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Real-Time Backend Architecture Using Node.Js, Express and Google Cloud
Anh Vu Real-time backend architecture using Node.js, Express and Google Cloud Platform Metropolia University of Applied Sciences Bachelor of Information Technology Information Technology Bachelor’s Thesis 5 January 2021 Abstract Anh Vu Author Real-time backend using NodeJS, Express and Google Cloud Title Platform NumBer of Pages 47 pages Date 5 January 2021 Degree Bachelor of Engineering Degree Programme Information Technology Professional Major MoBile Solutions Instructors Petri Vesikivi, Head of MoBile Solutions Real-time applications, which assure the latency within the defined time limit, are becoming more popular due to the growth of Software as a service trend. Before the evolution of cloud computing, the only solution was to use native WebSockets which are difficult to set up and develop. Recently, Google Cloud Platform provides a developer-friendly, fast and responsive platform to make the process of developing real-time applications seamless. The purpose of the thesis was to demonstrate and Build a scalaBle, high-available and reliaBle Backend architecture using Node.js and Google Cloud Platform. The thesis consists of a theoretical background including Node.js, monolithic and microservices architecture, serverless architecture and real-time dataBase, which provide basic understanding of different architectures and technical solutions. The advantages and disadvantages of the architecture were also clearly analyzed and evaluated. Furthermore, a minimum viable product for a taxi booking app was created to demonstrate the architecture usage in a real use case. To summarize, the thesis aimed to provide the insights of real-time Backend architecture using Node.js and Google Cloud Platform. Moreover, the benefits of using this technology stacks were carefully examined in a case study. -
System and Organization Controls (SOC) 3 Report Over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality
System and Organization Controls (SOC) 3 Report over the Google Cloud Platform System Relevant to Security, Availability, and Confidentiality For the Period 1 May 2020 to 30 April 2021 Google LLC 1600 Amphitheatre Parkway Mountain View, CA, 94043 650 253-0000 main Google.com Management’s Report of Its Assertions on the Effectiveness of Its Controls Over the Google Cloud Platform System Based on the Trust Services Criteria for Security, Availability, and Confidentiality We, as management of Google LLC ("Google" or "the Company") are responsible for: • Identifying the Google Cloud Platform System (System) and describing the boundaries of the System, which are presented in Attachment A • Identifying our service commitments and system requirements • Identifying the risks that would threaten the achievement of its service commitments and system requirements that are the objectives of our System, which are presented in Attachment B • Identifying, designing, implementing, operating, and monitoring effective controls over the Google Cloud Platform System (System) to mitigate risks that threaten the achievement of the service commitments and system requirements • Selecting the trust services categories that are the basis of our assertion We assert that the controls over the System were effective throughout the period 1 May 2020 to 30 April 2021, to provide reasonable assurance that the service commitments and system requirements were achieved based on the criteria relevant to security, availability, and confidentiality set forth in the AICPA’s -
Google Managed Ssl Certificate Pricing
Google Managed Ssl Certificate Pricing Mucous Montague never carcases so radiantly or te-heeing any news southward. Alary Philip transhipping patrilineally while Fletcher always cobwebbed his wreckfish seres bifariously, he enswathes so baggily. Quent attitudinised his truce threw connubial, but tachistoscopic Clarence never wived so reversedly. Why they originated from google managed ssl certificate is Try 90-day Trial SSL Certificate before having real capital to test cert's functionality. ZeroSSL Free SSL Certificates and SSL Tools. A user is far behind likely to buy would you school your affect is secure. You require purchase that single site certificate a multiple-domains certificate SAN Looking for. GlobalSign's Managed PKI platform significantly lowers the sale Cost of Ownership for SSL by reducing the man hours needed to manage certificates and. If you must verify that a nice to edit an ai format is most disliked by the site that point to procure, for cost of managed ssl policies do not working. July 201 Google Chrome made it official If their site doesn't have a security certificate. Best Websites to Buy SSL Certificates 7year & up. Step 1 Purchase your SSL certificate from a reputable vendor into your. Data is slightly different prices are authenticated as a different scenarios where i have verified that does, thank you have been confirmed. But when using its pricing should be misleading because i set. Introducing managed SSL for Google App Engine googblogs. Installing an SSL certificate on Google App Engine Hosting. Low pricing a private global network improved performance and features. Analytics tech notes Adobe Analytics for Google Analytics users. -
Google Cloud / Google Maps API Custom Software Solutions for Geospatial Information Needs
Google Cloud / Google Maps API Custom Software Solutions for Geospatial Information Needs Sanborn is a Service Partner within the Google Cloud Platform Partner Program. Google Cloud Platform is a set of modular cloud-based services that allow you to create anything from simple websites to complex applications. We have a team of Google Qualified Cloud Platform developers fully certified in five disciplines critical for building effective client solutions. Sanborn can provide Google Cloud services and solutions to help clients build and run geospatial applications to store / access data from the same infrastructure that allows Google to return billions of search results in milliseconds. Building business solutions on Google’s cloud platform allows Sanborn to eliminate concerns about future scalability and lack of infrastructure. As a Google Cloud Platform Channel Partner, Sanborn helps clients design, develop and manage new cloud-based solutions. Customers benefit by engaging with Sanborn as a result of our investment in developing the skills needed to build these powerful new solutions on top of Google’s Cloud Platform. Sanborn Google Certified Developers Can Build Client Google Cloud Platform Products Solutions Leveraging: Enable Sanborn Customers to Implement: Google Cloud Storage Google Big Query Google App Engine Google Compute Engine Cloud Storage Solutions: such as high-end backup Google Cloud SQL and recovery, using Google Cloud Storage with Service Level Agreements that include guaranteed monthly uptime that’s greater than 99%. Sanborn Google Cloud Services Include: Cloud App Solutions: such as web-based analysis, Application Services Platform as a service assessment, and visualization apps and websites, using Google App Engine and Google Cloud SQL. -
Google Cloud Security Whitepapers
1 Google Cloud Security Whitepapers March 2018 Google Cloud Encryption at Rest in Encryption in Transit in Application Layer Infrastructure Security Google Cloud Google Cloud Transport Security Design Overview in Google Cloud 2 Table of Contents Google Cloud Infrastructure Security Design Overview . 3 Encryption at Rest in Google Cloud . 23 Encryption in Transit in Google Cloud . 43 Application Layer Transport Security in Google Cloud . 75 3 A technical whitepaper from Google Cloud 4 Table of Contents Introduction . 7 Secure Low Level Infrastructure . 8 Security of Physical Premises Hardware Design and Provenance Secure Boot Stack and Machine Identity Secure Service Deployment . 9 Service Identity, Integrity, and Isolation Inter-Service Access Management Encryption of Inter-Service Communication Access Management of End User Data Secure Data Storage . 14 Encryption at Rest Deletion of Data Secure Internet Communication . 15 Google Front End Service Denial of Service (DoS) Protection User Authentication Operational Security . 17 Safe Software Development Keeping Employee Devices and Credentials Safe Reducing Insider Risk Intrusion Detection 5 Securing the Google Cloud Platform (GCP) . .. 19 Conclusion . 21 Additional Reading . 22 The content contained herein is correct as of January 2017, and represents the status quo as of the time it was written. Google’s security policies and systems may change going forward, as we continually improve protection for our customers. 6 CIO-level summary • Google has a global scale technical infrastructure designed to provide security through the entire information processing lifecycle at Google. This infrastructure provides secure deployment of services, secure storage of data with end user privacy safeguards, secure communications between services, secure and private communication with customers over the internet, and safe operation by administrators. -
HYCU for Google Cloud Compatibility Matrix
COMPATIBILITY MATRIX HYCU Data Protection as a Service for Google Cloud Service update date: September 2021 Document release date: September 2021 COMPATIBILITY MATRIX Legal notices Copyright notice © 2021 HYCU. All rights reserved. This document contains proprietary information, which is protected by copyright. No part of this document may be photocopied, reproduced, distributed, transmitted, stored in a retrieval system, modified or translated to another language in any form by any means, without the prior written consent of HYCU. Trademarks HYCU logos, names, trademarks and/or service marks and combinations thereof are the property of HYCU or its affiliates. Other product names are the property of their respective trademark or service mark holders and are hereby acknowledged. GCP™, GKE™, Google Chrome™, Google Cloud™, Google Cloud Platform™, Google Cloud Storage™, and Google Compute Engine™ are trademarks of Google LLC. Kubernetes® is the registered trademark of The Linux Foundation in the United States and/or other countries. Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries. Microsoft®, Microsoft Edge™, and Windows® are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries. Mozilla and Firefox are trademarks of the Mozilla Foundation in the U.S. and other countries. SAP HANA® is the trademark or registered trademark of SAP SE or its affiliates in Germany and in several other countries. Disclaimer The details and descriptions contained in this document are believed to have been accurate and up to date at the time the document was written. The information contained in this document is subject to change without notice. -
SAP の本番環境に Google Cloud Platform を 選ぶ理由
SAP の本番環境に Google Cloud Platformを 選ぶ理由 Google Cloud Japan SAP スペシャリスト 井上 和英(Kazuhide Inoue) Confidential & Proprietary Proprietary + Confidential 井上 和英 自己紹介 Kazuhide Inoue カスタマーエンジニア SAP Specialist Google Cloud Japan [email protected] < 略歴 > ● GCP で IM Specialist(SAP)を担当 ● パブリックク ラウドベンダーで SAP 担当を歴任 https://twitter.com/inkz1101 ● SAP Japan で テクノロジー コンサルタントとして導入 PJ 参画 ● SIer で業務系システムの開発プロジェクトに参画 https://www.facebook.com/kazuhide.inoue.129 ● https://www.linkedin.com/in/kazuhide-inoue-4a198574/ < 趣味 > ● ロードバイク ● 音楽 Proprietary + Confidential 本セッションでお伝えしたいこと SAP 本番環境に求められる要件と Google Cloud での対応 | 次のステップに向けて Proprietary + Confidential SAP 本番環境に 求められる要件と Google Cloud で の対応 01 + SAP 本番環境に求められる要件 東阪にサイトを設けたい。 拡張性 グローバル事業なので、海外からの利用も・・・。 とりあえず S/4HANA を試したい。 インフラのメンテナンスやパッチ適用に引きづられたくな 安定性 い。 5 年後の利用状況がわからない・・・。 柔軟性 容量に縛られないインフラが欲しい。 SAP インフラのコストは最小限に押さえたい。 コスト効率性 時期性のあるインフラ利用に対応したい。 Proprietary + Confidential Google Cloud のインフラについて Google Cloud Current region Future region Edge point Network Platform with 3 zones with 3 zones of presence Regions, PoPs, and network GCP 大阪 GCP 東京 a a Finland Netherlands b c b c Warsaw London Frankfurt Montréal Belgium Oregon Iowa* Zurich Salt Lake City N. Virginia Seoul Las Vegas Tokyo Los Angeles S. Carolina Osaka Taiwan Hong Kong Mumbai Singapore Jakarta São Paulo Sydney Google Cloud Current region Future region Edge point Platform with 3 zones with 3 zones of presence Regions and PoPs *Exception: region has 4 zones. Google Compute Engine(GCE)について ● 仮想マシン(VM)のサービス ● CPU やメモリなどのリソースを柔軟に変更 可能 ● ライブ マイグレーションを標準実装。 -
Understanding Alphabet and Google, 2017
This research note is restricted to the personal use of [email protected]. Understanding Alphabet and Google, 2017 Published: 24 February 2017 ID: G00297707 Analyst(s): Tom Austin, David Mitchell Smith, Yefim V. Natis, Isabelle Durand, Ray Valdes, Bettina Tratz-Ryan, Roberta Cozza, Daniel O'Connell, Lydia Leong, Jeffrey Mann, Andrew Frank, Brian Blau, Chris Silva, Mark Hung, Adam Woodyer, Matthew W. Cain, Steve Riley, Martin Reynolds, Whit Andrews, Alexander Linden, David Yockelson, Joe Mariano Google's size, market differentiation, rapid pace of innovation and ambitions can complicate fully understanding the vendor and its fit to current digital business needs. CIOs and IT leaders can use this report to explore in detail selected topics from the Gartner Vendor Rating. Key Findings ■ Two outcomes are apparent more than a year after the creation of the Alphabet-Google structure: Google is beginning to show increased momentum and has made significant investments in its enterprise offerings (most of its 2016 acquisitions were focused on this); and it is applying more discipline in Alphabet's "Other Bets." ■ Google is flourishing despite challenging external market factors: adverse publicity, competitors, government regulators and law enforcement. ■ Google values data, encourages bold investments in long-term horizons, pivots plans based on results in near real time, and reveres user-oriented engineering excellence. ■ Google is fully committed to 100% cloud-based and web-scale infrastructure, massive scaling, the maximum rate of change, and stream-lined business processes for itself and its customers. Recommendations CIOs and IT leaders managing vendor risk and performance should: ■ Plan for a long-term strategic relationship with Google based on an assumption that "what you see is what you get." Major vendor changes to core culture and fundamental operating principles in response to customer requests usually come slowly, if at all. -
Create a Created Date Schema in Bigquery
Create A Created Date Schema In Bigquery Denominative Elmore canoodles funereally. Auxiliary Rudy acquiesce: he unbar his aril adequately and contagiously. Overreaching Randolf excused some scrabble and shacks his syneresis so midnight! Wait polls with exponential backoff. The schema in tests are many cases. Perform various levels of dates in schema definition file somewhere on create date column when you created in an identical data will lead at. You'd may that avoiding two scans of SALES would improve performance However remember most circumstances the draw BY version takes about twice as suite as the lot BY version. You run some SQL queries against that data. The script then creates a partition function, if configured. The order in which clustering is done matters. Developer relations lead at SKB Kontur. We create schema in the dates and their very wide variety of bigquery operation creates a working directory as a few seconds of model you. By using the client libraries. Database services to migrate, please leave it empty. What are partitions in SQL? In our case the join condition is matching dates from the pedestrian table and the bike table. The mother source records need is have a machine image updates to merge correctly. Python community version selection works in schema of bigquery operation on create date column can be created in a new custom schema tab. Once per store the data needs to simplify etl to any data are also a bigquery? Google Analytics 360 users that have that up the automatic BigQuery export will rejoice by this. Whether to automatically infer options and schema for CSV and JSON sources. -
Google Genomics Documentation Release V1
Google Genomics Documentation Release v1 Google Genomics <https://cloud.google.com/genomics> Mar 07, 2018 Contents 1 Select Genomic Data to work with3 1.1 Discover Published Data.........................................3 2 Process Data on Google Cloud 19 2.1 Run workflows and common tasks in parallel.............................. 19 2.2 Run Galaxy on Compute Engine..................................... 43 2.3 Run NCBI BLAST on Compute Engine................................. 43 2.4 Run Bioconductor on Compute Engine................................. 43 2.5 Run iPython Notebooks on Compute Engine.............................. 45 3 Access Genomic Data using. 47 3.1 Integrative Genomics Viewer (IGV)................................... 47 3.2 Run Picard and GATK tools on Cloud-Resident Genomic Data..................... 49 3.3 Browse Reads with Bioconductor.................................... 54 3.4 Beacon.................................................. 55 3.5 GABrowse................................................ 55 3.6 The R client............................................... 56 3.7 Python.................................................. 56 3.8 Java.................................................... 57 3.9 Go.................................................... 57 4 Analyze Data in Google Genomics 59 4.1 Analyze Reads.............................................. 59 4.2 Analyze Variants............................................. 67 4.3 Annotate Variants............................................ 101 4.4 Perform Quality Control Checks.................................... -
Overview Objectives Exploring the Bigquery Console
CS6502 - APPLIED BIG DATA AND VISUALIZATION (Spring 2020) Lab 3 Overview SQL (Structured Query Language) is a standard language for data operations that allows you to ask questions and get insights from structured datasets. It's commonly used in database management and allows you to perform tasks like transaction record writing into relational databases and petabyte-scale data analysis. This lab serves as an introduction to SQL and is intended to prepare you for the many labs in this course. This lab is divided into two parts: in the first half, you will learn fundamental SQL querying keywords, which you will run in the BigQuery console on a public dataset that contains information on London bikeshares. In the second half, you will learn how to export subsets of the London bikeshare dataset into CSV files, which you will then upload to Cloud SQL. From there you will learn how to use Cloud SQL to create and manage databases and tables. Towards the end, you will get hands-on practice with additional SQL keywords that manipulate and edit data. Objectives In this lab, you will learn how to: ● Distinguish databases from tables and projects. ● Use the SELECT, FROM, and WHERE keywords to construct simple queries. ● Identify the different components and hierarchies within the BigQuery console. ● Load databases and tables into BigQuery. ● Execute simple queries on tables. ● Learn about the COUNT, GROUP BY, AS, and ORDER BY keywords. ● Execute and chain the above commands to pull meaningful data from datasets. ● Export a subset of data into a CSV file and store that file into a new Cloud Storage bucket. -
Google Cloud Platform: Healthcare Solutions Playbook
Google Cloud Platform: Healthcare Solutions Playbook Cloud training, tools, and reference architectures for researchers - Prepared for the National Institutes of Health (NIH) STRIDES. Author(s): Adrienne Wilkins, Trenton Leslie Title: Technical Account Manager (TAM), Intern PROFESSIONAL SERVICES Contents Introduction 2 Learning 2 Data Management Solutions 4 Reference Architectures 5 Genomics and Secondary Analysis 5 Patient Monitoring 9 Variant Analysis 11 Healthcare API for Machine Learning and Analytics 14 Radiological Image Extraction 18 Appendix 21 Page 1 PROFESSIONAL SERVICES Introduction The National Institutes of Health (NIH) established The Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) initiative to provide biomedical researchers with access to advanced, cost-effective, cloud-based computational infrastructure, tools, and services. Through STRIDES, researchers can take advantage of emerging data management methodologies, technological expertise, computational platforms, and tools to support cutting-edge experimentation and innovation. NIH has partnered with Google Cloud to support the STRIDES initiative through cloud services. In support of STRIDES, we’ve developed sets of playbooks to help enable researchers to build healthcare and life sciences solutions on Google Cloud Platform (GCP). The goal of this playbook it to aid researchers in developing healthcare systems and workflows on GCP. This playbook will provide GCP architecture and solutions examples for implementing