GCP - Cloud Digital Leader - Part 0

By Marco Ludeña

Published in GCP

December 13, 2022

3 min read

GCP has more than 200 services.

this exam expects knowledge of 40+ Services
Exam test your decision making habilities:
- Which service do you choose in which situation?
- This course is designed to help you make these choices
- Our Goal: Help

What is GCP ?

One of the TOP 3 cloud service providers.
Provides a number of services ( 200+ )
Reliable , secure and highly performant.(Infrastructure that powers 8 famous services with over 1 billion users: Gmail , Google Search, Youtube, etc).
The cleanest cloud : Net carbon-neutral cloud (electricity used matched 100% with renewable energy).

GCP - Cloud Digital Leader (Around 40 services)

Section 1: Getting started- GCP

Create our google cloud account: Requirements :
```
1. Gmail account
2. A debit or credit card  
Steps:
1. Login into your google account 
2. Go to cloud.google.com
```
Section 2: Regions and Zones in GCP (Conceptos generales de cloud)
```
1. Challenges in any application:
  - High Latency
  - Low availability
2. GCP provides 20+ regions around the world .
  - Region: Specific geographical location to host your resourcess .
    - Advantages:
      - High Availability
      - Low Latency
      - Global Footprint
      - Adhere to goverment regulations
   - Zones: Each region have multiple zones .
       - Each Region has three or more zones
       - Increased availability and fault tolerance within same region.
       - Each zone has one or more discrete clusters
         - Cluster: Distinct physical infrastructure that is housed in a data center.
```

Section 3 : Compute Engine , Instance Groups & Load Balancing

- GCE - Google Compute Engine -GCE (Lab01: Creating your first Virtual Machine in GCP)
- Web servers , GCE VM IP Addresses, Custom Images (Lab02: Installing HTTP Webserver on GCE Virtual Machine)
- Preemptible VMs
- Load Balancers

Section 4 Managed Services- IAAS , PAAS and SAAS in GCP (Conceptos generales de cloud)

- IAAS , PASAS
- Containers and Container Orchestation
- Serverless
- SAAS
- Shared Model Responsability.

Section 5 Exploring GCP Compute Services

- Google APP Engine (GAE): Environment standard and flexible
- Lab (GAE)
- GAE- App , Services and Versions.
- GAE - Service Categories- Scenarios
- Google Kubernetes Engine (GKE)
- Lab: Creating a GKE Cluster
- GKE : Create a deployment and a Service
- GKE: Scaling Deployments and Resizing Node Pools
- GKE: Kubernetes Journey - Autoscaling
- GKE: Delete GKE Service , Deployment and Cluster.
- Google Cloud Functions V2
- Google Cloud Run and Anthos V2
- GCP Conpute services

Section 6: Block , File and Object Storage in GCP

- Block and File Storage in GCP
- Cloud Storage
- Transfering data to cloud - online , Transfer Service and Transfer

Section 7: Databases in Google Cloud

- 
- 
- OLTP Relational Databases in Google Cloud - Cloud SQL & Cloud Spanner
- Lab: Playing with Cloud SQL
- Lab: Playing with Cloud Spanner v2
- OLAP Relational Database in Google Cloud- BigQuery
- NoSql Databases in Google Cloud- Firestore , Datastore and BigTable
- Lab : Playing with Firestore
- In memory Database in Google Cloud - MemoryStore

Section 8: Cloud IAM

- Roles 
- Service Accounts
- Lab: Playing with Service Accounts

Section 11: Devops

- CI/CD Global Concepts
- SRE
-

Section 12: Building Loosely Coupled Applications with Cloud Pub Sub

- Asyncronus Communication (Global Concept) 
- Cloud Pub Sub
- Lab : Playing with Cloud Pub Sub v2
- DataFlow

Section 13: Google Cloud Architecture for Cloud Digital Leader

- Big Data Flow Batch Ingest
- Streaming Data
- IOT
- Data lakes
- Exploring API Management- Apigee, Endpoints , API Gateway
- Introduction to Artificial Intelligence & Machine Learning 
- ML in Google Cloud  - Pre trained Models
- ML in Google Cloud - Custom Models
- Faster ML in Google Cloud - TPUs

Section 14: Digital Transformation with Google Cloud

- Infraestructure Modernization with GCP
- Application Modernization with GCP
- Business Platform with GCP

INTERESTING

Section 15: Cost Management in GCP

- Consumption based vs Fixed price Pricing Models
- GCP Pricing Calculator
- GCP Cost Management

Database Categories:

There are several categories of databases:

Relational(OLTP and OLAP) , Document , KeyValue , Graph , In Memory among others.
Choosing type of database for your use case is not easy . A few factors:
- Do you want a fixed schema?
- Do you want flexibility in defining and changing your schema? (schemaless)
- What level of transaction properties do you need? (atomicity and consistency).
- What kind of latency do you want ?(seconds , milliseconds or microseconds)
- How many transactions do you expect?(Hundreds or thousands or millions of transactions per second )
- How much data will be stored ? (Mbs or GBs or TBs or PBs)
- And a lot more …

Relational Database:

This was the only option until a decade back!
Most popular(or unpopular) type of databases
Predefined schema with tables and relationships
Very strong transactional capabilities (In a simple transactions we can make many updates , is all or nothing ) . Good for example for banking.
Used for :
- OLTP (Online transaction Processing) and OLAP (Online Analytics Processing)

Relational Database -OLTP (Online Transaction Processing:

Applications where large number of users make large number of small transactions: (Small data reads , updates and deletes)
Use cases: Most traditional applications, ERP , CRM , e-commerce , banking ,applications.
Popular databases (MySQL , Oracle , SQL Server, etc)

Recommended Google Managed Services:

Cloud SQL : Supports PostgreSQL , MySQL and SQL Server for regional relational databases (upto a few TBs - 64 if is dedicated or 3 if is shared)
Cloud Spanner : Unlimited scale(multiple PBs) and 99.9999% availability for global applications with horizontal scaling.

Recommended AWS Managed Services:

Recommended Azure Managed Services:

Lab: Playing with Cloud SQL

Enable the API for the first time
Create the instance, the database and table and populate it .
Execute some sql queries inside the cloud shell
Exploring monitorization (CPU utilization , Storage usage , Memory usage)
Checking the machine type , storage type (SS ord HDD) , Storage Capacity , Conectivity (private IP or Public IP) , Automated Backups(Window of time and the storage option could be regional or multiregional , also define the number of automated backups are stored at a time ). By default is enabled the point-in-time recovery , that allows you to recover data from a specific time
Lab: Playing with Cloud Spanner
Enable the Cloud Spanner API
Configurations :

Could be regional or multiregional
Allocate compute capacity: (Units(could be node (1K unit processing) or unit processing ).

Once the instance has been created , we could create the database . Here we could add a DDL template Example
CREATE TABLE Users( UserId INT64 NOT NULL, Username STRING(1024) ) PRIMARY KEY (UserId);

Now choose the table , and can create Indexes or execute execute query

You can use dbeaver to interact with cloud Spanner (https://cloud.google.com/blog/topics/developers-practitioners/exploring-cloud-spanner-data-dbeaver/)
Import/Export , we have many options:

Dataflow jobs (import/export)
Using Cloud Storage to export

Relational Database -OLAP (Online Analytics Processing):

Applications allowing users to analyze petabytes of data
- Examples: Reporting applications, Data ware houses , Business intelligence applications , Analytics systems
- Sample application: Decide insurance premiums analyzing data from last hundred years.
- Data is consolidated from multiple (transactional) databases