Google Cloud Certification Overview

Course Resources

• The course focuses on Google Cloud Certification resources.

Google Cloud Certification

• Different certification levels exist (Associate and Professional)
• Required experience varies by level
• Associate level requires 6+ months experience on Google Cloud
• Professional level requires 3+ years industry experience including 1+ years on Google Cloud
• User certification completion of Applied Digital Skills training course and G Suite Essentials quest
• There are different roles, including Cloud Engineer, Cloud Architect and Cloud Developer.
• Security (Networking), Developer/DevOps related roles also available.

Why Certify?

• Milestones for learning
• Keeping skills up-to-date
• Career advancement
• Higher market value
• Self-motivation

Scenario - Bowtie Inc.

• Bowtie Inc. is a global manufacturing company headquartered in Montreal, Canada
• Approximately 300 employees, 100 in Sales
• The company has offices/stores in Montreal, London, and Los Angeles
• It has in-store staff, IT, marketing, manufacturing, finance, sales people, managers, sewers.
• The company uses on-premises hardware for its operations
• The company has global inventory updated upon sales and new stock
• Its POS systems are in each store/office location, and its HQ in Montreal has all the infrastructure connected and backed up to a tape system.
• The company is currently facing limitations with its existing technology

Current Issues

• Legacy on-premises hardware is out of warranty
• Performance issues in POS systems across stores
• Lack of high availability (HA) and scalability
• Slow tape backups, which are costly and offsite

Favourable Results

• Reliable and stable connection between stores
• Fast and cost-effective cloud backup
• Deploying into new regions quickly when needed
• Scalable and low cost infrastructure
• Automation, avoiding manual intervention

Cloud Computing

• The delivery of a shared pool of on-demand computing services over the public internet.
• Provisioning and releasing resources rapidly.
• Minimal management effort from the service provider.

The 5 Characteristics of Cloud

• On-demand self-service
• Broad network access
• Resource pooling
• Rapid elasticity
• Measured service

Benefits of Cloud

• Agility: Flexibility for provisioning resources; faster innovation
• Cost: Pay-as-you-go; trade capital expenditure for variable expense
• Speed: Resources on demand; scriptable infrastructure; easier global disaster recovery; high availability
• Security: Always up-to-date; physical security; encryption at rest and in transit; compliance

Cloud Deployment Models

• Public Cloud: One public cloud
• Multi-Cloud: Two or more public clouds
• Private Cloud: On-premise cloud
• Hybrid Cloud: Private cloud + public cloud
• Hybrid Environment: On-premise data center + public cloud

Cloud Service Models

• Infrastructure as a Service (IaaS)
• Platform as a Service (PaaS)
• Software as a Service (SaaS)

Compute Engine

• Virtual Machines (VMs) called instances
• Choose deployment region and zone
• Users decide the operating system and software
• Use public or private images
• Manage multiple instances with instance groups
• Scalable with autoscaling
• Can use Google Cloud Storage
• Use SSH to connect directly
• IaaS model

Google Kubernetes Engine (GKE)

• Container orchestration system for deploying, scaling, and managing containers
• Built on open-source Kubernetes
• Integrates with Compute Engine instances as nodes in a cluster.
• A cluster is a group of nodes or Compute Engine instances
• CaaS (Container as a Service) model

App Engine

• Fully managed, serverless platform
• Develop and host web apps
• Code or containers
• Support for Python, Java, .NET, etc.
• Auto-scaling
• Versions for rollback and migrating
• Connect to external storage
• Standard and Flexible environments

Cloud Functions

• Serverless execution environment for building and connecting functions to events.
• Simple, single-purpose functions attached to events.
• Code executes in a fully managed environment
• No need to provision infrastructure

Storage & Databases

• Options include Cloud Storage and various databases.

Cloud Storage

• Consistent, scalable, large capacity, highly durable object storage (not file or block)
• Worldwide accessibility and locations
• Usage for: data files, text files, pictures, and videos
• Suitable for content delivery, big data sets, and backups
• Different storage classes (Standard, Nearline, Coldline, Archive)

Cloud SQL

• Fully managed relational database service
• Low Latency, transactional, relational
• MySQL, PostgreSQL, SQL Server
• Replication and Read Replicas
• On-demand and automatic backups
• 30TB storage capacity, storage increase automatic

Cloud Spanner

• Fully managed, relational database service
• Strongly consistent and horizontally scalable
• Supports schemas, ACID transactions, SQL queries
• Globally distributed, handles replicas and sharding
• Synchronous data replication
• Automatic scaling and redundancy
• High Availability (Up to 99.999%).

Network Services

• Virtual Private Cloud (VPC)
• Firewalls and Routes
• Load Balancing
• Cloud DNS
• Advanced Networking (VPN, Direct Interconnect, Carrier Peering)

Resource Hierarchy

• Resources are organized hierarchically like a parent/child relationship
• IAM manages the access control policies.

Cloud Billing

• Defining cost center owners
• Tracking Google Cost
• Using Sub-accounts for resellers
• Linking to a payment profile

Limits and Quotas

• Hard limits on Google Cloud resource usage
• Rate Quota - resets after a specified time
• Allocation Quota - must be released explicitly

Cloud IAM

• Managing access control policies and configurations
• Using Principle of Least Privilege (grant appropriate permissions)

Cloud Interconnect

• Low-latency, highly available connection between on-premise and GCP VPC networks
• Provides direct access to internal IP addresses without internet transit.
• Dedicated connection, not encrypted but expensive.

Deployment Manager

• Configuration definition for resources
• Defines the structure, including a resource section.
• Components include name, type and properties.
• Templates are used to automate deployment.

Load Balancing

• Distributes user traffic across multiple instances
• Provides a single point of entry with multiple backends
• Fully distributed and software defined.

Instance Groups and Instance Templates

• A collection of VM instances that you manage as a single entity
• Use in conjunction with Instance Templates to create new VMs, and used to update VMs.

Containers

• Consistent, efficient, and standardized method to run applications

Kubernetes

• Orchestration platform for containers to automate, schedule, and run workloads on a cluster.

Kubernetes Components

• API server
• Kube scheduler
• Kube controller manager
• Cloud controller manager
• etcd

Node Pools

• Group of nodes within a cluster that share same configurations
• Enable use of custom node pools for different resources
• Manually or automatically upgraded.

Cluster Types

• Single-zone
• Multi-zonal
• Regional

Cluster Upgrades

• Control plane upgrades before the nodes
• Upgrades are accomplished one control plane at a time.

Surge Upgrades

• Allows you to control the number of nodes upgraded at a time.

Pods and Object Management

• Entities that represent the state of a GKE cluster.
• Pod concepts include containers, shared storage, and shared networking.

Manifest File

• Configuration file required to create and run Kubernetes objects.
• Includes pod spec, with containers, images, ports, etc. to provide the desired state.

Kubernetes Services

• Persistent single IP
• Internal/External load balancing
• Scaling.

Service Types

• ClusterIP
• NodePort
• Load Balancer
• ExternalName
• Headless
• Uses labels and selectors for identifying pods and instances.

Ingress for GKE

• Provides external access to the cluster.
• Used to handle traffic to multiple pods.
• Defines rules for routing.

Health Checks

• How to define when a service is up and down

SSL Certificates

• Option to use Google managed or self-managed certificates for SSL.

GKE Storage Options

• Storage options available for Kubernetes, including databases, object storage, block storage, and NAS.

Docker Storage

• Basic storage unit
• Decoupling of storage from container
• File system storage
• Volumes
• Shared storage for containers

Kubernetes Storage Abstractions

• Basic storage unit
• Used for separating storage from container and pod

Persistent Volume Access Modes

• ReadWriteOnce, ReadOnlyMany, ReadWriteMany
• Storage types available for pods
• HA and zone specifics

Cloud VPN

• Connects your on-premise network to your GCP VPC network
• IPsec tunnel over the public internet for private access.
• Two types of Cloud VPN (Classic, HA)

Cloud Interconnect

• Dedicated physical connection for low latency and high speed
• Doesn't traverse the public internet
• Suitable for high traffic

CDN Interconnect

• Connection with third party CDN providers to direct traffic
• Lower egress costs

App Engine

• Fully managed serverless environment
• Supports multiple languages and frameworks
• Includes standard and flexible environments
• Supports scaling

Kubernetes Workloads

• Deploys, manages, and updates replicas of an app
• Supports configuration for containerized applications

Big Data Services

• Tools and services available to handle massive data sets
• Enables real-time data ingestion and analysis.

Machine Learning

• Functionality that enables software to perform tasks without explicit programming or rules.
• Recognizes patterns in datasets.
• Can be used for image analysis, text analysis, speech recognition, and translation.

Operations Suite

• Monitoring logging error reporter debugger trace profiler components that integrate with Google Cloud.

Cloud Monitoring

• Collects and displays metrics and dashboards to allow you to visualize applications.
• Works with Log, Error, Debug, and Trace to perform comprehensive diagnostics.

Cloud Logging

-Central logging repository for various cloud resources

• Includes GCP and non GCP resources.

Error Reporting

• Counts, analyzes, and aggregates errors occurring within the Google Cloud environment.
• Ensures you are alerted in case of an error.
• Supports various languages.

Debugger

• Debug a running application in real time with no latency
• Capture stack snapshot
• Allows for remote error reporting.

Trace

• Helps understand how long it takes an application to complete requests.
• Gathers latency data.
• Works with various platforms like Google Cloud.

Profiler

• Helps to monitor resource consumption by applications to detect and resolve performance issues.
• Collects data about CPU usage and memory allocation.