Cloud Infrastructure Building with Google Compute Engine

Google Compute Engine is the infrastructure as a Service (IAAS) component of the global Google Cloud Platform, using which you can build a cloud infrastructure. It allows users to launch virtual machines on demand. The best part about Google Compute Engine is customization (you can customize your server requirement according to the organizational needs). You can launch VMs from the standard images or custom images that you create. You can access Google Compute Engine via the Developer Console, RESTful API or command-line interface (CLI).

Example:  Let us consider a Company currently using an Application for 20 users. To run that application flawlessly, the appropriate configuration would be: 8 GB RAM, 2 Vcpu, 1TB HDD. If after 2 months 15 more users join, in that case, organization can increase the server specifications.  

Benefits of Compute Engine

Leading Performance:

Compute Engine's tool-set and workflow support enables scaling from single instances to global, load-balanced cloud computing. Virtual Machine Booting time is the fastest compared to other Cloud services and the high-performance consistency is definitely a Fantastic solution for any business.

Auto Cost Cutting:

Google uses the Pay-as-you-Use Model and Bills in second level increments, so users only have to pay for the compute time they used. Google will provide discounts for long-running workloads with no up-front commitments.

Predefined Virtual Machine:

Compute engine offers predefined VM Configurations to fulfill every need from Micro instances ( Static Website Hosting ) to instances with up to 160Vcpus and 3.75TB memory. For extra performance training and running machine learning models, you may leverage Cloud TPU or GPU.

Persistent Disk:

Google Compute Engine is providing network storage upto 64 TB in both HDD and SSD formats

If a VM instance somehow crashes, then we can retrieve all the data from the persistent disk and restore again to another disk. You can also take snapshots of your persistent disks and create new persistent disks from that snapshot only.

How to Create an  Instance:

Step 1: Go to the Cloud SQL Instances page in the Google Cloud Platform Console.

Step 2: Click Create an instance and name your instance.

Step 3: Select your region And zone.

Step 4: We need to select Asia South Mumbai (for India) and any of the zones available.

Step 5: Now we need to select the Machine Type.  

Note: The Number of memory and the number of cores always maintain a 1:6 ratio maximum

             Ex: For 2 Number of VCPUs the maximum memory allocation will be 12

Step 6: select number of GPU  ( Graphics Processing Unit )  

Step 7: Select The operating system  ( it can be LINUX or WINDOWS )  

Note: IF LINUX  we need minimum 10 GB Storage.

                IF WINDOWS we need minimum 50 GB Storage.

Step 8: Select  Database SQL Server from the Application Images Panel.

Note:

OS images are images of certain user’s OS, can be bootable to different infrastructures.

Custom images are the pre-defined OS, can be bootable to different infrastructures.

Snapshots are images or backup of data from persistent disk and can be bootable on the same infrastructure only.

Step 9: Select  The Existing Disk according to requirement.

Step 10: Select Save.   

An instance “instance-python-test” has been created.

  Other Options:

1. Linux & Windows support                                       4. Commitment Saving

2. Batch Processing                                                    5. Containers

3. Compliance and Security