Best Practices for Optimizing your Cloud Costs - on Google Cloud Platform (Compute Instances)

One of the greatest benefits that you will get if you are running your IT infrastructure on cloud, is being able to scale up and down to meet demand and reduce the avoidable operational expenditures. And that’s especially true when you’re experiencing unexpected fluctuations in customer  or organizational demand 

Following these best practices will help you rightsize your cloud costs to the needs of your business, so you can get through these challenging, unpredictable times.

1. Billing and Cost Management: 

A. The path to predictable cloud costs:-  

Google Cloud's cost management tools provide the visibility, accountability, control, and intelligence to your organization, so that you can scale your business in the cloud with confidence. Tailored to meet the needs of organizations of all sizes, these tools help to reduce the complexity and increase the predictability of your cloud costs.

B. Visibility is power:- 

Gain visibility into your current Infrastructure and forecasted costs, identify cost drivers, and leverage key insights to confidently plan, manage, and optimize your costs with built-in reporting and customizable dashboards.

C. Drive accountability, spend more responsibly:- 

Using Google Cloud platform you can promote a culture of accountability for costs across your organization and better understand your return on cloud investments with flexible options.  The Platform enables you to organize resources and allocate costs to departments and teams using google cloud admin console . 

D. Take control of your costs:- 

Control your costs and reduce the risk of overspending with strong financial governance policies and permissions that make it easy to control who can do the spending and view costs across your organization.

2. Pay for the Compute you Need: 

A. Schedule VMs to auto start and stop:- The benefit of a platform like Compute Engine on google cloud platform is that you only pay for the compute resources that you use.

Most of the cases if we monitor then we will see that the production systems tend to run 24/7; however, VMs in development, test or personal environments tend to only be used during business hours, and turning them off can save you a lot of money.

For example, a VM- Virtual machine that runs for 10 hours per day, Monday through Friday costs 75% less to run per month compared to leaving it running. To get started, we have a serverless solution that we developed to help you automate and manage automated VM shutdown at scale.

B. Rightsize VMs:- On Google Cloud platform you can already resize significant savings by creating the custom machine types with the right amount of CPU and RAM to meet your organizational needs. But workload requirements can change over time. Instances that were once optimized may now be servicing fewer users and traffic. To help, our rightsizing recommendations can show you how to effectively downsize your machine type based on changes in vCPU and RAM usage.

These rightsizing recommendations for your instance’s machine type (or managed instance group) are generated using system metrics gathered by Cloud Monitoring tools. 

C. Leverage preemptible VMs:- Google Cloud  Preemptible VMs are highly affordable compute instances that live up to 24 hours and that are up to almost 80% cheaper than regular instances. Google Cloud Preemptible VMs are a great fit for fault-tolerant workloads such as

1. big data, 

2. Genomics,

3. media transcoding,

4. financial modelling and simulation.

You can also use a mixed environment of regular and preemptible instances to finish compute-intensive workloads faster and cost-effectively, by setting up a specialized managed instance group.