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GCP Cost Optimization: A Guide to Maximizing Cloud Savings

Originally Published June, 2024 · Last Updated July, 2024
GCP cost optimization

GCP provides businesses of all sizes with a wide range of services, from simple website hosting to complex machine learning algorithms and Big Data analysis. 

Google Cloud is easy to set up and run based on your needs. However, as your business grows, managing GCP becomes more complicated, requiring additional services and resources. This calls for a well-defined cloud management system. 

Google Cloud Platform (GCP) optimization can help you maximize your return on cloud investment. 

This blog will share insights on effective strategies for optimizing your Google Cloud Platform. We’ll also discuss tools that can help you build a well-rounded cloud cost optimization strategy to maximize your cloud investment and avoid waste. 

What is GCP cost optimization?

Today, many businesses use Google Cloud Platform (GCP) because of its wide range of services, ease of scalability, and the flexibility it offers. Relying on these services will require managing cloud spend to avoid waste—like idle resources, storage redundancy, unoptimized storage, or underutilized services.

GCP cost optimization helps your business get the most value from your cloud investments by strategically managing resources within Google Cloud without sacrificing performance or functionality. Unoptimized cloud spending can lead to profit margin erosion or limit the ability to invest in further business growth.

In the recent State of FinOps 2024 Report, reducing waste has emerged as the top priority for organizations across all spending tiers. 

Image Source The State of FinOps 2024 Report

But why does cloud cost optimization matter? 

  • Organizations can save money by eliminating idle resource usage and working with the most cost-effective GCP service that suits their needs.
  • Optimizing costs leads to a more efficient cloud environment where it’s easy to identify underutilized resources and relocate them for better performance.
  • GCP optimization leads to financial transparency, where businesses have a clear idea of their cloud spending patterns. This leads to better budgeting and forecasting.

GCP native tools for managing cloud costs

GCP has built-in tools to help you manage your cloud costs. These tools will help you track, analyze, and optimize your spending. With granular insights, an easy-to-use interface, and automation enabled, these tools can be an asset to cloud management. 

Here are some of the GCP native tools and how they can help you:

Google Cloud Billing Reports

Google Cloud Billing Reports generates detailed, user-configurable reports with charts and tables that summarize your GCP usage costs. 

You can use the detailed reports to determine which cloud service you spend the most on, how costs per service compare over time, which projects cost the most, and many other financial metrics that can help you with better investment planning.

Google Cloud Billing Reports provide a clear picture of your overall spending and can help you identify areas for potential savings.

Image Source: Google Cloud Billing Reports

Google Cloud Pricing Calculator

Google Cloud Pricing Calculator allows users to estimate the cost of the intended GCP usage before deploying cloud resources. 

Organizations using BigQuery can especially benefit from this tool, as it helps determine the most effective storage locations and methods for their data.

Google Cloud pricing calculator is useful for budgeting and ensuring efficient resource allocation.

Google Cloud Cost Table

Google Cloud Cost Table showcases all GCP products and their pricing structures.

Using this service, businesses can better understand their cloud cost savings. For example, they can compare the costs using usage-based credits versus the savings from those credits. (Or, they can better understand negotiated savings in the case of custom pricing contracts.)

This tool is a valuable resource for understanding the cost implications of different service tiers and configurations.

Image Source: Google Cloud Cost Table

Google Cloud CUD Analysis Report

The Google Cloud CUD Analysis Report is designed for customers who use committed use discounts (CUDs). It analyzes the effectiveness, coverage, and utilization of your CUDs, helping to determine if they’re delivering the intended cost savings.

Organizations can use CUD Analysis Reports to determine how much they save through their CUDs and whether they are fully utilizing their commitments. The report also helps users quantify the savings opportunity of purchasing additional CUDs wherever possible. 

While these insights are valuable, it’s important to note that they still require manual oversight. ProsperOps removes this manual element, autonomously monitoring cloud spend and managing discount instruments to help your organization increase your Effective Savings Rate (ESR) while minimizing financial risk.

Google Cloud Recommender

Use the Google Cloud Recommender to analyze your GCP cloud resource usage and view recommendations for optimizing cloud spending. These recommendations are actionable across various aspects of your GCP environment, such as suggesting right-sizing options for VMs, turning off idle resources, storage updates, and more. When integrated with the GCP FinOps Hub, these insights help you optimize resource utilization and reduce costs significantly.

Image Source: GCP FinOps Hub

Choosing the right GCP pricing model for cost optimization

It is important to leverage the right pricing model to optimize costs and align your cloud spending with your specific needs. GCP offers various pricing models to cater to users’ different patterns and budgets:

Free tier

The free trial and free tier pricing model are best for beginners experimenting with GCP. It offers users limited resources for a specific period, allowing them to experiment with GCP functionalities without any upfront costs. The free tier pricing model includes several services, including Compute Engine, Google Cloud Storage, and BigQuery, but it has limitations on usage quotas.

Pay-as-you-go pricing

The pay-as-you-go pricing model allows users to only pay for services they are provisioning, making it an ideal model for unpredictable workloads and short-term projects. It’s one of the most flexible pricing models offered by GCP. Better yet, it gives room for scalability, allowing users to adjust their resources based on their needs.

Committed use discounts (CUDs) [long-term pricing]

Committed use discounts (CUDs) require a long-term resource commitment. They offer significant savings compared to the on-demand rates of the pay-as-you-go model. Resource-based CUDs require you to commit to a minimum amount of usage in a particular region for a machine series, and are well-suited for predictable and steady-state usage. Additionally, Spend based CUDs allow for more flexibility by letting you commit to a specific dollar amount of spending across various services, ideal for dynamic usage patterns.

Sustained use discounts (SUDs) [long-term pricing]

Sustained use discounts (SUDs) are another pricing model that offers significant savings for GCP users. SUDs offer a maximum discount of 20% or 30% depending on  the resource and machine type, and are automatically applied to instances that run for at least 25% of the month. However, SUDs can only apply if those resources aren’t receiving any other discounts.

Spot VMs

The Spot VMs are more of an instance type than a pricing model. They are best suited for fault-tolerant or batch-tolerant workloads. Spot VMs are provisioned with unused GCP compute capacity, allowing users to acquire them at significantly lower prices (60%–91% discounts) than standard VMs.

The downside is that spot VMs often get interrupted when needed to meet higher-priority workloads. For this reason, Spot VMs are suitable for tasks that tolerate occasional disruptions, such as batch processing or data analysis jobs. You can get significant savings with Spot VMs for your cloud infrastructure strategy without compromising performance for flexible workloads.

Best practices for managing and optimizing GCP costs

Google Cloud Platform is recognized for the flexibility it offers. But that can only be leveraged if you know how to manage associated costs effectively to avoid waste. The trick is to adopt the right approach without compromising performance.

Here are some best practices that will help you take control of your cloud costs:

1. Leverage cloud cost optimization tools

The cloud cost optimization tools, either the native ones or the third-party platforms, can be a big asset. Google Cloud cost optimization tools offer a deeper level of control and automation. These tools go beyond basic reporting, delivering granular analysis, actionable recommendations, autonomous management, and advanced cost-saving features to users. Make sure you are well-versed in the platform’s capabilities to make the most out of your cloud cost management strategy.

2. Utilize long-term pricing

GCP’s long-term pricing models like CUDs and SUDs reward customers with greater discounts for longer-term commitments (CUDs) and longer-term consistent resource usage (SUDs). You can learn more about the details on long-term pricing from the official Google Cloud documentation

3. Set budgets, alerts, and quotas

You should always practice proactive cost management. Set budgets and configure alerts to monitor your spending closely and prevent cost overruns. You need to define the spending limits for your GCP projects and services. Once these thresholds are established in the console, GCP will notify you to take necessary action when you approach your limits. 

By establishing quotas, you can safeguard your business against accidental overruns and define them for specific projects, services, and even individual users. Additionally, implementing budgets helps control your spending and avoid unnecessary surprises on your GCP bill.

4. Rightsize your resources

Rightsize your resources by choosing the most appropriate VM sizes, Google Cloud storage options, and network configurations based on your workload requirements. 

Avoid overprovisioning resources to reduce cloud waste. When you analyze your resource usage patterns, you identify opportunities to scale down resources during low-demand periods. This helps you optimize your spending. 

5. Leverage auto-start/auto-stop features

Take control of idle and underutilized resources. GCP has an auto-start and auto-stop feature for specific services that allow you to turn off resources when they’re not needed. A good example is development environments that you can turn off on weekends or off-hours. Doing this eliminates unnecessary idle time and significantly reduces overall spending.

6. Consider using Spot VMs

When you have workloads with flexible needs, consider using Spot VMs. They offer a cost-effective solution by leveraging unused GCP compute capacity, allowing users to acquire the resources at a significantly lower price than standard VMs. 

7. Utilize autoscaling

You should always avoid paying for resources you don’t need, and autoscaling can help with that. It automatically adjusts resource allocation based on customizable usage metrics. This ensures you have enough resources to handle peak traffic while automatically scaling down during low-demand periods. 

Eliminating manual provisioning and de-provisioning prevents unnecessary idle resource costs and helps you optimize your spending based on fluctuating workloads.

8. Regularly review your resource utilization

Your cloud costs can rise if left unchecked. So, review your resource utilization regularly to identify and eliminate waste spending on underutilized resources. Additionally, it can help you analyze resource usage patterns to identify VMs or storage that run below capacity. 

When you terminate or scale down these idle resources, you can free up the budget for other needs and ensure you’re paying for resources you’re actively using. You can also enjoy better forecasting, easier budgeting, and more effective planning for long-term pricing models.

9. Focus on non-Compute optimizations too

The State of FinOps 2024 Report revealed that most businesses focus primarily on compute spend, suggesting they miss key opportunities for cost savings in other areas. Therefore, it is advisable to also invest optimization efforts in crucial areas such as storage and database resources, depending on specific needs.

Image Source The State of FinOps 2024 Report

Optimize your GCP costs seamlessly with ProsperOps

There are several native tools within GCP that can help businesses manage cloud costs and find opportunities for savings. However, these tools still require manual oversight and management, which busy FinOps teams may lack the resources to handle.

This is where a solution like ProsperOps comes in. 

ProsperOps is an automated FinOps platform that manages a portfolio of discount instruments and dynamically adapts your commitments to usage changes in real time. Our solutions simplify cloud cost management by automating complex and time-consuming optimization and reporting tasks.

ProsperOps operates silently in the background 24/7 without manual intervention, enabling greater cloud savings, reduced financial risk, and seamless integration into your operations.

Schedule a free demo today to learn how ProsperOps can help you achieve significant savings with simplified, autonomous cloud cost optimization.

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