7 Best Practices for GCP Cloud Cost Management
Manage & monitor your GCP costs with these 7 best practices and optimize your resource allocation for significant cost savings.
March 31, 2023
by Adarsh Rai
8 mins Read
Table of Contents
- Understanding Google Cloud Platform (GCP) Costs
- Using Pricing Calculator for accurate estimates
- 7 Best Practices to Manage GCP Cloud Costs
- Use Long-Term Commitment Discounts (CUDs and SUDs)
- Cloud Monitoring & Cloud Logging
- Use preemptible VMs for non-critical workloads
- Set up Budget Alerts to monitor spending
- Use Auto-Scaling to optimize resource allocation
- Use right-sizing to allocate optimal resources
- Use Cost Breakdown reports for detailed cost analysis
- Conclusion
Are you looking to harness the power of Google Cloud Platform (GCP) to enhance your business operations? With its vast array of services, GCP can be a game-changer for businesses of all sizes. However, with the convenience of cloud computing comes the challenge of managing costs effectively. Without proper planning and oversight, costs can quickly escalate, leading to budget overruns and financial instability.
That’s where effective cost management strategies come into play. In this article, we’ll be discussing the seven best practices for GCP cloud cost management. By following these best practices, businesses can avoid surprises in their bills and ensure they are getting the most value out of their GCP investments.
Understanding Google Cloud Platform (GCP) Costs
To effectively manage GCP costs, it’s important to first understand how GCP pricing works. GCP pricing is based on a consumption-based model, where businesses pay for the resources they use. The pricing structure can be complex, and it’s essential to have a clear understanding of the key components to manage costs effectively.
The three primary components of GCP pricing are storage, network, and data.
- Storage pricing is based on the amount of data stored in GCP, while network pricing is based on the amount of data transferred over the internet.
- Data pricing is based on the specific GCP services used, such as compute, storage, or BigQuery.
By understanding these key components, businesses can identify areas where they may be overspending and optimize their usage.
Using Pricing Calculator for accurate estimates
It’s also essential to be aware of the different GCP costs that make up pricing. These costs can include compute resources, networking, storage, and Big Data analytics, among others. With so many different services and pricing models, it can be challenging to keep track of costs effectively.
The GCP Pricing Calculator provides businesses with a comprehensive estimate of their potential costs, allowing them to plan effectively and optimize their cloud usage. By using tools like the GCP Pricing Calculator, businesses can make projections for essential services and cut down on underutilized instances to get the most value from their investment.
Organizations should also consider a cloud cost audit every month to determine where they’re spending the most and uncover opportunities for cost optimization.
7 Best Practices to Manage GCP Cloud Costs
In this section, we’ll explore seven best practices for GCP cloud cost management, including strategies for using long-term commitments, resource optimization & allocation, and more. By implementing these best practices, you can gain greater control over your GCP costs and ensure that you’re getting the most out of your cloud investment.
Use Long-Term Commitment Discounts (CUDs and SUDs)
Long-term commitment discounts are a great way to optimize your cloud costs on GCP. By committing to use a specific resource for an extended period, GCP offers significant discounts. There are two types of long-term commitment discounts: Committed Use Discounts (CUDs) and Sustained Use Discounts (SUDs).
Sustained Use Discounts (SUDs): Sustained Use Discounts are available to users who run specific types of Compute Engine and Cloud SQL instances continuously for a month. With SUDs, the more you use a specific resource, the greater the discount you receive. The discount increases automatically as your usage increases, and you can save up to 30% on your costs.
- For instance, let’s say you run a specific Compute Engine instance for an entire month. At the end of the month, you will receive a discount based on the percentage of time you used that instance. If you used it for 70% of the month, you would receive a 10% discount. If you used it for 100% of the month, you would receive a 30% discount. SUDs are an excellent way to optimize your cloud costs without committing to a specific resource.
Committed Use Discounts (CUDs): Committed Use Discounts are available to users who commit to use a specific amount of resources for a one-or-three-year period. By committing to use a specific amount of resources for an extended period, GCP offers significant discounts on those resources. You can save up to 55% with CUDs.
- For instance, let’s say you commit to using a specific Compute Engine instance for a three-year period. By committing to use that instance for three years, you will receive a significant discount on that instance for the entire period, regardless of usage. CUDs are an excellent way to optimize your cloud costs if you know you will be using a specific resource for an extended period.
Cloud Monitoring & Cloud Logging
In order to optimize costs in GCP, it is important to monitor aand optimize resource usage. This can be achieved through the use of GCP tools like Cloud Monitoring and Cloud Logging.
Cloud Monitoring – Cloud Monitoring is a tool that provides insight into the performance, uptime, and overall health of your GCP resources. By using this tool, you can monitor and analyze the usage of your GCP resources in real-time. Cloud Monitoring also provides an alerting mechanism that can notify you when certain thresholds are met.
Ways to use Cloud Monitoring:
- Cloud Monitoring can help you identify underutilized resources, so you can turn them off and save costs.
- By setting up alerts for when a resource exceeds a certain threshold, you can take action to prevent unexpected costs.
- Use Cloud Monitoring to create dashboards that display the usage and performance of your GCP resources.
- Set up alerts for when certain metrics exceed a certain threshold.
- Use Cloud Monitoring to analyze and optimize the performance of your GCP resources.
Cloud Logging – Cloud Logging is a tool that provides centralized logging for your GCP resources. By using Cloud Logging, you can view, search, and analyze your log data in real-time. Cloud Logging also provides an alerting mechanism that can notify you when certain events occur.
Ways to use Cloud Logging
- Cloud Logging can help you identify and troubleshoot issues in your GCP resources.
- By analyzing your log data, you can identify trends and usage patterns, and make informed decisions to optimize your costs.
- Use Cloud Logging to view and analyze your log data in real-time.
- Set up alerts for when certain events occur.
- Use Cloud Logging to troubleshoot issues in your GCP resources.
Use preemptible VMs for non-critical workloads
Preemptible VMs are Google Cloud’s short-lived and low-cost virtual machines that are perfect for running workloads that can tolerate interruptions. Since they are much cheaper than regular VMs, preemptible instances are a great way to reduce your overall compute costs. However, there is a catch: Google can shut down your instance at any time and without warning, so they should only be used for workloads that can be interrupted without causing any significant issues.
They are ideal for batch processing jobs, video encoding, rendering, and other non-critical workloads that are designed to be fault-tolerant. By using preemptible VMs, you can take advantage of Google Cloud’s spare capacity while reducing your overall compute costs. You can also use them to run workloads that require a lot of processing power, such as machine learning training jobs, without having to pay the full price for regular VMs.
How to use Preemptible VMs?
- To use preemptible VMs, simply select the “Preemptible” option when creating a new instance. You can also use managed instance groups to automatically scale up and down your preemptible instances based on demand. Just keep in mind that preemptible instances have a maximum lifespan of 24 hours, so make sure your workloads are designed to handle interruptions.
Set up Budget Alerts to monitor spending
Setting up budget alerts is a critical practice in GCP cloud cost management, allowing you to set a budget for your cloud usage and receive notifications when your spending approaches or exceeds that budget. This can help you avoid any unwanted surprises on your bill and keep your cloud costs under control.
How to setup Budget Alerts in GCP?
- To set up budget alerts in GCP, you can use the GCP Console, Cloud SDK, or the Cloud Billing API. You can set a budget for each billing account, project, or billing subaccount. You can also create multiple budgets to monitor different types of spending.
- Once you have set up your budget, GCP will automatically send email notifications when your spending reaches certain thresholds that you define. You can set alerts for when you have used a percentage of your budget, when you have exceeded a specific amount, or when there has been a significant increase in spending.
Use Auto-Scaling to optimize resource allocation
Auto-scaling is a powerful tool that can help optimize resource allocation in GCP, while also reducing costs. By automatically adjusting the number of compute resources based on the current demand, auto-scaling ensures that the resources are used efficiently and effectively, without over-provisioning. This means that you only pay for the resources you actually need, and not for the ones that are sitting idle.
How to enable Auto-Scaling in GCP?
To enable auto-scaling in GCP, users can use managed instance groups (MIGs) and configure them to automatically adjust the number of instances based on demand. This can be done using a variety of metrics, such as CPU utilization, network traffic, or requests per second. GCP also offers auto-scaling policies that allow users to set specific rules for how resources should be scaled based on the defined metrics.
- Auto-scaling is particularly useful in scenarios where there is a lot of variability in the demand for computing resources. For example, an e-commerce site may experience a spike in traffic during a holiday season, or a video streaming service may see increased demand during the weekends. By using auto-scaling, you can easily handle these spikes in demand without having to provision additional resources manually.
Use right-sizing to allocate optimal resources
Right-sizing is the process of matching an application’s resource requirements with the resources allocated to it. Essentially, it means ensuring that your application is not over- or under-provisioned, which can result in unnecessary costs or performance issues. Right-sizing your resources can be achieved by monitoring your application’s resource usage and scaling them accordingly.
By using right-sizing, you can optimize your resource usage and ensure that you are only paying for what you need. GCP offers several tools for right-sizing, such as the Instance Right Sizing recommendations in the Compute Engine, which analyzes VM usage and suggests a better machine type that provides better performance and lower costs.
- Suppose your application is running on a Compute Engine virtual machine. Initially, you might have started with a machine type that was too small for your application’s needs, resulting in poor performance.
- However, if you upgraded to a larger machine type, you might have been paying more than you needed to for the resources that your application was using.
- In this case, Instance Right Sizing can provide recommendations for a better-suited machine type based on your application’s resource usage, allowing you to optimize your resources and reduce costs.
Use Cost Breakdown reports for detailed cost analysis
Using cost breakdown reports is a powerful way to gain insight into how much you are spending on GCP resources. With cost breakdown reports, you can see how much each of your services and resources is costing you, as well as track your usage over time. This information can help you make informed decisions about where to allocate your resources and identify areas where you can optimize your costs.
How to use Cost Breakdown Reports?
To use cost breakdown reports, you need to enable billing export to Google Cloud Storage. Once enabled, GCP will automatically export your billing data to a bucket in your Google Cloud Storage account. You can then use tools like BigQuery or Data Studio to query and analyze the data in the exported reports.
In addition to identifying underutilized resources, cost breakdown reports can help you monitor trends and forecast future costs.
Conclusion
In conclusion, managing cloud costs is an essential aspect of any business, and GCP offers many tools and best practices to help users optimize their cloud spending. By implementing the seven best practices we discussed, users can significantly reduce their cloud bills and allocate their resources effectively. It is important to remember that GCP cost optimization is an ongoing process and requires continuous monitoring and optimization.
If you are interested in learning more about GCP pricing, visit our GCP Pricing page to get an idea of pricing and potential savings.
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