Why Does GCP Cost Optimization Matter?

Google Cloud Platform is packed with services and setups to fit your unique needs, but all that flexibility makes its pricing a bit tricky. Your costs can shift based on usage, duration, and advanced features like enhanced security. But do not stress–let’s simplify it together!

We’ll guide you through understanding GCP pricing, choosing the right payment plan, and using the best tools to keep your costs in check.

How Much Does GCP Cost?

To get a handle on your GCP costs, it's crucial to grasp how Google Cloud pricing works. GCP’s consumption-based pricing sounds straightforward—pay for what you use. But in reality, managing those costs can feel like juggling too many things at once. Economize helps you stay ahead of the game, by giving you the tools to optimize your usage and maximize your budget, all while keeping things simple and clear.

How to Calculate your GCP Costs?

Our GCP Pricing Calculator is here to make things easy for you. Just plug in your instance type, region, and usage duration, and you’ll get a clear picture of what your costs will be. It’s the perfect tool for keeping your GCP spending in check.

Google Cloud Pricing Models

GCP offers three key pricing models to accommodate varying user requirements: Free Tier, On-Demand, and Long-Term.

GCP Free Tier: Usage and Limits

The GCP Free Tier is a great way to start exploring Google Cloud services without spending a dime. It gives you limited monthly usage on key services like Compute Engine and Cloud Storage. Want to know the specifics? Let’s take a look at some of the free tier limits.

• Compute Engine: 1 non-preemptible e2-micro VM instance per month
• Cloud Storage: 5 GB months of regional storage per month
• Google Kubernetes Engine: No management fee for one Autopilot or Zonal cluster per billing account
• Firestore: 1 GB storage per project
• Cloud Logging: Free monthly logging allotment
• BigQuery: 1 TB of querying and 10 GB of storage per month
• App Engine: 28 hours per day of "F" instances

Remember, if you go beyond the Free Tier limits, charges will apply based on GCP’s regular pricing.

On-Demand Pricing

This flexible model lets users pay for resources as and when they use them. Users can scale up or down depending on their needs and only pay for the services consumed. This option is ideal for organizations with unpredictable workloads or who need to quickly adapt their resources.

For the General-Purpose Machine Types (C3):

• Predefined Memory: $3.32515 / GB month
• Spot Pricing for vCPUs: $2.25278 / vCPU month
• Spot Pricing for Memory: $0.30149 / GB month
• Predefined vCPUs: $24.80686 / vCPU month

For the C3 Standard Machine Types:

• c3-standard-4: $0.208808 per hour
• c3-standard-8: $0.417616 per hour
• c3-standard-22: $1.148444 per hour
• c3-standard-44: $2.296888 per hour

Long-Term Pricing

If your resource usage is predictable, Long-Term Pricing options like Committed Use (CUD) and Sustained Use Discounts (SUD) are ideal. You commit to using specific resources for one or three years and, in return, enjoy reduced pricing.

Committed Use Discounts (CUDs)

Committed Use Discounts (CUDs) allow you to commit to a set amount of resources for a specific period of time, in return for a discounted rate.

For example, if you need to run a virtual machine for a year, you can commit to a certain number of CPU and memory resources, and receive a discount for doing so. Discounts range from 20% to 77% for 1 and 3-year commitments respectively.

License pricing with CUDs:

• SLES: 1-2 vCPUs at 77% (1-year) and 79% (3-year) CUD
• SLES for SAP: Any number of vCPUs at 59% (1-year) and 63% (3-year) CUD
• RHEL and RHEL for SAP: Any number of vCPUs at 20% (1-year) and 24% (3-year) CUD

Sustained Use Discounts (SUD)

Sustained Use Discounts (SUD) on the other hand, are automatically applied when you use a virtual machine for a certain amount of time each day, over a 30-day period.

The longer you use the machine, the more you save, with discounts ranging from 10% to 90%. This pricing model is ideal for businesses that have predictable resource requirements and need to run virtual machines for extended periods of time.

• n1-standard-1 VM: 0%–25% of the month at $0.0475/hour, 25%–50% at $0.0380/hour, 50%–75% at $0.0285/hour, and 75%–100% at $0.0190/hour
• c2-standard-4 VM: 0%–25% of the month at $0.2088/hour, 25%–50% at $0.1811/hour, 50%–75% at $0.1530/hour, and 75%–100% at $0.1252/hour

Understanding these pricing components and models allows businesses to spot areas of potential overspending and optimize their GCP usage.

1. GCP Spot Virtual Machines (VMs)

Google Cloud Platform Spot VMs are a cost-effective option for running workloads that can tolerate interruptions. hile they’re cheaper than regular on-demand VMs, they can be pulled back with only a 30-second heads-up when GCP needs to prioritize other users. If your workloads are flexible, this is an easy win for your budget.

Some examples of workloads that can benefit from using GCP Spot VMs include:

• Batch jobs: These are typically non-interactive workloads that can be stopped and resumed without any negative impact. Examples include data processing, analytics, and rendering.
• Stateless workloads: These are workloads that do not maintain any persistent state, and can easily be replaced by another instance if needed. Examples include web servers and load balancers.
• Fault-tolerant workloads: These are workloads that can continue to function even if one or more instances are terminated. Examples include distributed systems and applications that use auto-scaling.

2. GCP Active Assist - Optimizing Resources

GCP Active Assist provides real-time guidance and suggestions to help users troubleshoot and optimize their GCP resources. It can help users identify and resolve issues related to performance, cost, security, reliability, manageability, and sustainability, GCP calls it “Recommenders”.

It also provides automated remediation actions to help users quickly resolve problems and improve the overall health of their GCP resources through Recommendations Hub. These Recommendations can also be consumed via Recommender API or exported to BigQuery on a scheduled manner.

VM Machine Type Recommender

• It takes into account data such as CPU and memory usage, as well as how many vCPUs and how much memory is allocated to the VMs. It also considers the cost of the different machine types so you can get the most cost-effective option.
• The recommender can also detect VMs that are underutilized or idle and suggest shutting them down or resizing them to save money. It can also detect VMs that are overutilized and suggest upgrading them to improve performance.
• It relies on machine learning algorithms to make its recommendations. They are updated in real-time as new usage data becomes available, which lets the recommender adapt to changing usage patterns and make more accurate recommendations.

3. Cloud Asset Inventory

Cloud Asset Inventory helps in optimizing resource allocation. It can provide detailed information about the resources in use, such as the resource type, location, and size.

This information can be used to optimize resource allocation by identifying resources that are over or under-allocated and adjusting them accordingly.

While Cloud Asset Inventory can be a powerful tool for tracking resource changes, there are some limitations to be aware of:

• Limited historical data: Cloud Asset Inventory may not retain historical data for an extended period of time, which can make it difficult to track long-term resource changes or trends.
• Limited visibility into certain resources: Some resources, such as cloud services or applications, may not be fully visible to Cloud Asset Inventory, which can make it difficult to track changes to those resources.
• Limited integration: Cloud Asset Inventory may not be able to integrate with other tools or systems, which can limit the ability to track resource changes in a centralized way.

How can Economize Help to Optimize your GCP Costs?

Economize stands out in the cloud cost management space by offering a dynamic and effective solution for organizations struggling with high cloud costs across AWS, GCP, and Azure environments. Here are a few ways it can help cut down your costs:

Ridiculously Beautiful Cost Reports

Gain a holistic view of your cloud costs by bringing together all spend data from different cloud environments into one place, making it easier to track and manage your costs. With our aggregated view, you can get a complete picture of your cloud financial health and make informed decisions. Always stay on top of your cloud costs and pilot it like a pro.

Slice and dice your complex cost data

Flexibility for you to focus on the area that matters the most to you — whether that be at the organization, project, billing account, or even tag level. Export the reports and share them with your team and stakeholders. Obtain a bird’s-eye view of your entire organization’s costs and drill down to an organization, or a project, a billing account, or as granular as a tag. Promote transparency and accountability and align everyone on a shared FinOps goal.

Cloud Visibility. Financial Stability.

Empower your developers with cloud cost visibility allows them to understand the financial impact of their decisions and take ownership of their costs. Foster a culture of cost awareness and accountability to achieve long-term financial stability. Analyze cost patterns and consumption trends and predict future costs to perform budgeting and financial planning.