Logging and Monitoring in Google Cloud
Earned Feb 28, 2022 EST
可靠的 Google Cloud 基础设施: 设计和流程
Earned Feb 26, 2022 EST
Developing a Google SRE Culture
Earned Feb 23, 2022 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Feb 9, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Feb 8, 2022 EST
在 Google Cloud 上设置应用开发环境
Earned Feb 7, 2022 EST
Google Cloud 基础知识：核心基础设施
Earned Feb 6, 2022 EST
为 Compute Engine 实现云负载均衡
Earned Feb 5, 2022 EST
Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
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本课程指导学员运用久经考验的设计模式在 Google Cloud 上构建高度可靠且高效的解决方案。它是“Google Compute Engine 架构设计”或“Google Kubernetes Engine 架构设计”课程的延续，并假定您有使用其中任何一门课程所涵盖技术的实践经验。通过一系列演示、设计活动和动手实验，学员可以了解如何定义及平衡业务要求和技术要求，以便设计可靠性和可用性高、安全且经济实惠的 Google Cloud 部署。
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据，展示以下技能： 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Dataproc 中创建集群和运行 Apache Spark 作业，以及调用机器学习 API，包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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完成“在 Google Cloud 上设置应用开发环境”课程，赢取技能徽章；通过该课程，您将了解如何使用以下技术的基本功能来构建和连接以存储为中心的云基础设施： Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。
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“Google Cloud 基础知识：核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务，并提供重要的资源和政策管理工具。
Logging and Monitoring in Google Cloud
Earned Feb 28, 2022 EST
可靠的 Google Cloud 基础设施: 设计和流程
Earned Feb 26, 2022 EST
Developing a Google SRE Culture
Earned Feb 23, 2022 EST
在 Google Cloud 上为机器学习 API 准备数据
Earned Feb 9, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Feb 8, 2022 EST
在 Google Cloud 上设置应用开发环境
Earned Feb 7, 2022 EST
Google Cloud 基础知识：核心基础设施
Earned Feb 6, 2022 EST
为 Compute Engine 实现云负载均衡
Earned Feb 5, 2022 EST