GDev-100: Google Cloud Platform for Developers


  • Duration: 5 Days
  • Mode of Delivery: Online -Instructor-led training
  • Job role: Cloud Architect, Developer
  • Preparation for exam: Google certification exam
  • Cost: USD$2,750.00

This course teaches you how to develop applications that can opertae in the flexible infrastructure and platform services provided by Google Cloud Platform(GCP). In this course, you will learn how to dveleop, analyze and deploy applications using GCP-based components.

20 in stock

SKU: AZ-303-1-1 Categories: , ,


This Google Cloud Platform Architect course is well-suited for: Software developers, Cloud solutions architects, Systems operators, DevOps engineers


  • Knowledge of Google Cloud Platform fundamentals or any cloud platform is beneficial
  • Basic knowledge of command-line tools and Linux operating system environments

Skills Gained

In depth Understanding on Google Cloud Platform
  • GCP Services – Networking , Storage , Databases, Containers, Virtual Machines, App Engine, Security etc
  • GCP Compute Service : Virtual Machine (GCE), App Engine (GAE), Container Service (GKE), Google Cloud Function
  • GCP Networking VPC, CDN, Interconnect, DNS
  • GCP Management Tools – Stackdriver Monitoring, Logging, Trace, Error Reporting, Deployment Manager, Shell, Console, Cloud SDK
  • GCP Storage & Database Service : Cloud Storage, Cloud SQL, Cloud BigQuery, Cloud Spanner, Cloud DataStore, Cloud Spanner
  • GCP IAM and Security : Cloud IAM, KMS, Resource Manager, Security Scanner

Course outline

Module 1: Why GCP?
The public cloud landscapes
• Amazon Web Services
• Microsoft Azure
Google Cloud Platform
• Standing on the shoulders of giants
• A world-class global presence
• Choosing your own adventure
• Leading the way for big data
• The Open Cloud and innovation
• Dedication to customer success
• Bottom-up security
• In good company

Module 2: The Google Cloud Console
Getting started – Google Cloud projects
• Architectural role of Google Cloud projects
• Creating a project
• Free trials on GCP
The Google Cloud Console
• Understanding the Cloud Console dashboard
The Google Cloud Shell
• Launching the Cloud Shell
• Supporting multiple sessions
• Features and integrations
• File management
• Web Preview
• The Cloud Shell Code Editor
• Opening in Cloud Shell
• Trying it out
• Installing additional tools
• Boost mode
• Repairing the Cloud Shell
Other tools
• Mobile apps
• Developer tool integrations

Module 3: APIs, CLIs, IAM, and Billing
Google Cloud APIs
• Managing APIs
• Google APIs Explorer
• Trying out the APIs Explorer
The Google Cloud SDK
• Installing the Google Cloud SDK
The gcloud command-line tool
• The basics of gcloud
• Command groups
• Root commands
• Global flags
• Initializing the Google Cloud SDK
• Authentication
• Managing your Google Cloud SDK
• Updating and rollbacks
• Alpha and beta channels
• Configurations in the Google Cloud SDK
• Modifying configuration properties
• Multiple configurations
Other command-line tools
• bq
• gsutil
• kubectl
Automating tasks with gcloud
• Modifying output and behavior
• Formatting attributes
• Formatting projections
• Filtering
Google Cloud IAM
• How IAM works
• IAM roles
• The structure of IAM policies
• Organization-level policies
• Project-level policies
• Resource-level policies
• Cross-project access
• Managing IAM
• Service accounts
Billing on Google Cloud
• Billing accounts
• Billing accounts and IAM
• Budgets and billing alerts
• Google Cloud Platform Pricing Calculator
• Creating an estimate

Module 4: Google App Engine Compute services on the GCP
• Google Compute Engine
• Google Kubernetes Engine (GKE)
• Google App Engine
• Google Cloud Functions
• General considerations
Google App Engine
• Features and benefits
• Developer velocity
• Visibility
• Scalability
• Simple integrations
• Structure of a Google App Engine application
• Architecture of an App Engine solution
• Microservices
• Batch work and task queues
• App Engine locations
• IAM on the Google App Engine
• App Engine service accounts
• The standard and flexible environments
• Standard environment
• Flexible environment
• Setting up the App Engine
The App Engine standard environment
• Language support
• Developing for the App Engine standard environment
• The Python runtime
• WSGI and CGI
• Getting started
• The App Engine development server
• The Go runtime
• Running multiple services locally
• The Java runtime
• Deploying App Engine standard services
• Deployment behavior
• Splitting network traffic
• Instance classes
• Pricing in the standard environment
• Spending limits
The App Engine flexible environment
• Benefits of the flexible environment
• More control over the infrastructure
• Application portability
• Language support
• Developing for the flexible environment
• Deploying App Engine flexible apps
• Container technologies
• Google Container Builder
• Google Container Registry
• Custom runtimes
• Building custom runtime services
• Deploying a service to the flexible environment
• Pricing in the flexible environment
App Engine resources and integrations
• Task queues
• Push and pull queues
• Push queues
• Named queues
• Pull queues
• Creating tasks
• Structuring tasks queues
• Scheduled tasks
• Deploying a cron definition
• Trying the App Engine cron service
Scaling App Engine services
• Autoscaling
• Basic and manual scaling
Externalizing configuration and managing secrets
• Application configuration files
• Compute Engine metadata server
• Runtime Configurator
• Cloud Key Management Service (KMS)
• General considerations
Networking and security
• The App Engine firewall
• Cloud Endpoints
• Google Cloud IAP
• Virtual private networks

Module 5: Google Kubernetes Engine Google Kubernetes Engine
• When to choose GKE
• GKE or App Engine Flex
Creating and maintaining a GKE cluster
• Node pools
• Multi-zonal and regional clusters
• Container Registry
Deploying workloads to GKE
• Rolling updates
• Rolling back updates
• Scaling deployments
• Manually scaling deployments
• Automatically scaling deployments
Exposing GKE Services
• Exposing services within a cluster
• Exposing services to external traffic
Managing secrets with GKE
• Creating/Storing secrets
• Using secrets

Module 6: Google Cloud Functions
Functions as a Service
Google Cloud Functions
• Advantages of Cloud Functions
• Price
• Scalability
• Developer velocity
• Considerations when using Cloud Functions
Invoking Cloud Functions
• HTTP functions
• Processing HTTP requests
• Background functions
• Cloud Pub/Sub functions
• Cloud Storage functions
• Background function retries and termination
Developing Cloud Functions
• Using the Cloud Console
• Local development
• Debugging functions
Deploying Cloud Functions
• Deploying from a local machine
• Deploying from a source repository
Integrating with other Google services
IAM and billing
• Cloud Functions and IAM
Frameworks and tooling

Module 7: Google Compute Engine
Understanding Compute Engine
• IaaS
• Infrastructure as Code (IaC)
• More than virtual machines
• When to use Compute Engine
• A straightforward migration path
• Host anything
• Building a robust global presence
• Long running and resource intensive processes
• Security and compliance
Virtual machines on Google Compute Engine (GCE)
• Machine types
• Standard machine types
• High-memory machine types
• Mega-memory machine types
• High-CPU machine types
• Shared-core machine types
• Custom machine types
• Extended memory
• Other resources
• Disk storage
• GPUs
• Images
• Public images
• Premium images
• Community images
• Container images
Managing Compute Engine instances
• Creating instances
• Remote access
• SSH access
• SCP access
• Remote Desktop Protocol (RDP) access
• Metadata server
• Default metadata
• Project-wide metadata
• Instance-specific metadata
• Setting and removing metadata
• Querying metadata from within instances
• Trying it out
• Modifying API responses
• Startup and shutdown scripts
• Startup scripts
• Shutdown Scripts
• Windows machines
• Updates and patches
• Availability policies
• Maintenance behavior
• Restart behavior
• Relocating an instance
Storage solutions
• Persistent disks
• Standard and solid-state drive (SSD) persistent disks
• Persistent disk performance
• Boot disks
• Managing persistent disks
• Persistent disk snapshots
• Local SSDs
Creating scalable solutions with GCE
• Custom images
• Creating images from a persistent disk
• Copying an image
• Creating images from snapshots
• Golden images
• Security concerns
• Managed instance group (MIG)
• Instance templates
• Creating MIGs
• Built for resilience
• Autoscaling
• Autohealing
• Change management
• Performing a rolling update
IAM and service accounts
• Administrative operations
• General roles
• Compute resource roles
• Network and security resource roles
• Compute instance IAM
Pricing on GCE
• Instance discounts
• Preemptible instances
• Committed use discounts
• Sustained use discounts
• Other resource costs
• Always-free tier

Module 8: NoSQL with Datastore and Bigtable
NoSQL solutions on GCP
• NoSQL technologies
Google Cloud Datastore
• When to use Datastore
• Getting started
• Datastore locations
• Managing entities in the Cloud Console
Datastore core concepts
• The structure of Datastore data
• Entities, kinds, and properties
• Data types
• Entity identifiers
• Namespaces
• Ancestry paths and keys
• Entity groups and consistency
• Entity groups
• Consistency and queries
• Working with entities
• Queries with GQL
• Using GQL in the Cloud Console
• Indexes
• Single property indexes
• Composite indexes
• Datastore under the hood
• The entities table
• Key
• Entity group
• Kind
• Properties
• Custom indexes
• Index tables
• EntitiesByKind
• EntitiesByProperty
• EntitesByCompositeProperty and Custom Indexes
Datastore management and integrations
• Administrative tasks
• The Datastore Admin Console
• gcloud operations
• Integrations with other GCP services
• App Engine standard environment
• Other GCP services
• Datastore pricing and IAM
• Permissions in Datastore
Google Cloud Firestore
• Comparison to Datastore
• A promising future
Google Bigtable
• Core concepts
• Structure of Bigtable data
• Columns and column families
• Column families
• Scalable and intelligent
• Bigtable under the hood
• Building on other Google technologies
• Tablets and servers
• Creating and managing clusters
• Instances, clusters, and nodes
• Development instances
• Bigtable locations
• Create a development cluster
• Using gcloud
• Scaling clusters
• Promoting development clusters
• Deleting a cluster
• Interacting with data on Bigtable
• The cbt command-line interface
• The Bigtable HBase Client
• Platform integrations
• BigQuery external tables
• Dataflow Bigtable IO
• Bigtable pricing and IAM
• Permissions in Bigtable

Module 9: Relational Data with Cloud SQL and Cloud Spanner
Google Cloud SQL
Configuring Cloud SQL instances
• Creating a Cloud SQL instance
• Database engines
• MySQL generations
• Machine and storage types
• Choosing a machine type
• Configuring storage
• Cloud SQL locations
• When to use multiple instances
Connecting to Cloud SQL
• Authorized networks
• Connecting with gcloud
• SSL support
• Establishing an SSL Connection
• The Cloud SQL Proxy
• Setting up the Cloud SQL Proxy
• Authenticating with the Cloud SQL Proxy
• Trying it out
Managing Cloud SQL instances
• Maintenance operations
• Importing data to Cloud SQL
• Exporting data to cloud storage
• Backups and recovery
• Trying it out
• Point-in-time recovery
• Updates
• Database flags
• Database flags and SLAs
• Replicas and high availability
• Read-only replicas
• External replicas
• High availability
• Forcing a failover
• Scaling Cloud SQL instances
• Scaling Storage
• Scaling compute
• Alerting on resource pressure
• Horizontal scaling
Migrating databases to Cloud SQL
Cloud SQL IAM and users
• IAM policies
• Database users
• Default and system users
• Additional users
• Changing user passwords
• Cloud SQL Proxy users
• Cloud SQL pricing
Google Cloud Spanner
• Instances and instance configurations
• Regional configurations
• Multi-region configurations
• Nodes, databases, and tables
• Creating a Cloud Spanner instance
• Importing data into Cloud Spanner
• Performing a simple query
Understanding Cloud Spanner
• Cloud Spanner and CAP theorem
• Maintaining consistency
• TrueTime and linearization
• Paxos groups
• Read operations
• Write operations
• Transactions
• Database design and optimizations
• Query execution plans
• Primary keys
• Data collocation and interleaving
• Secondary indexes and index directives
Cloud Spanner administration
• Cloud Spanner IAM Roles
• Cloud Spanner prices

Module 10: Google Cloud Storage
GCS basics
• Buckets
• Bucket names
• Domain-named buckets
• The global bucket namespace
• Objects
• Object data
• Object metadata
• Virtual file structures
• Using gsutil
• Creating and using a bucket
• Uploading files to GCS
Storage classes and locations
• Regional and Multi-Regional Storage
• Standard and durable reduced availability
• Nearline and Coldline Storage
• Cloud Storage locations
• Nearline and Coldline Storage locations
• Choosing the right storage class
• Cloud Storage pricing
• Bucket and object storage classes
Automating object management
• Monitoring lifecycle events
• Object versioning
Data governance in Cloud Storage
• Cloud Storage IAM
• ACLs
• Limitations of concentric access control
• Customer supplied encryption keys
• Signed URLs
Capabilities and integrations
• Integrating with Google Cloud Functions
• Static web content and Backend Buckets

Module 11: Stackdriver
Lessons from SRE
• Monitoring and alerting
Preparation for this Module
Stackdriver basics
• Stackdriver and GCP projects
• Creating and linking a Stackdriver account
Stackdriver Logging
• Filtering and searching
• Basic filtering
• Advanced filtering
• Exporting Stackdriver logs
• Exporting to Cloud Storage
• Exporting to BigQuery and Cloud Pub/Sub
Monitoring and alerting
• The Stackdriver Monitoring console
• Exploring Stackdriver metrics
• Creating dashboards
• Stackdriver alerting policies
• Policy conditions
• Creating an alerting policy
• Notifications and documentation
• Stackdriver incidents
• Other types of metrics
Error reporting
• Investigating errors
Stackdriver APM
• Stackdriver Trace
• Investigating application latency
Stackdriver Debugger
• Debugging the todos services
• Logpoints
• Stackdriver Profiler

Module 12: Change Management
Preparing for this Module
Google Cloud Source Repositories
Google Cloud Deployment Manager
• Declarative configuration management
• Basic configurations
• Resource types and properties
• Deployments
• Deploying a simple configuration
• Deployment manifests
• Updating deployments
• Create and delete policies
• Maintaining deployment state
• Remediation
• Templates
• Creating a template
• Other template features
• Cloud Launcher and Deployment Manager
• Runtime Configurator
• Watchers
• Waiters
Google Cloud Container services
• Google Container Registry – GCR
• Container Builder
• Build triggers
Continuous deployment in Google Cloud

Module 13: GCP Networking for Developers
Networking fundamentals
• Virtual private networks
• Subnetworks
• Configuring VPC networks
• Networks and compute resources
• Firewall rules
• Components of a firewall rule
• Action
• Direction
• Target
• Source or destination
• Protocol and port
• Priority
• Securing networks with firewall rules
• Routes
• IP addresses
• Internal and external IP addresses
• Ephemeral and static IP addresses
• Global IP addresses
Google load balancers
• Network load balancers
• Target pools
• Forwarding rules
• Health checks
• Failover ratio and backup pools
• Creating a TCP network load balancer
• Internal load balancing
Global load balancers
• Components of global load balancers
• Backend services
• Target proxies
• Global forwarding rules
• SSL and TCP proxies
• HTTP(S) load balancers
• Autoscaling load balanced resources
Google Cloud DNS
Access control and API management
• Google Cloud Endpoints
• Services
• API providers
• Access and discovery
• Identity-Aware Proxy
• Cloud Armor

Module 14: Messaging with Pub/Sub and IoT Core
Google Cloud Pub/Sub
• Topics and subscriptions
• Push and pull message delivery
• Pull subscriptions
• Push subscriptions
• Choosing a subscription model
• Message acknowledgment
• Nacking messages
• Designing for resilience
• Message loss
• Processing failures
• Duplicate messages
• Out-of-order messages
Google Cloud IoT Core
• Device management and registries
• Device authentication and security
• Consuming device data

Module 15: Integrating with Big Data Solutions on GCP
Big data and Google Cloud Platform
Cloud Dataflow
• Evolution of data processing at Google
• Pipelines
• Collections
• Transformations
• Element-wise transforms
• Aggregate transforms
• Composite transforms
• Sources and sinks
• Creating and executing pipelines
• Executing pipelines locally
• Executing pipelines on Cloud Dataflow
• Executing streaming pipelines
• Pipeline templates
• Google provided pipeline templates
• Managing Cloud Dataflow jobs
Google BigQuery
• How BigQuery executes queries
• Integrating with BigQuery
• BigQuery as a Cloud Dataflow Sink
• Batch loading files from Cloud Storage
• Streaming inserts
• Exploring BigQuery data


Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date

Product Information

It is true—there is no cloud: it’s just someone else’s computer. With the cloud, what we are actually doing is accessing resources and consuming services that are hosted on someone else’s computer. If we want to be more precise, the cloud is a pool of computers.
The five essential characteristics of the cloud are as follows:
• On-demand self-service: Services are provisioned automatically without manual provider intervention.
• Broad network access: Resources are available through the network.
• Resource pooling: Resources are pooled from a shared pool, giving the user a sense of location independence. For some of the resources, the location might be restricted.
• Rapid elasticity: Services can be elastically provisioned and deprovisioned with capacity being managed by the provider.
• Measured service: Resource usage is monitored and can be reported on.

The four deployment models are as follows:
• Private cloud: Used by specific organizations, but can be managed by third parties
• Public cloud: Used by the general public
• Community cloud: Used by specific communities
• Hybrid cloud: Composed of two or more different clouds
When we look at GCP, it fulfills all of the five characteristics and fits into the public cloud deployment model. In the next section, we will have a look at GCP itself. Google has been developing its own tools to deliver services into such a model as: Gmail, YouTube, Google Drive, and Google+ for years. These tools have been converted into services that can be consumed by others. Consumers are given the amazing scalability that Google has to use for their own purposes. Google Cloud Platform (GCP) lets you choose from computing, storage, networking, big data, and machine learning (ML) services to build your application on top of them. The number of services is growing constantly, and new announcements are made on an almost weekly basis. New services and features are released, first as alpha then as beta versions, and finally, are made available globally. The early releases are available even earlier for selected customers and partners. This allows the services to be tested by external parties even before the official release.
GCP Developers create and manage applications on the GCP architecture according to the needs and requirements of their company. They are given a variety of options when it comes to developing such solutions. Depending on our requirements and flexibility, developers can choose from one of the following service models:
• Infrastructure as a Service (IaaS): Google Compute Engine (GCE)
• Container as a Service (CaaS): Google Kubernetes Engine (GKE)
• Platform as a Service (PaaS): Google App Engine (GAE)
• Function as a Service (FaaS): Cloud Functions

Additional Information and FAQs

CERTFICATE OF COMPLETION: Participants will receive a certificate of completion at the end of a course. This is not an official certification for the product and/or software. Our courses do indicate the appropriate certification exam(s) that the participant can sit. Data Vision Systems does not provide certification or deliver the certification exams. Participants are responsible for arranging and paying for the certification exams on the appropriate certification body.

CANCELLATION POLICY: There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so.


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