span><\/a><span style=\"font-weight: 400;\"> not a simple conversion. You need to ensure that your downstream system doesn&#039;t crash as a result of inconsistent data set migrations, both during and after the migration. So you have to plan your move.\u00a0<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Chien_luoc_di_chuyen_kho_du_lieu\"><\/span><strong>Data warehouse migration strategy<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The following steps are typical for a successful migration:\u00a0<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Evaluate and plan:<\/b><span style=\"font-weight: 400;\"> Pre-scoping to plan legacy data warehouse migrations\u00a0<\/span>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Define data sets, patterns, and application accessibility\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Use tools and utilities to identify unknown levels of complexity and dependencies<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Identify required application conversions and test<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Determine initial processing and storage capacity for budget forecasting and capacity planning\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Consider growth and anticipated changes during the migration period<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Formulate future state strategy and vision to guide design<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Migration:<\/b><span style=\"font-weight: 400;\"> Setting up the platform <a href=\"https:\/\/gcloudvn.com\/en\/google-cloud-platform\/\">GCP<\/a> and start moving<\/span>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">The cloud is being established, consider running centralized POCs to validate processes and data migration<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Look for automated utilities to help with any forced code migrations<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Plan to maintain data synchronization between the legacy EDW and the target for the duration of the migration. This becomes an important business process to keep the project on schedule.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Plans to integrate several enterprise tools to help existing teams scale both environments<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Review current data access patterns among communities of EDW users and how they map to similar controls available in Big Query.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Main scope includes code integration and data model transformation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Expect to refine capacity forecasts and refine attribution designs. In Big Query, there are many options for balancing cost and performance to maximize business value. For example, you can use on-demand or price <\/span><span style=\"font-weight: 400;\">permanent<\/span><span style=\"font-weight: 400;\"> or a combination of both.\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul style=\"text-align: justify;\">\n<li aria-level=\"1\"><b>Validate and check<\/b><\/li>\n<\/ul>\n<ul style=\"text-align: justify;\">\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Look for tools to enable intelligent, automated data validation\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Scope must include schema and data validation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Ideally, solutions would allow for continuous validation from source to target system during migration<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Test complexity and duration will be driven by the number and complexity of applications using data from EDW and the rate of change of those applications\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The key to a successful migration is finding Google Cloud partners who have experience migrating EDW workloads. For example, our Google Cloud partner <\/span><span style=\"font-weight: 400;\">Datametica <\/span><span style=\"font-weight: 400;\">provide services and <\/span><span style=\"font-weight: 400;\">Specialized Movement Accelerator<\/span><span style=\"font-weight: 400;\"> for each of these migration phases to help plan and execute the migration more efficiently<\/span><\/p>\n<figure id=\"attachment_8583\" aria-describedby=\"caption-attachment-8583\" style=\"width: 600px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8583\" src=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-300x169.png\" alt=\"How to migrate data warehouse on premises to BigQuery on Google Cloud\" width=\"600\" height=\"338\" srcset=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-300x169.png 300w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-1024x576.png 1024w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-768x432.png 768w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-1536x864.png 1536w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1-18x10.png 18w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Strategy.max-2000x2000-1.png 2000w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><figcaption id=\"caption-attachment-8583\" class=\"wp-caption-text\">How to migrate data warehouse on premises to BigQuery on Google Cloud<\/figcaption><\/figure>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Di_chuyen_kho_du_lieu_Nhung_dieu_can_xem_xet\"><\/span><strong>Data Warehouse Migration: Things to Consider<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Financial benefits of open source<\/b><span style=\"font-weight: 400;\">: Target moves to &#039;Open Source&#039; where no services have license fees. For example: <\/span><b>BigQuery<\/b><span style=\"font-weight: 400;\"> use standard SQL; <\/span><span style=\"font-weight: 400;\">Cloud Composer <\/span><span style=\"font-weight: 400;\">managed by Apache Airflow, <\/span><span style=\"font-weight: 400;\">. <\/span><span style=\"font-weight: 400;\">based on Apache Beam. Considering this as <\/span><b><i>managed services<\/i><\/b><span style=\"font-weight: 400;\"> provides the financial benefits of open source, but avoids the burden of maintaining open source platforms internally.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Serverless<\/b><span style=\"font-weight: 400;\">: Migrate to \u201cserverless\u201d big data services. The majority of services used in the proposed GCP data architecture scale on demand allowing for more cost-effective aligning with demand. Using fully managed services allows you to focus your engineering time on business process priorities, not building and maintaining infrastructure.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Efficiency of a unified platform<\/b><span style=\"font-weight: 400;\">: Any data warehouse migration involves integration with services around the EDW for data ingest and pre-processing and advanced analysis on the data stored in the EDW to maximize business value. A cloud provider like GCP offers a full range of &#039;big data&#039; services integrated and managed with machine learning integration. This can significantly reduce long-term TCO by increasing both operational efficiency and cost when compared to EDW specific point solutions.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Establish a solid cloud foundation<\/b><span style=\"font-weight: 400;\">: From the beginning, take the time to design a secure platform that will serve the business and technical needs of the next workload. Key features include: Scalable Resource Hierarchy, Multi-layered Security, multi-tier networking and data center strategy, and automation using Infrastructure as code. Also allows time to integrate cloud-based services into existing enterprise systems such as CI\/CD pipelines, monitoring, alerting, logging, process scheduling, and service request management service.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Unlimited capacity expansion<\/b><span style=\"font-weight: 400;\">: Moving to the cloud sounds like a big step, but really think of it as adding more data centers to your teams. Of course, these data centers offer many new services that are difficult to develop in-house and offer virtually unlimited scalability with minimal upfront financial commitment. .\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Patient and temporary foundation<\/b><span style=\"font-weight: 400;\">: Migrating EDW is usually a long running project. Willing to design and operate transient platforms for data synchronization, validation, and application testing. Consider the impact on the up and down system. It makes sense to migrate and modernize these systems at the same time as the EDW migration as they can be both sources of data and sinks and may be facing similar growth challenges. Also available to meet new business requirements that develop during migration. Take advantage of the long window of time your existing operations teams learn new services from a partner leading the rollout so your teams are ready to take over after the move.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Experienced Partner<\/b><span style=\"font-weight: 400;\">: Migrating EDW can be a huge undertaking with its challenges and risks during migration, but presents a tremendous opportunity to reduce costs, simplify operations, and provide significantly improved capacity. for internal and external EDW users. Choice <\/span><span style=\"font-weight: 400;\">suitable partner<\/span><span style=\"font-weight: 400;\"> helps reduce technical and financial risks, and allows you to plan and can start taking advantage of these long-term benefits early in the migration process.<\/span><\/li>\n<\/ul>\n<figure id=\"attachment_8582\" aria-describedby=\"caption-attachment-8582\" style=\"width: 600px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-8582\" src=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-300x169.png\" alt=\"What to keep in mind when moving a data warehouse?\" width=\"600\" height=\"338\" srcset=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-300x169.png 300w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-1024x576.png 1024w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-768x432.png 768w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-1536x864.png 1536w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1-18x10.png 18w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2022\/01\/DW_Migration_Architecture.max-2000x2000-1.png 2000w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><figcaption id=\"caption-attachment-8582\" class=\"wp-caption-text\">What to keep in mind when moving a data warehouse?<\/figcaption><\/figure>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Cac_vi_du_ve_kien_truc_di_chuyen_kho_du_lieu\"><\/span><strong>Data warehouse migration architecture examples<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Set of background elements. In GCP includes, IAM for authorization and access, cloud <\/span><span style=\"font-weight: 400;\">resource hierarchy<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">payment<\/span><span style=\"font-weight: 400;\">, networking, code pipelines, Infrastructure as code to use <\/span><span style=\"font-weight: 400;\">Cloud Build <\/span><span style=\"font-weight: 400;\">with Terraform ( <\/span><span style=\"font-weight: 400;\">GCP Foundation Toolkit<\/span><span style=\"font-weight: 400;\">), Cloud DNS and a Partner Dedicated Link to connect to existing data centers.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Enable security scanning and monitoring services before real user data is loaded with <\/span><span style=\"font-weight: 400;\">Cloud Operations<\/span><span style=\"font-weight: 400;\"> \u00a0for monitoring and logging and <\/span><span style=\"font-weight: 400;\">Security Command Center\u00a0<\/span><span style=\"font-weight: 400;\">for security monitoring.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Extract files from legacy EDW on premise and transfer to Cloud Storage and set up ongoing sync using <\/span><span style=\"font-weight: 400;\">BigQuery Transfer Services<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">From Cloud Storage, process data in Dataflow and Load\/export data to BigQuery.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Validate exports with Datametica&#039;s validation utilities running in a cluster <a href=\"https:\/\/gcloudvn.com\/en\/google-kubernetes-engine-gke\/\">GKE<\/a> and Cloud SQL to check and synchronize historical data as needed. Application teams check validated data sets during migration.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Streamline the entire process using Cloud Composer, integrated with on-premises scheduling services as needed to leverage established processes and keep old and new systems in sync.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Maintain close coordination with teams\/services that ingest new data into EDW and downstream analytics teams that rely on EDW data for ongoing advanced analytics.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Set up granular access controls for data sets and start making data available in BigQuery to existing application usage, visualization, and reporting tools using the BigQuery data connector for users to access and test &#039;down-stream&#039;.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ascending <\/span><span style=\"font-weight: 400;\">Big Query&#039;s fixed rate processing capabilities <\/span><span style=\"font-weight: 400;\">to provide the most cost-effective use of resources during migration.\u00a0<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Learn more about migrating from on premises Enterprise Data Warehouse (EDW) to Bigquery and GCP here: <a href=\"https:\/\/cloud.google.com\/architecture\/dw2bq\/dw-bq-migration-overview\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/cloud.google.com\/architecture\/dw2bq\/dw-bq-migration-overview<\/a><\/span><\/p>\n<p style=\"text-align: right;\"><strong>Source: <a href=\"https:\/\/gcloudvn.com\/en\/\">gcloudvn.com<\/a><\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>Companies&#039; Data teams face ongoing challenges in consolidating, processing, and making data useful. They deal with challenges such as mixed\u2026<\/p>","protected":false},"author":2,"featured_media":8583,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1,135],"tags":[],"class_list":["post-8581","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kienthuc","category-google-cloud-platform","entry","has-media"],"_links":{"self":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/8581","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/comments?post=8581"}],"version-history":[{"count":0,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/8581\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media\/8583"}],"wp:attachment":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media?parent=8581"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/categories?post=8581"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/tags?post=8581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}