Notes from my Google Cloud Associate Cloud Engineer — Section 1

I passed the Associate Cloud Engineer exam. I successfully cleared this exam after 2 months of lecture and practices. In this article I want to share with you the first part of my notes that I took during the preparation steps.

The exam needs a lot of preparation. Before diving in the notes I recommend these useful resources :

• Architecting with Google Cloud Platform Specialization.

Architecting with Google Cloud Platform | Coursera

• Google Cloud Platform Associate Cloud Engineer Practice Test.

Google Cloud Platform Associate Cloud Engineer Practice Test

• Google Kubernetes Engine

Getting Started with Google Kubernetes Engine | Coursera

Billing

• You can create budgets and attach them to project or a billing account, then define alert based on percentage.
• You can export billing information to BigQuery(dataSet) or Cloud Storage (bucket).
• Billing is accumulated from bottom to top ( billing accumulates all the resource consumption of a specific project).

Pricing calculator

BigQuery

• On-demand (better) : storage pricing & query pricing
• Flat-rate : storage pricing

Storage options

Cloud bigTable

• Size Petabyte
• Key value API ( you can have only one index..)
• No-Sql database
• For flat large data, analytics and big data application use ( IoT , machine learning ..)
• Manage scalability
• Heavy read/write query
• Low latency
• Single key lookup
• Structured

Cloud Datastore

• Size Terabyte
• AppEngine storage option
• kind -> Entity -> properties
• Persistant HashMap
• Structured
• NoSql database for application
• with transactions and SQL-like queries (GQL)
• Multi-regional / Regional
• You can have more than one index / you can set specific column as index in specific row.

Cloud Storage

• Size Petabyte +
• Like file in file system
• Structured & Unstructured
• Immutable object
• The only database that have unstructured objects
• Multi-regional / Regional
• The long-term storage location for data
• They are immutable, and new versions overwrite old unless you turn on versioning.

Cloud Spanner

• Size Petabyte
• The best of Relationnel and non-relationnel database
• Transactional / horizontale scalability
• Sql
• Entreprise grade security
• Multi-regional / Regional

Cloud Sql

• Size Terabyte
• Relationnel database
• Transactional
• More faster than cloud spanner
• Sql for application
• Scope is only regional ( you can’t make replicas within different region , but it is possible in different zone )
• Mysql / posture database

BigQuery

• Size Petabyte
• Sql
• Analytics target
• Warehouse
• ServerLess
• Scope global

2 — Load Balancing :

• Load balancing is not a hardware. It is some rules that you apply to traffic based on criteria like capacity and distance etc.
• Load balancer receives traffic and redirect it to different instances (the closet group of instance. If the closet doesn’t have enough capacity , it will redirect it to the next closet that have enough capacity)
• Load balancer as a server is much more flexible than a hardware load balancer

HTTP(S) Load Balancing

HTTP(s) Load Balancing

• If the selected backend Service don’t have the capacity to make a load balancing ( CPU utilization, request per seconds..) , the target proxy will choose an other back-end service to do the job.
• Cross-region http(s) load balancing will make the load balancing to the closet region which have enough capacity to support the charge
• Cross-content load balancing will make the load balancing to the region based onURL & header.
• Each back-end service have a collection of instance groups.

Network Load balancing (regional non proxied load balancer)

• the traffic is forwarding to a target pool that choose which health check it will perform on the instances.
• The advantage of the managed instances is the autoscaler, depending on traffic coming to the target pool you can spin up / spin down the instances and this changement will be recognized by the target pool
• Each project can have up a 50 target pool.

Best practices of Load Balancing :

• Make a firewall rules to restrict the traffic only for a specific LoadBalancer in the GCP network.
• Disabling external ip adresses.

Autoscaling :

Set an autoscaler per managed instance group to scale-up or scale-down based on traffic load ( zonal managed instance group / regional managed instance group) . The autoscaler make an horizontal scalability.

Autoscaling policies :

• Average CPU utilization : maintain cpu utilization among managed instance group to the target utilization ( for example it shouldn’t exceed or be very less from 70% ) .If you exceed 70% you should scale up instances
• You can use Stackdriver’s metrics.
• The autoscaler allows multiple policies in a one instance group.
• It collect instance based in policies in order to have the maximum number of instances.
• You can define custom metrics in Stackdriver and use them as base for the autoscaler

I hope you have found the above resources useful for the exam. Please let me know if I should add anything else to this list.