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Google Cloud Training courses

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Platform Fundamentals Course Outline:

Module 1:  Introduction to Google Cloud Platform

  • Google Cloud Infrastructure
  • GCP Regions, Zones, Edge Caching, and Cloud CDN
  • GCP Services

Module 2: Setting Up Accounts and Billing

  • GCP Accounts, Billing Accounts, Projects, and Admin Setup
  • Account, Billing, Project, and Admin Setup

Module 3: Networking

  • GCP Networks, Subnets, Routes, and Firewall Rules
  • VMs in Networks
  • Lab: Add VMs, Explore the Default Network, and Test Connectivity

Module 4: Working with VM Instances

  • Google Compute Engine Machine Types
  • Instances, Persistent Disks, Local SSDs, and Preemptible VMs
  • VM and Web App Deployment
  • Lab: Deploy VMs with an App by Console and Command-Line

Module 5: Scaling and Load Balancing Apps

  • Google Compute Engine Instance Templates
  • Managed Instance Groups and Load Balancing
  • Autoscaling and Load Balancing Setup
  • Lab: Scale and Load Balance Instances and Test Under Load

Module 6: Isolating Instances and Apps

  • A 3-Tier Web App in GCP
  • A Custom Network with Custom Subnets and Firewall Rules
  • Lab: Build a 3-Tier Web App with Public Front-End and Private Backend

Module 7: Using Storage as a Service and Database as a Service

  • Google Cloud Storage and Google Cloud SQL
  • Cloud Spanner and Google Cloud Datastore
  • Google Cloud Bigtable and Google BigQuery
  • Lab: Use Gsutil Command-Line Tool to Perform Operations on Buckets and Objects in Cloud Storage
  • Lab: Load and Analyse Data in BigQuery

Module 8: Deployment and Monitoring

  • Google Cloud Deployment Manager, Google StackDriver
  • Lab: Deploy your Infrastructure Using Deployment Manager

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Google Cloud Platform Fundamentals Course Overview

This course teaches delegates about cloud platform fundamentals. This course focuses on networking, compute, storage, and database. Delegates will have a thorough understanding of Google cloud infrastructure, GCP regions, zones, edge caching, and cloud CDN. They will also gain an understanding of GCP networks, subnets, routes, and firewall rules.

This course will provide a comprehensive knowledge of Google compute engine machine types, instance, persistent disks, local SSDs, preemptible VMs. Delegates will get an understanding of how to deploy VMs with an App by console and command line. They will also acquire knowledge of Google compute engine instance templates, managed instance groups, and load balancing.

In this 1-day training, delegates will learn how to build a 3-tier web app with public front-end and private backend. Delegates will be familiarised with Google cloud storage, Google Cloud SQL, cloud spanner, Google cloud datastore, Google Cloud Bigtable and Google BigQuery. They will also gain knowledge of how to use gsutil command-line tool to perform operations on buckets and objects in cloud storage. At the end of this course, delegates will learn about Google cloud deployment manager and Google stack driver. They will gain an understanding of how to deploy infrastructure using a deployment manager.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (3 days)

Classroom (3 days)

Online Self-paced (24 hours)

Architecting Infrastructure with Google Cloud Platform Training​ Course Outline

Module 1 - Get Started with Google Cloud Platform

  • Introduction to Google Cloud
  • Role of the Cloud Architect
  • Solution Domains as an Approach to Design

Module 2 - Core Management Service

Cloud Resource Manager

  • Management Services
  • Resource Hierarchy
  • Labels and Quotas

Cloud IAM

  • Cloud IAM Overview
  • Service Accounts and Scopes on Google Compute Engine

Monitoring with Stackdriver

  • Stackdriver Overview
  • Stackdriver Logging Concepts
  • Stackdriver Monitoring Concepts
  • Trace, Error Reporting, and Debug Concepts

Module 3: Core Building Blocks

Google Cloud Storage

  • Cloud Storage Concepts
  • Using the Gsutil Command
  • Cloud Storage Security Concepts
  • Object Versioning and Lifecycle Management

Managed Databases on Google Cloud Platform

  • Introduction to Managed Databases
  • Managed Databases on Google Cloud
  • Cloud SQL and BigQuery Overview

Virtual Networks

  • VPC Concepts
  • Firewall Rules
  • Shared VPC Concept
  • Create a Custom Mode VPC Network on Google Cloud Platform
  • Create Firewall Rules on Google Cloud VPC Network

Interconnecting Networks (Hybrid Networking) 

  • Connecting Network to Google
  • Cloud VPN
  • Cloud DNS

Compute Engine – Virtual Machines

  • Compute Engine Overview
  • Disks
  • Images
  • Snapshots
  • Startup and Shutdown Scripts
  • Preemptible VM’s

Module 4: Elastic Cloud Infrastructure: Scaling and Automation

Load Balancing and Instance Groups

  • Force Multipliers- Automation and Scaling
  • Load Balancers
  • Instance Groups and Autoscaling
  • Creating a Load Balanced Managed Instance Group on Google Cloud Platform

Google Cloud CDN

  • Introduction to Google Cloud CDN
  • Cloud CDN Concept

Cloud Deployment Manager

  • Cloud Deployment Manager Concepts
  • Deploying Resources with Google Cloud Deployment Manager

Module 5: Elastic Cloud Infrastructure: Managed Compute Services

Compute Service Overview

  • Where to Run Code?

App Engine

  • App Engine Overview
  • Managing Versions of an App Engine Application

Kubernetes Engine

  • Container Resources
  • GKE Administration Concepts
  • GKE Commands
  • Creating and Deploying a Google Kubernetes Engine Cluster

Big Data, Machine Learning, and Data Lifecycle

  • Big Data and Machine Learning Services
  • Data Lifecycle

Module 6: Architecting Google Cloud Solution

Planning your Cloud Transition

  • Making a Case for the Cloud and GCP
  • Cost Optimisation
  • Architecting Cloud Applications

Migrating to Google Cloud

  • Planning a Successful Cloud Migration
  • Storage Transfer Service
  • Migration Applications

Resilient Cloud Solution Infrastructure

  • Disaster Recovery Concepts
  • Backup and Recovery Methods in GCP

Security and Compliance

  • Security Methods in GCP
  • Network Design for Security and Isolation
  • Legal Compliance and Audits

Development Practices

  • Software Development Lifecycle Concepts
  • Testing your Application for Resiliency

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud technologies.

Architecting Infrastructure with Google Cloud Platform Training​ Course Overview

Architecting with Google Cloud Platform focuses on designing and planning a cloud solution architecture, managing and provisioning the cloud infrastructure. Along with this, it also focuses on analysing and optimising technical and business process, managing implementations of cloud architecture and designing for security and compliance.

This course will teach delegates about the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform. In this course, delegates will learn about cloud resource manager and cloud AMI. They will also gain an understanding of stack driver logging and monitoring. This course describes Google cloud storage, cloud storage security concepts, trace, error reporting, and debug concepts.  Delegates will learn how to manage databases on the Google cloud platform. They will also gain an understanding of virtual networks, interconnecting networks (hybrid networking) and virtual machines. In virtual machines, they will also learn about disks, images, snapshot and preemptible VM’s.

In this 3-day course, delegates will learn about load balancing and instance groups. They will gain an understanding of how to create a load-balanced managed instance group on google cloud. Delegates will learn how to deploy resources with Google cloud deployment manager. They will go through compute services, app engine, kubernetes engine, big data, machine learning, and data lifecycle. On course completion, delegates will also get an understanding of Google cloud, disaster recovery, security and compliance.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (3 days)

Classroom (3 days)

Online Self-paced (24 hours)

Course Outline

The following modules are focused on acquiring knowledge about the Data Engineering on Google Cloud Platform. Delegates will learn about google cloud Dataproc and its running jobs as well as get an understanding of how to integrating Dataproc with Google Cloud platform. These modules will cover all essential concepts that required to become a Data Engineer on Google Cloud Platform.

Module 1: Google Cloud Dataproc Overview

  • Dataproc Overview
  • Understand Creating and Managing Clusters
  • Custom Machine types and preemptible worker nodes
  • Scaling and deleting Clusters
  • Creating Hadoop Clusters with Google Cloud Dataproc

Module 2: Running Dataproc Jobs

  • Running Pig and Hive jobs.
  • Separation of storage and compute
  • Understand Running Hadoop and Spark Jobs with Dataproc
  • Understand Submit and Monitor jobs

Module 3: Integrating Dataproc with Google Cloud Platform

  • Understand the Customise Cluster with initialisation Activities
  • Understand BigQuery Support
  • Understand GCP Services

Module4: Unstructured Data with Google’s Machine Learning APIs

  • Machine Learning APIs 
  • Use Cases of ML
  • Understand ML APIs
  • Adding Machine Learning Capabilities to Big Data Analysis

Module 5: Serverless Data Analysis with BigQuery

  • BigQuery Overview
  • Learn about Functions and Queries
  • Writing queries in BigQuery
  • Loading data into BigQuery
  • Exporting data from BigQuery
  • Loading and exporting data
  • Nested and repeated fields
  • Querying multiple tables
  • Complex queries

Module 6: Serverless, autoscaling data pipelines with Dataflow

  • Beam programming model Overview
  • Understand Data pipelines in Beam Python
  • Understand Data pipelines in Beam Java
  • Writing a Dataflow pipeline
  • Scalable Big Data processing using Beam
  • MapReduce in Dataflow
  • Incorporating additional data
  • Side inputs
  • Handling stream data
  • GCP Reference architecture

Module 7: Getting started with Machine Learning

  • What is machine learning (ML)
  • Machine Learning Types
  • Explore and create ML datasets

Module 8: Building ML models with Tensorflow

  • Understand TensorFlow
  • TensorFlow graphs and loops
  • Understand Use low-level TensorFlow
  • Understand Monitoring ML training
  • Charts and graphs of TensorFlow training

Module 9: Scaling ML models with CloudML

  • Cloud ML Overview
  • Understand TensorFlow model
  • Understand Running of ML Model

Module 10: Architecture of streaming analytics pipelines

  • Understand Stream data processing
  • Handling variable data volumes
  • Learn about unordered/late data
  • Designing a streaming pipeline

Module 11: Ingesting Variable Volumes

  • Cloud Pub/Sub Overview
  • Working of Cloud Pub/Sub

Module 12: Implementing streaming pipelines

  • Stream Processing Overview
  • Handle late data
    • Watermarks
    • Triggers
    • Accumulation
  • Understand Stream data processing pipeline

Module 13: Streaming analytics and dashboards

  • Streaming Analytics Overview
  • Querying Streaming Data with BigQuery
  • Google Data Studio Overview
  • Build a real-time Dashboard to visualise processed data

Module 14: High throughput and low-latency with Bigtable

  • Cloud Spanner Overview
  • Designing Bigtable schema
  • Ingesting into Bigtable
  • Understand streaming into Bigtable

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Prerequisites

There are no formal prerequisites for this course. It would be great if delegates have basic knowledge of managing data and its operations.

Audience

This course is designed for IT Professionals and Google Cloud platform learner. This course is also beneficial for who wants to be a certified engineer for this technology.

Data Engineering with Google Cloud Platform​ Course Overview

As we all know, Google is the curiosity Planner within Global technologies development. Google always responsible for changing the Curiosity to implementation the terms with perfections. The Google cloud platform provided numerous services for users and developers to develop future technologies and products. Google provides the data engineering service on its Google Cloud Platform. By collecting transforming and publishing data Engineer can enable data-driven for decision-making term. Data engineer can design, build, operationalise, secure and monitor data processing systems with a particular emphasis on security and compliance as well as scalability, efficiency, reliability and portability. Data engineer can able to leverage, deploy and continuously train pre-existing machine learning models.

This 3-day course provides the ability to implementation of data processing arrangements on the Google Cloud Platform. Delegates will learn about Google Cloud platform services are using for Data management. The Google cloud DataProc and its running Jobs concepts are also included in this course. Delegates will gain a better knowledge of how to design and build data processing systems on this platform as well as learn about process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. They also gain an understanding of how to integrating Dataproc with Google Cloud Platform. Also, Delegates have a chance to acquire technical knowledge of unstructured data with Google’s machine learning APIs and also gain an understanding of serverless Data Concepts from this course. They will gather knowledge of how to design a data processing system, build an end to end data pipelines, analyse data and machine learning.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Networking with Google Cloud Platform ​Course Outline

The following modules are focused on providing complete knowledge of networking in Google Cloud. From these technically arranged modules, delegates will gain a better understanding from initial stage networking to monitoring and troubleshooting network.

Module 1: Google Cloud VPC Networking Fundamentals

  • Default, Auto, and Custom Networks
  • Understand Networks and Subnets
  • IPv4 addresses
  • Cloud Domain Name System (DNS)
  • Create Compute Engine Instances with IP Aliases
  • Create Compute Engine Instances with Multiple Virtual Network Interfaces

Module 2: Controlling Access to VPC Networks

  • Understand IAM Policies
  • Control Access to Network Resources
  • Control Access to Compute Engine Instances with Tag-Based Firewall Rules

Module 3: Sharing Networks Across Projects

  • Configuring Shared VPC
  • Differentiate IAM Roles
  • Configure Peering Between Unrelated VPC Networks
  • Shared VPC and VPC Peering

Module 4: Load Balancing

  • Load Balancing Services
  • Explain Layer 7 HTTP(S) Load Balancing
  • Cloud Armor and CDN
  • Configure Internal Load Balancing

Module 5: Hybrid Connectivity

  • Hybrid Connectivity Overview
  • GCP Interconnect and Peering Services
  • Dedicated Interconnect and Partner Interconnect
  • VPN with Cloud Router
  • Direct and Partner Peering


Module 6: Network Design and Deployment

  • Network Design Patterns
  • Understand the Deployment Manager
  • Explain and Configure Network Solutions

Module 7: Network Monitoring and Troubleshooting

  • Configure Uptime Checks, Alerting Policies, and Charts 
  • Understand VPC Flow Logs
  • Describe Analyse Network Traffic

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Prerequisites

There are no formal prerequisites for this course. It will be beneficial if delegates have a basic knowledge of the Google cloud platform and network terms.

Audience

This course is designed for IT professionals and Google Cloud technologies learners.

Networking with Google Cloud Platform ​Course Overview

Networking is an essential element in any field of technology. Networking in the Google Cloud Platform helps to set up a network within networking options. Google Cloud Platform allows using numerous network resources and services from the cloud with the lowest latency. GCP provides key components such as Virtual Private Cloud (VPC) networks, subnets, Cloud NAT, interconnection among networks, NAT, load balancing, cloud DNS, and Cloud CDN for implementation of networks.

This 1-day course will provide a complete knowledge of networking on Google Cloud Platform. Delegates will learn how to design and deploy a network in the Google cloud platform. They will get an understanding of Google cloud VPC networking, sharing networks, hybrid connectivity, as well as load balancing in the Google Cloud Platform. From this course, delegates will acquire the troubleshooting skills to resolve the technical issues of networking.

On course completion, delegates will be able to design and deploy a network in Google Cloud Platform as well as manage the network in GCP.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Google BigQuery Training​ Course Outline

Module 1: Interacting with BigQuery

  • Introduction to BigQuery
  • BigQuery Sandbox and Web UI
  • Command-Line Tools
  • BigQuery Classic Web UI

Module 2: Running and Managing Jobs

  • Introduction
  • Running Jobs Programmatically
  • Managing Jobs

Module 3: Working with Datasets

  • Define Datasets
  • Dataset Locations
  • Creating and Copying Datasets
  • Controlling Access to Datasets
  • Listing Datasets
  • Updating Dataset Properties
  • Managing Datasets
  • Availability and Durability

Module 4: Working with Table Schemas

  • Specifying a Schema
  • Specifying Nested and Repeated Columns
  • Auto-Detecting Schemas
  • Modifying Table Schemas
  • Manually Changing Table Schemas

Module 5: Working with Tables

  • Creating and Using Tables
  • Managing Tables and Table Data
  • Exporting Table Data
  • Updating Table Data using DML

Module 6: Working with Partitioned Tables

  • What are Partitioned Tables?
  • Creating Ingestion-time Partitioned Tables
  • Creating Date/Time Partitioned Tables
  • Creating Integer Range Partitioned Tables
  • Managing and Querying Partitioned Tables
  • Using DML with Partitioned Tables

Module 7: Working with Clustered Tables

  • Define Clustered Tables
  • Creating and Using Clustered Tables
  • Querying Clustered Tables

Module 8: Working with Views

  • Introduction to Views
  • Creating Views
  • Controlling Access to Views
  • Creating Authorised Views
  • Listing Views
  • Updating View Properties
  • Managing Views

Module 9: Labeling BigQuery Resources

  • Adding Labels
  • Viewing Labels
  • Updating Labels
  • Filtering Using Labels
  • Deleting Labels

Module 10: Loading Data into BigQuery

  • Loading Data from Cloud Storage
  • Loading Data from a Local File
  • Streaming Data into BigQuery

Module 11: Querying BigQuery Data

  • Running Interactive and Batch Queries
  • Performing a Query Dry Run
  • Writing Query Results
  • Using Cached Results
  • Running Parameterised Queries
  • Querying Data Using a Wildcard Table
  • Saving and Sharing Queries
  • Scheduling Queries
  • Using the Query Plan Explanation
  • Using the BigQuery Connector for Excel

Module 12: Querying External Data Sources

  • Creating a Table Definition File
  • Querying Externally Partitioned Data
  • Federated Queries with Cloud SQL Data
  • Querying Cloud Bigtable and Storage Data
  • Querying Google Cloud Drive Data

Module 13: Controlling BigQuery Costs

  • Introduction to BigQuery Costs
  • Estimating Storage and Query Costs
  • Custom Cost Controls

Module 14: Securing BigQuery Resources

  • Access Controls
  • Encryption at Rest
  • Using Cloud DLP to Scan BigQuery Data
  • Protecting Data with Cloud KMS Keys
  • BigQuery Monitoring Using Stackdriver

Module 15: BigQuery API Basics

  • Authentication
  • Authorising API Requests
  • Batch Requests
  • Paging through Tables
  • API Performance Tips

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Google BigQuery Training​ Course Overview

BigQuery is Google’s fully managed, petabyte-scale, low-cost analytics data warehouse. It is an enterprise data warehouse that solves storing and querying massive datasets problem by enabling super-fast SQL queries using the processing power of Google’s Infrastructure. Delegates can access BigQuery by using command-line, by using Classic web UI or GCP console, or by making calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python.

This course teaches delegates about running and managing jobs, working with datasets, table schema, partitioned tables, clustered tables, and views. Delegates will acquire knowledge of how to add, view, update, filter, and delete labels in BigQuery resources. This course describes how to load data into BigQuery and querying BigQuery data. Delegates will learn how to query externally partitioned data, federated queries with cloud SQL data, query cloud big table data, cloud storage, and Google drive data. In addition, delegates will also gain an understanding of controlling BigQuery costs, securing BigQuery resources, monitoring, logging and BigQuery API.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Introduction to Google Cloud Security Course Outline

Module 1: Get Started with Google Cloud Security

  • Introduction to Google Cloud Security
  • Why Google Cloud Security?

Module 2: Understanding Identity in the Cloud

Identity and Access Management (IAM)

  • GCP Resource Hierarchy
  • Identity and Access Management (IAM)
  • Navigating IAM
  • Adding IAM Roles
  • Service Accounts
  • Custom Roles
  • Edit IAM Policy
  • IAM Best Practices

Module 3: Infrastructure Security

Securing GCP Network Infrastructure

  • Virtual Private Cloud (VPC)
  • Firewall Basics
  • Viewing Firewall Rules
  • Create Targeted Firewall Rule
  • Automate Firewalls Rules for Webserver
  • Limiting Exposure
  • Google Cloud VPN
  • Bastion Host
  • Interactive Serial Console
  • Routes
  • Private Google Access
  • Network IAM Roles

Securing your Operating System

  • OS Security Overview
  • Limit OS Access by Location
  • OS Updates
  • Securing Scaling Instance Groups
  • SSH Keys and Metadata
  • Securing SSH Access to Linux Instance
  • Linux Access and IAM Roles
  • Window Instance Access Management
  • OS Security Best Practices and Acceptable Use

Module 4: Data Security

Securing your Data

  • Securing Cloud Storage
  • Cloud Storage IAM Roles
  • Demonstrating Storage IAM Scopes
  • Access Control Lists (ACLs)
  • Signed URLs
  • Database Security

Module 5: Monitoring, Alerting, and Auditing

Monitoring GCP

  • Logging and Monitoring with Stackdriver
  • Viewing Stackdriver Logs
  • Exporting Logs
  • Monitoring and Alerts

Google Cloud Platform and Auditing

  • Compliance on Google Cloud Platform

Module 6: Encryption Essentials

GCP Encryption Options

  • Encryption on Google Cloud Platform
  • Key Management Service
  • Encryption Demonstration with KMS

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Introduction to Google Cloud Security ​Course Overview

This course will teach the core fundamentals necessary to secure your Google Cloud environment properly and manage who has access to what resources. This course focuses on identity and access management, securing GCP network infrastructure, securing operating system and data.

In IAM, delegates will learn about GCP resource hierarchy, navigating IAM, adding IAM roles, service account, custom roles, and edit IAM policy. They will acquire knowledge of how to secure GCP network infrastructure. Delegates will go through Virtual Private Cloud, firewall basics, and automate firewall rules for a web server, and network IAM roles. This course describes how to secure your operating system. Delegates will learn about securing scaling instance groups, SSH keys and metadata, securing SSH access to Linux instances and IAM roles.

This course describes cloud storage IAM roles, ACLs, and database security. Delegates will learn about GCP logging and monitoring with stackdriver. They will also acquire knowledge of encryption on Google Cloud Platform and key management services.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Google Search Appliance Fundamentals Course Outline

Module 1: Crawling and Serving Web Content

  • End-User Experience
  • How the Continuous Crawler Locates and Indexes Content?
  • Interpreting Crawl Diagnostics
  • Navigating the Administration Console
  • Creating, Managing, and Testing Front Ends with the Page Layout Helper
  • Creating Key Match and Related Queries
  • Implementing Query Expansion
  • Creating and Managing Collections


Module 2: One Box Modules and Indexing with Feeds

  • Onebox Modules Integrates with Enterprise Applications
  • Differentiate Between Internal and External Onebox Modules
  • Modifying XSLT Stylesheet for Onebox Results
  • Integrating the Onebox Module within a Front End
  • Feeds Integrate with Content Management Systems
  • Creating and Submitting Different Types of Feeds
  • Index Database Content
  • Basics of Connector Framework


Module 3: Reporting, Security, and Modifying XSLT Stylesheet

  • Crawl and Serve Security Functions
  • LDAP (Implement Directory Service) Integration
  • Implementing Forms Authentication Security
  • Running Reports
  • Query Request Parameters
  • XML Response Object
  • Upgrading Google Search Appliance Using Version Manager
  • Locating Google Search Appliance Documentation

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Google Search Appliance Fundamentals Course Overview

This course teaches delegates how to administrate and customise their Google Search Appliance. This course focuses on crawling and indexing documents from the web server and file system, using feeds and connectors to insert content into the index. Along with this, delegates will also learn how to implement one box modules, modify the presentation of search results, and implement security when serving results.

In this course, delegates will acquire knowledge of how the continuous crawler locates and indexes content. They will also learn about how to create, manage, and test front ends with the page layout helper. This course describes how Onebox modules integrate with enterprise applications and learn the difference between internal and external one box modules.

During this course, delegates will gain an understanding of how feeds integrate with content management systems. They will also learn how to create and submit different types of feeds: web, metadata and content. In this 2-day course, delegates will gain an understanding of how to implement directory service (LDAP) integration and forms authentication security.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Developing Applications with Google Cloud Platform Course Outline

The Course is based on how to develop applications with the Google Cloud Platform. The following modules are arranged to provide better knowledge of application development, Google Cloud SDKs, Data storage options, debugging, and Monitoring performance for application development.

Module 1: Application Development

  • Applications Development Overview
  • Design and Development of Application Components and Microservices
  • Understand Integration and Delivery of Applications
  • Re-architecting Applications for the Cloud

Module 2: Google Cloud Libraries and SDKs

  • Understand Google Cloud Client Libraries
  • Google Cloud and Firebase SDK
  • Google Cloud Libraries and SDKs on Linux Instance

Module 3: Data Storage for application data

  • Data Storage Overview
  • Use Cases for Data Storage Options

Module 4: Google Cloud Datastore

  • Google Cloud Datastore Overview
  • Understand Queries
  • Built-In and Composite Indexes
  • Understand Batch Operations
  • Transactions
  • Error Handling
  • Google Cloud DataFlow
  • Store Application Data in Cloud Datastore

Module 5: Google Cloud Storage 

  • Bucket and Object Operations Overview
  • Understand Consistency Model
  • Understand Error Handling
  • Naming Buckets and Objects
  • Performance Considerations
  • Understand Cross-Origin Resource Sharing (CORS)
  • Storing Files in Cloud Storage

Module 6: Authentication and Authorisation

  • Access Management
  • Understand Firebase Authentication
  • Understand Cloud Identity-Aware Proxy
  • Authenticate Users

Module 7: Integration Components of Applications

  • Understand Topics, Publishers, and Subscribers
  • Pull and Push Subscriptions Concept
  • Use Cases for Cloud Pub/Sub

Module 8: APIs with Application

  • Cloud Vision API Overview
  • Cloud Natural Language Processing API
  • Open API Deployment Configuration

Module 9: Google Cloud Functions

  • Google Cloud Functions Overview
  • Key Concepts of Google Cloud Functions
  • Use Cases of Google Cloud Functions
  • Development and Deployment of Functions
  • Logging, Error Reporting and Monitoring

Module 10: Deploying an Application

  • Overview
    • Google Cloud Cloud Build
    • Google Cloud Container Registry
    • Google Cloud Deployment Manager
  • Creating and Storing Container Images
  • Understand Deployment Configuration and Templates

Module 11: Execution Environments for Application

  • Execution Environments Overview
  • Google Compute Engine
  • Kubernetes Engine
  • App Engine Flexible Environment
  • Cloud Functions and Dataflow

Module 12: Debugging, Monitoring, and Tuning Performance

  • Google Stackdriver Overview
  • Stackdriver Debugger
  • Stackdriver Error Reporting
  • Stackdriver Logging

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Prerequisites

There are no formal prerequisites for this course. It would be great if Delegates have Basic knowledge of the Development of applications.

Audience 

This course is designed for anyone who wants to become a developer and develop new applications or redesign applications with Google Cloud Platform. GCP Technologies learners also included for this Course Audience.

Developing Applications with Google Cloud Platform Course Overview

The Google Cloud Platform provides Platform as a Service (PaaS), Infrastructure as a service (IaaS), and Serverless computing environments. Google cloud platform is allowed to develop and maintain applications. The app engine is a platform for developing and hosting web applications in Google-managed data centres. There are many alternative cloud platforms that provides managed and better tools for developing applications. But, Google provides future proof infrastructure and the services at high availability to develop applications.

In this 2-day course, delegates will get a complete understanding of how to develop applications with GCP and its essential terms. Delegates will learn how to design, develop and deploy applications. This course teaches how to use GCP services and pre-trained machine learning API to build scalable, secure, and intelligent cloud-native applications. Delegates will learn about data storage options for the application's data as well as they will gain knowledge of debugging, trace and monitor applications. In addition, they will also learn about deployment services and runtime environments, such as Google Container.

On course completion, delegates will be able to develop applications with GCP as well as manage deploying applications.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Google Cloud Compute Engine Course Outline

Get Started with GCP

  • Create VM Instance
  • Connecting to VM Instance
  • Managing Access to VM Instances
  • Adding Storage
  • Backing Up Persistent Disk Snapshots

Building and Managing Custom Images

  • Creating, Deleting, and Depreciate Custom Images
  • Sharing Images, Snapshots, and Disks Across Projects
  • Setting Up Trusted Images Policies
  • Building Custom Operating Systems
  • Exporting a Custom Image to Cloud Storage
  • Importing Custom Image and VM Instance
  • Managing Instances

Creating and Managing Groups of Instances

  • Managed Instance Groups
  • Create Groups of Unmanaged instances

Networking

  • Virtual Private Cloud
  • Configure IP Address
  • Using Protocol Forwarding
  • Creating a PTR Record for a VM Instances

Deploying Containers and Scaling your Application

  • Deploying Containers on VM and Managed Instance Groups
  • Configuring Options to Run Container
  • Cloud CDN
  • Load Balancing
  • Autoscaling Groups of Instances

Monitoring Activity

  • Viewing Audit Logs
  • Migrating from Activity Logs to Audit Logs
  • Viewing Activity Logs and Usage Reports
  • Labelling Resources
  • Granting Access to Compute Engine Resources

Migrating VMs to Compute Engine

  • Overview
  • Migrating VMs Using Migrating for Compute Engine

Advanced VM Configurations

  • Enabling Nested Virtualisation for VM Instance
  • Encrypting Disks with Customer Supplied and Managed Encryption Keys
  • Sending Email from an Instance
  • Automated Image Build with Jenkins, Packer, and Kubernetes

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Google Cloud Compute Engine Course Overview

Compute Engine allow to create and run virtual machines on Google Cloud Infrastructure. It offers scalable performance, and value that enables you to launch large compute clusters quickly on Google’s infrastructure. Delegates can run thousands of virtual CPUs on a system that has been designed to be fast and to offer strong consistency of performance.

This course teaches delegates how to create and connect VM instances. Delegates will learn how to create, delete, and depreciate custom images. They will also learn about sharing images, snapshots, and disks across projects. This course describes how to export and import custom images and VM instances. Delegates will get an understanding of how to create and manage groups of instances.

During this Google Cloud Compute Engine training, delegates will learn how to create a PTR record for a VM instance. They will also acquire knowledge of how to deploy containers, scale application, monitor activity, label resources, and grant access to compute engine resources. In this 2-day course, delegates will learn how to migrate VMs and enable nested virtualisation for VM instances.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Storage Training Course Outline

This course will cover the following modules to deliver complete knowledge of Google Cloud Storage. These modules are arranged by our IT professionals to provide a technical understanding of Cloud storage.

Module 1: Introduction to Google Cloud Storage (GCS)

  • What is Google Cloud Storage?
  • Key Terms
  • Feature and Benefits of GCS

Module 2: Understand Concepts of Google Cloud Storage

  • Storage Classes
  • Bucket Locations
  • Bucket and Object Naming
  • Domain-Named Bucket
  • Encryption in Google Cloud Storage
  • Authentication in Google Cloud Storage

Module 3: Implement Buckets in Google Cloud Storage

  • Create Storage Buckets
  • Listing of Buckets
  • Change Class of Bucket
  • Operations of Buckets in GCS
    • Moving Buckets
    • Renaming Buckets
    • Deleting Buckets

Module 4: Objects in Google Cloud Storage

  • Upload Objects in Cloud Storage Bucket
  • Listing Objects Stored in Cloud Storage Bucket
  • Downloading Objects
  • Operations of Objects
    • Renaming Objects
    • Copying Objects
    • Moving Objects
  • Change Storage Classes of Objects
  • Object Metadata Operation in Google Cloud Storage
    • Viewing Object Metadata
    • Editing Object Metadata 
  • Composing Objects
  • Understand Streaming Transfers
  • Deleting Objects

Module 5: Controlling Access for Google Cloud Storage

  • Controlling Access Overview
  • Managing IAM Permissions
  • Using Bucket Level Access
  • Creating and Managing Access Control Lists
  • Understand Sharing and Collaboration

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Prerequisites

There are no formal prerequisites for this course but it would be great If delegates have a basic understanding of Google Cloud Platform as web services.

Audience

This course is designed for IT professionals and Google Cloud Technology learner. Individuals who wants to understand the Cloud Data Storage to maintain and manage by his specific role can also attend this course.

Google Cloud Storage Training​ Course Overview

Google Cloud Storage provides managed cloud storage at any time with high availability. It is used for serving website content, storing data for archival and disaster recovery or distributing large data objects. It is also integrated storage into apps within a single unified API. This is Designed for secure and durable storage. Google Cloud Storage Included Access data instantly from any storage class. From this Google Cloud Technology, User can easily store data in the cloud to get secure and highly available object storage at the lowest latency. Apart from Cloud Storage Product, Google Cloud Platform also provides more storage products such as Persistent Disk, Cloud File store, cloud storage for firebase, data transfer services and drive enterprise.

This 1-day course will teach about Cloud Storage provided by Google Cloud Platform. Delegates will learn about key terms of Google Cloud Storage. This course provides a better knowledge of Storage classes and buckets. Delegates will get an understanding of access control of the Google Cloud Platform to use the storage services of GCP. For security perspective, the topic of encryption is also included in this course. From the encryption options and keys concepts, delegates will get an understanding of the security strategies, and they can entirely use encryption options. Beside this, delegates will get familiarised with the concept of authentication. Learners will also gain knowledge of how to use Google Cloud Platform user interface.

After the course completion, delegates will be able to create cloud storage and manage accordingly. They will also work with Google Cloud Buckets and objects to get the skill for Google Cloud Storage.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Developing with Google App Engine Training Course Outline

This course will provide accurate and essential knowledge of Google App Engine. This course is created to provide knowledge of Google App Engine to delegates. The following modules are arranged in a way that will teach about the working process of Google App Engine from basic to advanced concepts.

Module 1: Google App Engine Overview

  • Introduction to Google App Engine
  • Architecture and Runtime
  • Features of Google App Engine
  • Use Cases Models 
  • Understand Workflow
  • Writing and Deploying a Simple Application

Module 2: Web Requests in Google App Engine

  • Request Handling in Google App Engine
  • Rendering Templates
  • Understand Static Resources
  • Using Web Frameworks

Module 3: Datastore in Google App Engine

  • Understand Datastore in Google Engine
  • BigTable Overview
  • Understand BigTable Operations
  • Data Stored Strategies
  • Scaling BigTable to BigData

Module 4: Queries, Indexes, and Transactions

  • Understand Queries
  • Query API and Query Object
  • Transactions

Module 5: Google App Engine Services

  • Google App Engine Services
  • Memcache
  • Multi-tenancy
  • Blobs
  • User in Datastore

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Prerequisites

There are no formal prerequisites for this course. However, a basic knowledge of programming languages would be helpful.

Audience                                                                                 

This course is designed for IT professionals and Google technologies Learner.

Developing with Google App Engine Training​ Course Overview

The App Engine is a fully managed, serverless platform to develop and host web applications at scale. Google App Engine supports various popular languages, libraries, and a framework for developing applications. Based on demand, Google App Engine provision servers and scale app instances. It provides two environments – standard and flexible. There is no need to maintain or provision a server for development as it provides built-in services as a requirement.

This 1-day course will teach about Google App Engine and its essential terms. Delegates will learn about how to integrate with other Google products as well as establish a workflow. Delegates will gain an understanding of App Engine on Windows as well as app engine services. Delegates will acquire knowledge of how to work with images, style sheets, and other static files. They will get familiarised with Python and App Engine. In addition, delegates will work with HTML variables and HTML Templates.

During this course, delegates will learn about implementing App Engine Storage. Delegates will also learn about request handlers and instances, DataStore Entities, Datastore Queries, and managing the request logs. On course completion, delegates will be able to develop scalable web and mobile applications on Google’s infrastructure and manage applications on Google App Engine.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Dataflow Training Course Outline

Module 1: Get Started with Google Cloud Dataflow

  • Introduction to Google Cloud Dataflow
  • Google Dataflow Concepts
  • Installing the SDK
  • Creating a Pipeline
  • Specifying Execution Parameters
  • Deploying a Pipeline
  • Using Monitoring UI and Command-Line Interface
  • Stackdriver Monitoring
  • Logging Pipeline Message

Module 2: Troubleshooting and Updating Pipeline

  • Troubleshooting and Debugging
  • Common Guidance
  • Updating an Existing Pipeline
  • Stopping a Running Pipeline

Module 3: Creating and Running Templates

  • Google Provided Templates
    • Get Started
    • Streaming Templates
    • Batch Templates
    • Utility Templates
  • Creating and Running Templates
  • Migrating from MapReduce
  • Migrating from SDK 1.x for Java

Module 4: Configuring Networking and Using Cloud Pub/Sub Seek

  • Specifying Networks
  • Configuring Internet Access and Firewall Rules
  • Using Cloud Pub/Sub Seek
  • Using Flexible Resource Scheduling

Module 5: Creating Cloud Dataflow SQL Jobs

  • Introduction to Cloud Dataflow SQL
  • Streaming Pipeline Basics
  • Using Cloud Dataflow SQL
  • Data Sources and Destinations

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Google Cloud Dataflow Training Course Overview

Cloud Dataflow is a fully managed service for transforming data in stream and batch modes with equal reliability. This course teaches delegates how to deploy batch and streaming data processing pipelines using Dataflow, including directions for using service features. The Apache Beam SDK is an open-source programming model enabling delegates to develop batch and streaming pipelines. They create their pipelines with an Apache Beam program and then run them on the Dataflow service.

In this 1-day course, delegates will acquire knowledge of how to create and deploy pipeline. They will also learn how to troubleshoot, update an existing pipeline, and stop running pipeline. This course describes Google provided templates and how to create and run templates. Delegates will get an understanding of how to configure internet access and firewall rules. In addition, they will also learn how to use cloud pub/sub seek with cloud dataflow and create a cloud dataflow SQL jobs.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Spanner Training Course Outline

Module 1: Get Started with Google Cloud Spanner

  • Introduction to Google Cloud Spanner
  • Google Cloud Spanner Concepts
    • Instances
    • Schemas
    • Transactions
    • Performance Tuning
    • Data Manipulation Language (DML)
    • Commit Timestamps
    • Replication
    • True Time and External Consistency
    • Access Control
    • Audit Logging
  • Create and Manage Instances

Module 2: Modifying Data

  • Using the GCP Console
  • Using DML, Mutations, and GCloud
  • Applying IAM Roles
  • Managing Long-Running Operations

Module 3: Monitoring Instance

  • With the GCP Console
  • With Stack Driver
  • Viewing Query Statistics

Module 4: Using Cloud Spanner

  • Using Cloud Spanner in a Virtual Machines
  • Cloud Spanner with Cloud Function
  • Cloud Dataflow Connector

Module 5: Importing and Exporting Databases

  • Exporting from Cloud Spanner to Avro
  • Importing Cloud Spanner Avro Files
  • Importing and Exporting Data in CSV Format
  • Working with STRUCT Objects

Module 6: Integrations

  • With Other GCP Services
  • With Hibernate ORM
  • With Spring Data

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Prerequisites

There are no formal prerequisites for this course but it would be great If delegates have a basic understanding of Google Cloud Platform as web services.

Audience                                                                                 

This course is designed for IT professionals and Google technologies Learner.

Google Cloud Spanner Training ​Course Overview

Cloud Spanner is scalable, enterprise-grade, globally-distributed, and strongly consistent database service built for the cloud to combine the benefits of relational database structure with non-relational horizontal scale. The standard way to manipulate data in relational databases is the SQL data manipulation language (DML). Cloud Spanner is designed to support global online transaction processing deployment, SQL semantic, highly available horizontal scaling and transactional consistency. The transaction can be applied across rows, columns, table, and database within a spanner universe. Delegates can control the replication and placement of data using automatic multi-site replication and failover.

This course teaches delegates about Google cloud spanner concepts: instances, schemas, transactions, performance tuning, data manipulation language (DML), and replication etc. They will acquire knowledge of how to create, manage, and monitor instances. Delegates will get an understanding of how to modify the data and manage a long-time running operation.

During this course, delegates learn how to use cloud spanner in a virtual machine instance and cloud spanner with cloud functions. In addition, delegates will also learn how to use the cloud spanner with cloud dataflow connector. On course completion, delegates will be able to import and export databases and work with STRUCT objects.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Firestore Training Course Outline

This outline focuses on providing a complete essential component of Google Cloud Firestore. The following modules are arranged to get a better understanding of this technology.

Module 1: Introduction to Firestore

  • Google Cloud Firestore Overview
  • Working Overview
  • Key Capabilities
  • Implementation of Firestore Overview

Module 2: Concepts of Firestore

  • Data Model
  • Data Types and Index Types
  • SDKs and Client Libraries
  • Structured Data and Add Data
  • Transactions
  • Operations Cloud Firestore

Module 3: Secure and Validate data

  • Secure and Validate Data
  • Understand Security Rules
  • Conditions for Security Rules 
  • Troubleshooting Rules
  • Testing of Security Rules
  • Secure Query Data

Module 4: Cloud Firestore Solution Overview

  • Introduction to Cloud Firestore Solution
  • Aggregation Queries 
  • Distributed Counters
  • Understand Data Access
  • Understand Sharded Timestamps

Module 5: Cloud Firestore Integrations

  • Understand Cloud Firestore REST API
  • Cloud Functions

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Prerequisites                                                                                      

There are no formal prerequisites for this course.

Audience

This course is designed for everyone who wants to gain knowledge of Google Cloud Firestore mode. This course is also beneficial for Google Cloud Platform technology learners.

Google Cloud Firestore Training Course Overview

Google Cloud Firestore is a fully managed database service by Google on the Google Cloud Platform. It is a highly scalable database service. While the cloud Firestore interface has almost the same database features as traditional databases and NoSQL databases, but still it differs from them by its relationships between data object. It also provides a facility to analytic data and transaction data. Google Cloud Firestore is built upon Google’s Bigtable and Megastore technology. Cloud Firestore is a NoSQL documents database built for automatic scaling, high performance, and ease of application development. It also offers transactions that affect multiple databases and scale automatically to handle loads. Cloud Firestore is a highly-scalable NoSQL database for the application as well as it automatically handles sharding and replication, providing high availability and durability of a database that scales automatically to handle applications’ load.

This 1-day course will provide a complete knowledge of Cloud Datastore and its essential terms. Delegates will become familiarised with all the concepts of Google Cloud Firestore. From this course, delegates will get an understanding of entities, properties and keys as well as learn more about database queries. Within this course, delegates will also gain knowledge of indexes and transactions terms of cloud firestore in datastore mode.

During this course, delegates will get an understanding of how to handle errors. On course completion, delegates will become familiarised with the functionality of Google cloud datastore mode. In addition, they will be able to use features of the datastore mode interface accurately.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Big Data and Machine Learning with Google Cloud Platform Course Outline

Module 1: Introduction to Google Cloud Platform

  • Google Platform Fundamentals Overview
  • Google Cloud Platform Big Data Products

Module 2: Compute and Storage Fundamentals

  • CPUs on Demand (Compute Engine)
  • Global Filesystem (Cloud Storage)
  • CloudShell
  • Lab: Set Up an Ingest Transform Publish Data Processing Pipeline

Module 3: Data Analytics on the Cloud

  • Stepping-Stones to the Cloud
  • Cloud SQL: Your SQL Database on the Cloud
  • Lab: Importing Data into CloudSQL and Running Queries
  • Spark on Dataproc
  • Lab: Machine Learning Recommendations with Spark on Dataproc

Module 4: Scaling Data Analysis

  • Fast Random Access
  • Datalab
  • BigQuery
  • Lab: Build a Machine Learning Dataset

Module 5: Machine Learning

  • Machine Learning with TensorFlow
  • Lab: Carry out ML with TensorFlow
  • Pre-built Models for Common Needs
  • Lab: Employ ML APIs

Module 6: Data Processing Architectures

  • Message-Oriented Architectures with Pub/Sub
  • Creating Pipelines with Dataflow
  • Reference Architecture for Real-Time and Batch Data Processing

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Prerequisites

There are no prerequisites for this course.

Audience

This course is for IT Professionals who want to learn about Google Cloud Technologies.

Big Data and Machine Learning with Google Cloud Platform​ Course Overview

This course introduces delegates to the big data and machine learning capabilities of Google Cloud Platform. It provides an overview of the Google Cloud Platform and then dives into the data processing capabilities. Delegates will learn about the Google cloud platform big data products and will acquire knowledge of how to compute and store. They will learn how to set up ingest transform publish data processing pipeline.

In this 1-day course, delegates will get an understanding of how to import data into cloud SQL and run queries and machine learning recommendations with Spark on Dataproc. Delegates will get familiarised with fast random access, Datalab, and BigQuery. They will learn how to build machine learning datasets and machine learning with TensorFlow.

At the end of this course, delegates will learn about data processing architectures: message-oriented architectures with Pub/Sub and creating pipelines with dataflow.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

Show moredown

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

Google Cloud Bigtable Training​ Course Outline

This course is based on the Google Cloud Bigtable and its essentials terms to acquire the skills of designing and managing the database. Technically, this outline is designed to provide the best knowledge of the design database. So let's start with this course and acquire excellent skills to work on Google Cloud Bigtable.

Module 1: Overview of Google Cloud Bigtable

  • Introduction to Google Cloud Bigtable
  • Key Advantages
  • Understand Storage Model and Architecture
  • Load Balancing
  • Data Types
  • Cloud Bigtable Performance

Module 2: Google Cloud Bigtable Resources Overview

  • Instances and Properties
  • Cluster in Google Cloud Bigtable
  • Nodes in Google Cloud Bigtable

Module 3: Designing Database with Google Cloud Bigtable

  • Designing Schema
  • Row Keys and Types
  • Reverse Domain Names
  • String Identifiers
  • Timestamps
  • Domain Names
  • Sequential Numeric IDs
  • Frequently Updated Identifiers
  • Hashed Values

Module 4: Creating and Managing Instances

  • Creating Instance
  • Creating and Managing Labels
  • Operation on Instance
    • Modifying
    • Monitoring
    • Deleting

Module 5: Managing Data in Google Cloud Bigtable

  • Data Overview
  • Importing and Exporting Data
  • Managing Tables
  • Cloud Bigtables Writes and Writing Data

Module 6: Troubleshooting and Logging

  • Key Visualiser Overview
  • Key Visualiser Scans
  • Audit Logging

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Prerequisites

There are no formal prerequisites for this course. It would be great if the delegates have a basic knowledge of Google Cloud platform.

Audience

This course is designed for IT professionals and Google Cloud technologies learner.

Google Cloud Bigtable Training​ Course Overview

The Google Cloud Bigtable is Google’s NoSQL and fully managed database service. It is responsible for managing the database and handling the configuration as well as tuning of the database. This technology sparsely populates a table that can scale to billions of rows and thousands of columns, enabling to store terabytes or even petabytes of data. Cloud Bigtable is perfect for storing large amounts of single-keyed data with very low latency. It performs read and write throughput at low latency and is an ideal data source for MapReduce operations. It exposed to applications through multiple client libraries. Cloud Bigtable integrates easily with popular big data tools such as Hadoop, Cloud, Dataflow, and Cloud Dataproc.

This 1-day course will provide a comprehensive knowledge of Google Cloud Bigtable and its essential terms. Delegates will learn about how to design a database with Google cloud Bigtable schema and storing time-series data. From this course, they will get an understanding of how to create and manage instances. For manage instances, delegates will acquire the skills of data storage selections, handling labels, modifying and monitoring strategies as well as managing data. Delegates will also get a better understanding of garbage data collections, the configuration of garbage collection and understand the concept of storing sequential numbers in timestamps. The troubleshooting for resolving the real-time issues is also included in this course.

On course completion, delegates will be able to design a database with Google Cloud Bigtable schema and manage the database for an application as well as troubleshooting with key Visualiser.

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  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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Not sure which course to choose?

Speak to a training expert for advice if you are unsure of what course is right for you. Give us a call on +64 800 446148 or Enquire.

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Frequently asked questions

FAQ's

Google Cloud Platform is a suite of Cloud Computing services that runs the infrastructure services. It has key services such as compute, storage and databases, networking, Big Data, Cloud AI, Management Tools, Identity and Security, Internet of Things (IoT), API Platform, etc.
The following are the various components of the Cloud Platform: • Google Computer Engine • Google Cloud Container Engine • Google Cloud App Engine • Google Cloud Storage • Google Cloud Dataflow • Google BigQuery Service • Google Cloud Job Discovery • Google Cloud Endpoints • Google Cloud Test Lab • Google Cloud Machine learning Engine
Google Cloud Hosting provides high availability services at the lowest latency. The following are key points to choose Google Cloud for hosting. • Benefits of live migration of the machines • Enhanced performance and execution • Commitment to constant development and expansion • The private network provides efficiency and maximum time • Strong control and security of the cloud platform • Inbuilt redundant backups ensure data integrity and reliability
The Knowledge Academy is the Leading global training provider in the world for Google Cloud Training.
The price for Google Cloud Training certification in New Zealand starts from NZD1495.

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