Google Cloud Platform培训

Google Cloud Platform培训

Google Cloud Platform

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Google Cloud Platform大纲

代码 名字 期限 概览
cpb102 CPB102: Machine Learning with CloudML 8小时 This 8-hour instructor led course builds upon CPB100 and CPB101 (which are prerequisites). Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn machine learning and Tensorflow concepts and develop hands-on skills in developing, evaluating, and productionizing machine learning models. This class is intended for programmers and data scientists responsible for developing predictive analytics using machine learning.  The typical audience member has experience analyzing and visualizing big data, implementing cloud-based big data solutions, and transforming/processing datasets. Objectives Understand what kinds of problems machine learning can address Build a machine learning model using TensorFlow Build scalable, deployable ML models using Cloud ML Know the importance of preprocessing and combining features Incorporate advanced ML concepts into their models Invoke and customize ML APIs Productionize trained ML model   Module 0: Welcome  [⅓ hr] We assume that attendees attended CPB100. Logistics Introductions Module 1: Getting started with Machine Learning [1½ hr] What is machine learning (ML)? Effective ML: concepts, types Evaluating ML ML datasets: generalization Lab: Explore and create ML datasets Module 2: Building ML models with Tensorflow [2 hr] Getting started with TensorFlow Lab: Using tf.learn TensorFlow graphs and loops + lab Lab: Using low-level TensorFlow + early stopping Monitoring ML training Lab: Charts and graphs of TensorFlow training Module 3: Scaling ML models with CloudML [1 hr] Why Cloud ML? Packaging up a TensorFlow model End-to-end training Lab: Run a ML model locally and on cloud Module 4: Feature Engineering [1.5 hr] Creating good features Transforming inputs Synthetic features Preprocessing with Cloud ML Lab:   Feature engineering Module 5: ML architectures [optional] Wide and deep Image analysis Embeddings and sequences Recommendation systems Summary
cp100a CP100A: Google Cloud Platform Fundamentals 8小时 This 1 day instructor-led class provides an overview of Google Cloud Platform products and services. Through a combination of presentations and hands-on labs, participants learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies. This class is intended for solutions developers, systems operations professionals, and solution architects planning to deploy applications and create application environments on Google Cloud Platform. This class is also suitable for executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. At the end of this one-day course, participants will be able to: Identify the purpose and value of each of the Google Cloud Platform products and services Explain the difference between Iaas and PaaS List the methods of interacting with Google Cloud Platform services Describe ways in which customers have used Google Cloud Platform to improve their businesses Understand how to choose an appropriate application deployment environment on Google Cloud Platform: Google App Engine, Google Container Engine, or Google Compute Engine Deploy an application to: Google App Engine, Google Container Engine, and Google Compute Engine Compare the Google Cloud Platform storage options: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore Deploy an application that uses Google Cloud Datastore and Google Cloud Storage to store data Load data into BigQuery and query it Module 1: Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform Define the components of Google's network infrastructure, including: Points of presence, regions, and zones Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Lab: Sign Up for the Free Trial and Create a Project Register for the GCP free trial Create a project using the Cloud Platform Console Module 2: Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform Understand the purpose of and use cases for Identity and Access Management List the methods of interacting with Google Cloud Platform Lab: Getting Started with Google Cloud Platform Deploy a LAMP stack using Google Cloud Launcher Module 3: Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore Contrast the App Engine Standard environment with the App Engine Flexible environment Understand the purpose of and use cases for Google Cloud Endpoints ​Lab: Deploying Applications Using App Engine and Cloud Datastore Deploy a sample Python application called Bookshelf to the App Engine standard runtime environment Test the Bookshelf application and inspect data saved to Cloud Datastore Module 4: Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable Learn how to choose between the various storage options on Google Cloud Platform Lab: Integrating Applications with Google Cloud Storage Create a Google Cloud Storage bucket to store images Deploy an App Engine application that uses Cloud Storage Use the Cloud Storage Browser to view objects Module 5: Google Container Engine Define the concept of a container and identify uses for containers Identify the purpose of and use cases for Google Container Engine and Kubernetes Lab: Deploying Applications Using Google Container Engine Create a container cluster using the Cloud SDK Build and push a Bookshelf image to Container Registry Use kubectl to deploy the Bookshelf container Module 6: Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine Understand the various Google Cloud Platform networking and operational tools and services Lab: Deploying Applications Using Google Compute Engine Create a Google Compute Engine instance Deploy the Bookshelf application using a startup script Add a firewall rule to allow HTTP traffic to the application Module 7: Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms Lab: Getting Started with BigQuery Load a CSV file into a BigQuery table using the web UI Query the data using the BigQuery web UI Query the data using the CLI and the BigQuery shell
cpa200 CPA200: Google Cloud Platform Architect Fundamentals 8小时 The intended audience is people who will be designing solutions using Google Cloud Platform but who do not have a lot of experience with designing cloud-based solutions. At the end of this one-day class, participants will be able to: Understand the core tenants to be considered when designing & deploying to a cloud Be confident enough to leverage what Google Cloud Platform offers without focusing on undifferentiated heavy lifting Understand how to get started on Google Cloud Platform Be able to identify the appropriate Google Cloud Platform products to use for popular architectural patterns   Module 1 - Keeping things simple Managing applications at scale Describe the problems that Google addressed to allow them to deploy Google scale applications Explain how using Google Cloud addresses each of the problems faced when designing for distributed scalable applications that are deployed across regions Micro services Security & compliance Module 2 - Focusing on Your Business Managing applications at scale Describe the problems that Google addressed to allow them to deploy Google scale applications Explain how using Google Cloud addresses each of the problems faced when designing for distributed scalable applications that are deployed across regions Micro services Security & compliance Module 3 - Embrace Failure Decoupling Self healing Testing Module 4 - Moving to the Cloud Migrating applications to Google Cloud Platform Off site disaster recovery and archival with Google Cloud Platform Hybrid architectures and multi cloud deployments Lock in is not an issue using Google Cloud Platform Module 5 - Architectural patterns using Google Cloud Platform Cloud Deployment manager Image processing Mobile applications Big Data Virtual network environments
cpo200 CPO200: Google Cloud Platform for Systems Operations Professionals 32小时 This 4 day instructor-led class introduces participants to the implementation of application environments and public cloud infrastructure using Google Cloud Platform. Through a combination of instructor-led presentations and hands-on labs, students learn how to deploy cloud infrastructure components such as networks, systems, and applications. This course is designed to give participants a robust hands-on experience and is primarily lab-focused. This class is intended for Systems Operations professionals and Systems Administrators using Google Cloud Platform to create or migrate application environments and infrastructure. At the end of this four-day course, participants will be able to: Understand the core tenants to be considered when designing & deploying to a cloud Use the Google Developers Console to create and manage multiple projects Use service accounts and permissions to share view-level access between projects Create Google Compute Engine instances Create a non-default network and review your network configuration Compare default and non-default networks Create firewall-rules with and without tags Create and use a customized Compute Engine image Set authorization scopes for a Compute Engine instance Reserve an external IP address for an instance Snapshot a Compute Engine instance Snapshot a data disk Create an image using a boot persistent disk Upload an image to Google Container Registry Create a Compute Engine instance group with instances Create a Cloud SQL instance using the Cloud SDK Deploy and test a web application Add instance and project metadata Query instance and project metadata using the Cloud SDK Create an instance using a startup script in metadata and Google Cloud Storage Create an instance with a shutdown script and install the Cloud Logging agent Use the API Explorer to query an API request Run sample code that uses the Google API Client Library Test and build a container that uses the Cloud SQL APIs Create an instance template and managed instance group Configure a managed instance group for autoscaling Create multiple autoscaled managed instance groups Configure fault-tolerant HTTP load balancing Test health checks for use with HTTP load balancing Manage application deployment using Jinja and Python templates with Google Cloud Deployment Manager Delete Google Cloud Platform projects and resources Module 1: Google Cloud Platform Projects Identify project resources and quotas Explain the purpose of Google Cloud Resource Manager and Identity and Access Management Lab: Google Cloud Platform Projects Use the Google Developers Console to create and manage multiple projects Use service accounts and permissions to share view-level access between projects Module 2:Instances Explain how to create and move instances Identify how to connect to and manage instances Lab: Google Compute Engine Instances and Machine Types Create an instance using the Google Developers Console Configure the Cloud SDK on the Compute Engine instance Initialize Cloud Source Repositories using Git Module 3: Networks Explain how to create and manage networks in projects Identify how to create and manage firewall rules, routes, and IP addresses Lab: Google Compute Engine Networks Create a non-default network Compare default and non-default networks Create firewall-rules with and without tags Review network configuration in Google Cloud Monitoring Module 4: Disks and Images Explain how to create and manage persistent disks Identify how to create and manage disk images Lab: Google Compute Engine Disks and Images Create an instance and install the Java 7 JRE from OpenJDK Create a customized Compute Engine image Launch and test a Compute Engine instance based on your image Module 5: Authorization Explain the purposes of and use cases for Google Compute Engine service accounts Identify the types of service account scopes Lab: Google Compute Engine Authorization Set authorization scopes for a Compute Engine instance Reserve the external IP address for the new instance Install and configure Jenkins on a Compute Engine instance Module 6: Snapshots Identify the purpose of and use cases for disk snapshots Explain the process of creating a snapshot Lab: Google Compute Engine Snapshots Prepare and snapshot a Compute Engine instance Restore and test the snapshot to a different zone Snapshot a data disk without shutting down an instance Module 7: Google Cloud Storage Explain the purpose of and use cases for Google Cloud Storage Identify methods for accessing Google Cloud Storage buckets and objects Explain the security options available for Google Cloud Storage buckets and objects Lab: Google Cloud Storage for Backups Create and configure Nearline and DRA buckets Modify the lifecycle management policy for a bucket Copy data to a bucket using the Cloud SDK Review, modify, and test bucket ACLs Configure Jenkins to perform a backup to Cloud Storage Test and verify that the backups are working Lab: Google Container Registry Create a customized Jenkins build node instance Create an image using the instance's boot persistent disk Create a test build node instance based on the new image Test uploading images to Google Container Registry Module 8: Instance Groups Identify the purpose of and use cases for instance groups Explain the process of creating and using instance groups Lab: Google Compute Engine Instance Groups Create a Compute Engine instance group with instances Define Jenkins build tasks and run them Run the build tasks to create a guestbook image Module 9: Google Cloud SQL Understand how to create and administer Cloud SQL instances Explain how to access Cloud SQL instances from Compute Engine instances Lab: Google Cloud SQL Create a Cloud SQL instance using the Cloud SDK Create a Compute Engine instance from a custom image Deploy and test the Guestbook web application Module 10: Metadata Explain the purpose of metadata and identify the use cases for project and instance metadata Identify how to set and query metadata Lab: Google Compute Engine Metadata Add instance and project metadata Query instance and project metadata using the Cloud SDK Query metadata from inside a Compute Engine instance Module 11: Startup and Shutdown Scripts Identify the purpose of and use cases for startup and shutdown scripts Lab: Google Compute Engine Startup Scripts Create an instance with a startup script in metadata Create an instance with a startup script from Cloud Storage Create an instance with a shutdown script and install the Cloud Logging agent Lab: Google API Client Library Use the API Explorer to query an API request Run sample code that uses the Google API Client Library Test and build a container that uses the Cloud SQL APIs Create a new Compute Engine image Module 12: Autoscaling Explain the use cases for autoscaling and how autoscaling functions Identify the purpose of autoscaling policies Lab: Google Compute Engine Autoscaler Create an instance template and managed instance group Configure the managed instance group for autoscaling Generate an artificial load to trigger scaling of your cluster Module 13: Load Balancing Explain the differences between network load balancing and HTTP load balancing Identify the purpose of and use cases for cross-region and content-based load balancing Lab: HTTP/HTTPS Load Balancing Create multiple autoscaled managed instance groups Configure fault-tolerant HTTP load balancing Test health checks for use with HTTP load balancing Lab: Google Cloud Deployment Manager Create a Guestbook deployment using a plain YAML format Manage a Guestbook deployment using a Jinja template Create a Guestbook deployment using Python templates Lab: Deleting Cloud Platform Projects and Resources Delete Google Cloud Platform resources Test dependencies between resources Delete Google Cloud Platform projects
cpv200 CPV200: Google Container Engine and Kubernetes 8小时 This 1 day instructor­led class introduces participants to Google Container Engine (GKE) and Kubernetes. Through a combination of instructor­led presentations, demonstrations, and hands-on labs, students learn the key concepts and practices for deploying and maintaining applications using Google Container Engine. This class is intended for solutions developers, systems operations professionals, solution architects, and development operations professionals who develop, migrate, and deploy container­based applications on Google Cloud Platform (GCP). At the end of this one­day course, participants will be able to: Identify the purpose of and use cases for Google Container Engine and Kubernetes Explain the function of the container cluster components: pods, labels, replication controllers, and services Identify the purpose of and use cases for Google Container Registry Create a Docker image and send it to the Google Container Registry Explain the function of the cluster components: the master instance an cluster nodes Use the Cloud Platform Console to create a container cluster Use the Google Cloud SDK command­line tools and the kubectl command­line utility to interact with container clusters Define a pod using a JSON template Deploy the pod to a Container Engine cluster Create a Container Engine cluster to host a dynamically scaled group of Redis instances  Complete a configuration file which defines a replication controller and the pod configuration that it manages After creating a replication controller and pods, rescale the group Deploy a container­based application using YAML files that define services, replication controllers, pods, and so on Define firewall rules and load balancers to expose a service for a container­based application Module 1: Introduction to Google Container Engine Identify the purpose of and use cases for Google Container Engine and Kubernetes Explain the function of the container cluster components: pods, labels, replication controllers, and services Identify the purpose of and use cases for Google Container Registry Lab, Part I: Sign Up for the Free Trial and Create a Project Register for the GCP free trial Create a project using the Cloud Platform Console Lab, Part II: Create a Compute Engine Labs Instance Create a Linux­based Compute Engine VM instance Configure the Cloud SDK on the instance Lab, Part III: Create a Docker Image and Send It to the Registry Create a Docker image and send it to the Google Container Registry Module 2: Google Container Engine Fundamentals Explain the function of the cluster components: the master instance and cluster nodes Lab: Create a Container Cluster Use the Cloud Platform Console to create a container cluster Module 3: Interacting with Google Container Engine Describe the various methods used to interact with a container cluster Lab: Working with Container Engine clusters using the Cloud SDK and kubectl Use the Google Cloud SDK command­line tools and the kubectl command­line utility to interact with container clusters Module 4: Container Clusters Describe the high­level container cluster infrastructure Identify the components of a container cluster node Module 5: Pods Describe the purpose of a pod and how to work with pods Lab: Define and Deploy a Pod Define a pod using a JSON template Deploy the pod to a Container Engine cluster Module 6: Replication Controllers Describe the purpose of a replication controller and how to work with replication controllers Lab: Replication Controllers Create a Container Engine cluster to host a dynamically scaled group of Redis instances  Complete a configuration file which defines a replication controller and the pod configuration that it manages After you creating the replication controller and its pods, rescale the group Module 7: Services Describe the purpose of a service and how to work with services Lab: Deploy an Application Deploy a container­based application using YAML files that define services, replication controllers, pods, and so on Define firewall rules and load balancers to expose a service for a container­based application
cpd200 CPD200: Developing Solutions on Google Cloud Platform 24小时 This 3 day instructor-led class introduces participants to Solution Development for Google Cloud Platform. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to develop cloud-based applications using Google App Engine, Google Cloud Datastore, and Google Cloud Endpoints. This class is intended for experienced application developers who want to learn how to develop solutions using Google Cloud Platform to create highly scalable backends for both web and mobile applications. At the end of this one­day course, participants will be able to: Manage Google Cloud Source Repositories using the Google Cloud Platform Console Test an App Engine application using the App Engine SDK Access the App Engine Development Server Console Create an API using Google Cloud Endpoints Test a Cloud Endpoint API using the API Explorer Deploy an application to App Engine using the App Engine SDK Design, structure and configure an App Engine application using multiple services Create Client IDs using the Google Cloud Platform Console Secure App Engine services and Cloud Endpoints APIs using authentication Configure and upload new versions of App Engine services Integrate Google Cloud Logging into App Engine applications Review quota usage in a Google Cloud Platform project Integrate different types of storage with App Engine applications Create and implement a data model for use with Google Cloud Datastore Implement a variety of queries in Google Cloud Datastore Update the index configuration in Google Cloud Datastore Implement transactions using Google Cloud Datastore Review Google Cloud Trace reports in the Google Cloud Platform Console Integrate the Memcache API into an App Engine application to increase performance Configure, run and review the output of Google Cloud Security Scanner Configure the scaling behaviour of individual App Engine Services Create App Engine handlers for Push Task Queues Send email from an App Engine application using the Mail API Schedule Tasks in App Engine using the Cron Service Update the configuration of the Cron Service Secure Task Push, and Cron Service handlers  Export Google Cloud Platform data from a project Delete Google Cloud Platform projects and resources   Module 1: Developing Solutions for Google Cloud Platform Identify the advantages of Google Cloud Platform for solution development Identify services and tools available for solution development using Google Cloud Platform Compare examples of Google Cloud Platform architectures for solution development Lab: Google Cloud Source Repositories Create a project for the course Use Google Cloud Shell to develop and test an application using the App Engine SDK  Configure Google Cloud Source Repositories to remotely host code in Google Cloud Platform Module 2: Google Cloud Endpoints Identify Cloud Endpoints features Explain how to develop APIs using Cloud Endpoints Compare development of Cloud Endpoints APIs using Java and Python Lab: Google Cloud Endpoints Review and edit Cloud Endpoints source code Deploy an application to App Engine Test a Cloud Endpoints  API in the APIs Explorer Module 3: App Engine Services Explain the use cases for App Engine Services and how to use them in structuring an application Identify how to deploy and access individual App Engine services Explain how to route requests to individual services Lab: Google App Engine Services Review the code for a sample application used throughout the remainder of the course Deploy multiple App Engine services to a single project Module 4: User Authentication and Credentials Compare authentication and authorization Identify options for securing App Engine applications Explain the use cases for Application Default Credentials Lab: User Authentication Configure the OAuth consent screen and create a client ID Modify Conference Central to use your client ID Test Conference Central authentication Modify your admin service to require administrator rights Module 5: Managing App Engine Applications Explain the use cases for App Engine versions Identify how to access App Engine monitoring and logging services Explain the use of resource quotas and how to troubleshoot related errors Lab: Managing Google App Engine Applications Review App Engine settings, quotas, instances, and logs Update App Engine services to log to Cloud Logging Deploy new versions of your default and admin services Route all traffic to a new version of the default service Module 6: Storage for Solution Developers Compare storage options for App Engine Solutions Developers Explain the purpose of, and use cases for, Google Cloud Storage Compare Cloud SQL integration with App Engine and Compute Engine Explain basic Cloud Datastore terminology and concepts, including Entity Groups Lab: Google Cloud Datastore Update an existing application to save data persistently Test saving application data to Cloud Datastore List and view Cloud Datastore entities in the Google Cloud Platform Console Module 7: Queries and Indexes Identify available query filters for Cloud Datastore Compare single­property, and composite indexes in Cloud Datastore Configure and optimize indexes for Cloud Datastore Lab: Google Cloud Datastore Queries and Indexes Add support for querying entities by kind and ancestor Add query filters to Cloud Datastore searches Update an index configuration to support composite indexes Module 8: Entity Groups, Consistency, and Transactions Identify the steps of a Cloud Datastore write Compare strong and eventual consistency in Cloud Datastore Identify how to achieve strongly consistent queries Identify best practises for Cloud Datastore transactions Lab: Google Cloud Datastore Transactions Add support for using Cloud Datastore transactions to an application Add a Cloud Endpoint API method to view data from a different service Module 9: App Engine Performance and Optimization Identify Memcache types, use cases, and implementation patterns Compare available scaling behaviours for application services Configure application scaling for individual services Lab: Google App Engine Performance and Optimization Review Cloud Trace reports for an application Configure and run a security scan for an application Update an application to make use of memcache Configure and test application scaling for application services Module 10: Task Queues Compare Push and Pull Queues Explain how to schedule tasks with the Cron Service Configure and securing Push and Pull Queues, as well as the Cron Service Lab: Task Queue API Add a task handler to send an email using the Mail API Add a Cron Service handler and configuration to an existing application Lab: Deleting Google Cloud Platform Projects and Resources Export Google Cloud Platform data from a project Delete Google Cloud Platform resources Shut down a Google Cloud Platform project
cpb101 CPB101: Serverless Data Analysis with BigQuery and Cloud Dataflow 8小时 This 8 hour instructor led course builds upon the CPB100 (which is a prerequisite). Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. This class is intended for data analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data. Objectives Build up a complex BigQuery using clauses, inner selects, built-in functions and joins Load and export data to/from BigQuery Identify need for nested, repeated fields and user-defined functions Understand pipeline processing, terms and concepts Write pipelines in Java or Python and launch them locally or in the Cloud Implement Map,  Reduce  trransforms in Dataflow pipelines. Join datasets as side inputs Interoperate Dataflow, BigQuery and Cloud Pub/Sub for real-time streaming The basic thrust is to cover the foundations in Module 2, workloads they could migrate to GCP immediately (i.e., lift-and-shift) in Module 3, and the more transformational things (i.e., what’s next) in Module 4. Module 0: Welcome  [⅓ hr] We assume that attendees may attended CPB100. Logistics Introductions Module 1: Serverless data analysis with BigQuery [3  hr] A 3 hour (1.5 hours lecture + 1.5 hours hands-on) deep dive into details of BigQuery. What is BigQuery? Queries and functions + lab Load and export data + lab Advanced Capabilities Performance and pricing Module 2: Serverless, autoscaling data pipelines with Dataflow [3  hr] A 3 hour (1.5 hours lecture + 1.5 hours hands-on) deep dive into details of Cloud Dataflow.  What is Dataflow? Data pipeline + lab MapReduce in Dataflow + lab Side inputs + lab Streaming + demo Module 3: Summary [⅓  hr] Where to go from here Resources
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