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Ismael Romero

Учасник із 2023

Срібна ліга

Кількість балів: 11730
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned січ. 29, 2024 EST
Developing Containerized Applications on Google Cloud Earned січ. 24, 2024 EST
App Deployment, Debugging, and Performance Earned січ. 18, 2024 EST
Securing and Integrating Components of your Application Earned січ. 16, 2024 EST
Getting Started With Application Development Earned січ. 4, 2024 EST
Build Batch Data Pipelines on Google Cloud Earned жовт. 3, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned вер. 7, 2023 EDT
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська Earned серп. 16, 2023 EDT
Create and Manage Cloud Resources Earned серп. 10, 2023 EDT

This course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle. You learn about service identities, how to control access to services, and how to develop and test your application locally before deploying it to Cloud Run. The course also teaches you how to integrate with other services on Google Cloud so you can build full-featured applications.

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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to develop more secure applications, implement federated identity management, and integrate application components by using messaging, event-driven processing, and API gateways. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer. This is the second course of the Developing Applications with Google Cloud series. After completing this course, enroll in the App Deployment, Debugging, and Performance course.

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to apply best practices for application development and use the appropriate Google Cloud storage services for object storage, relational data, caching, and analytics. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer. This is the first course of the Developing Applications with Google Cloud series. After completing this course, enroll in the Securing and Integrating Components of your Application course.

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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.

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Пройдіть квест Create and Manage Cloud Resources й отримайте skill badge. Ви навчитеся виконувати наведені нижче дії. Писати команди gcloud і використовувати Cloud Shell, створювати й розгортати віртуальні машини в Compute Engine, запускати контейнерні додатки за допомогою Google Kubernetes Engine, а також налаштовувати розподілювачі навантаження для мережі й HTTP.Skill badge – це ексклюзивна цифрова винагорода, яка підтверджує, що ви вмієте працювати з продуктами й сервісами Google Cloud, а також застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати skill badge й показати його колегам, пройдіть цей квест і підсумковий тест.

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