Cloud computing has revolutionized the way businesses operate. However, with the rise of cloud adoption comes a new set of challenges. One of the biggest challenges that organizations face today is managing their cloud costs.

This is where FinOps comes in.

In this article, we will explore the concept of FinOps and provide 7 best practices for optimizing cloud costs using FinOps for both Google Cloud Platform (GCP) and Amazon Web Services (AWS). But before we dive into the strategies, let’s first understand what FinOps is and why it is important for organizations to adopt a FinOps strategy.

What is FinOps?

FinOps, or Financial Operations, is an emerging set of practices that combines financial and technical expertise to manage the costs of cloud computing. It is a set of guidelines, principles, and practices designed to help organizations optimize their cloud spending, align it with business objectives, and improve their overall cost-effectiveness.

The FinOps methodology is based on three core principles:

1. Accountability: Everyone involved in the cloud infrastructure must take responsibility for the costs they incur, and work together to optimize spending.
2. Collaboration: Teams across the organization must work together to share knowledge, tools, and best practices to optimize costs and improve efficiency.
3. Transparency: The cost of cloud infrastructure must be transparent to everyone involved, so they can understand the impact of their actions on the bottom line and make informed decisions.

Is you cloud bill haunted by the ghosts of unused instances? Maybe it’s time to go with a FinOps approach

Benefits & Advantages of FinOps Implementation

Adopting a FinOps strategy can help your organization reap many benefits from your cloud environment in terms of resource utilization, cost optimization, and increased efficiency. Here are a few major benefits:

Cost Optimization

One of the primary goals of FinOps is to optimize cloud costs, which is a critical factor for organizations that want to maximize their return on investment (ROI) from the cloud. By applying FinOps principles, teams can gain visibility into their cloud infrastructure costs and identify areas for optimization, such as rightsizing instances, leveraging spot instances, and using reserved instances.

Better Alignment with Business Objectives

By integrating FinOps practices into their cloud operations, organizations can align their cloud spending with business objectives. This alignment can help ensure that cloud investments are focused on achieving specific outcomes, such as increasing revenue, improving customer satisfaction, or enhancing operational efficiency.

Improved Governance and Control

FinOps provides organizations with the tools and practices they need to govern and control their cloud spending effectively. This control includes the ability to set budgets, enforce policies, track spending, and provide accountability for cloud costs.

Increased Collaboration and Efficiency

FinOps promotes collaboration and knowledge sharing across teams and departments, which can help organizations achieve greater efficiency and cost savings. By working together, teams can share best practices, leverage automation tools, and reduce duplication of effort.

Conducting a maturity assessment by measuring the effectiveness rate of your FinOps Domains and Capabilities is a great way to get started.

Top 7 FinOps Strategies & Best Practices for Cloud Cost Optimization

In the following sections, we will outline 7 FinOps strategies that organizations can adopt to optimize their cloud costs and improve their overall cost-effectiveness. These strategies apply to both Google Cloud Platform (GCP) and Amazon Web Services (AWS) and can help organizations achieve significant savings and improve their cloud ROI.

Right-sizing Resources

One of the most effective ways to optimize cloud costs is to right-size your resources. This involves matching the resource needs of an application or workload with the appropriate amount of resources,  which can help to avoid both under-provisioning and over-provisioning. Under-provisioning can lead to poor performance and user experience while over-provisioning can result in unnecessary cloud costs.

By right-sizing their resources, cloud users can optimize their cloud costs and improve the performance and user experience of their applications or workloads. It’s important to regularly review your resource usage and adjust your resources as needed to ensure that you’re not paying for more than you need.

Both AWS and GCP offer tools and services to help users right-size their resources. Here are some of the most commonly used options:

• AWS Trusted Advisor: A tool that provides recommendations to optimize AWS resources based on usage data and best practices.
• Amazon EC2 Auto Scaling: A service that automatically adjusts the number of EC2 instances in response to changes in demand, helping users to scale their resources up or down as needed.

Within GCP:

• GCP Cost Optimization Recommendations: A feature that provides specific recommendations to reduce costs across GCP services.
• Compute Engine Autoscaling: A service that automatically adjusts the number of instances in response to changes in demand, helping users to scale their resources up or down as needed.
• GCP Stackdriver Monitoring: A service that provides resource utilization data and insights to help users optimize their resource allocation.
• Google Cloud’s FinOps Hub is a consolidated dashboard designed to help organizations take a data-driven approach to cloud financial management.

Reserved Instances and Savings Plans

Reserved instances (RIs) and Savings Plans are cost-saving mechanisms offered by cloud service providers like AWS and GCP. These mechanisms allow users to save costs by committing to a specified amount of usage over a longer period. RIs and Savings Plans can help users optimize their cloud costs, especially for workloads with predictable usage patterns.

With RIs, users commit to using a specific instance type for a minimum duration of one year. The commitment comes with a significant discount compared to On-Demand pricing, and the discount can range from 30% to 70%, depending on the RI type.

Savings Plans, on the other hand, are a flexible pricing model that offers savings on AWS usage in exchange for committing to a specific dollar amount per hour for a one- or three-year term.

Here are the services offered by GCP:

• Committed Use Discounts: Users can commit to using resources like VMs and SQL instances for one or three years to save up to 57% on the On-Demand price.
• Sustained Use Discounts: Users can receive discounts of up to 30% for using particular resources for a significant portion of a month.

By utilizing RIs and Savings Plans, cloud users can save significant costs on their cloud usage. These savings can be reinvested in other areas of the business, such as innovation and growth. However, it is essential to note that RIs and Savings Plans come with limitations and conditions that users need to understand before committing to them. Nonetheless, they are highly recommended for workloads with predictable usage patterns, depending on the user’s needs.

Selecting the Right Storage Tier

Cloud storage providers typically offer multiple storage tiers, with varying prices based on the frequency of access, durability, and performance requirements. Organizations can optimize their storage costs by selecting the right storage tier for their data.

For instance, frequently accessed data can be stored in a more expensive but faster and more responsive storage tier, while less frequently accessed data can be stored in a cheaper, slower storage tier. This can help reduce costs without compromising performance or durability.

Both AWS and GCP offer different storage classes for different use cases. AWS offers Standard, Infrequent Access (IA), and Glacier storage classes, while GCP offers Standard, Nearline, and Coldline storage classes. AWS users can use the S3 Lifecycle policy to automatically transition objects to the appropriate storage class based on their lifecycle.

Similarly, GCP users can use Object Lifecycle Management to automatically transition objects to the appropriate storage class based on their age, access frequency, or custom criteria. By selecting the right storage tier and automating data transitions, organizations can optimize their cloud storage costs while still meeting their performance and durability requirements.

Another upcoming concept, Augmented FinOps automates financial governance, budgeting, and cost optimization through AI and ML practices.

Tagging and Resource Grouping

Resource tagging and grouping is an essential strategy for cloud cost optimization. It involves organizing resources in a cloud environment based on a set of tags or labels. This strategy helps organizations understand their cloud usage patterns and identify areas for cost optimization.

Let’s take for instance, a company can group resources based on departments, projects, or applications. This approach allows the organization to monitor usage patterns and costs associated with each group, enabling them to make informed decisions on how to allocate resources and optimize costs.

• In AWS, users can utilize AWS Cost Categories to group resources based on tags, accounts, or services. AWS Cost Allocation Tags enable users to tag resources with metadata such as department, project, or environment.
• AWS Cost Explorer allows users to visualize cost data, identify cost trends, and forecast future costs. Users can use this information to optimize their usage and improve their cost efficiency.
• Similarly, GCP provides Cloud Tags to tag resources based on metadata such as department, project, or environment.

Monitoring and Analyzing Usage

This strategy involves closely monitoring the resources being used by an organization and analyzing usage patterns to identify areas where costs can be reduced. By tracking usage patterns, companies can identify where resources are being overused or underused and take steps to optimize their cloud costs.

For instance, suppose an organization is using a cloud-based CRM application and has observed a spike in usage during certain periods of the day. By monitoring usage patterns and analyzing the data, the organization may find that users are running reports during peak hours, causing a spike in usage. By moving the report generation to non-peak hours, the organization can reduce its cloud costs without impacting user experience.

To implement this strategy, both AWS and GCP offer a range of services and tools.

• For GCP users, Cost Breakdown Reports provide detailed insights into where costs are being incurred, making it easier to identify areas where costs can be optimized. Additionally, BigQuery Monitoring for Cloud Billing Export can be used to analyze billing data and identify usage patterns. Budget alerts in GCP can also be set up to notify users when costs reach a certain threshold, allowing organizations to stay on top of their spending and make necessary adjustments.
• For AWS users, CloudWatch is a powerful monitoring tool that can be used to track resource usage in real time. Storage Lens can also be used to monitor S3 usage and identify areas where storage costs can be optimized.

Utilizing Spot Instances and Preemptible VMs

One of the most effective ways to save costs on cloud computing is to use preemptible VMs and spot instances. Preemptible VMs are short-lived instances in GCP that can be terminated at any time by the platform, usually at a significantly lower cost than regular instances.

AWS has a similar offering with spot instances, which are spare computing capacity that can be used at a discount if no one else requires them. This approach can be a cost-effective way to perform tasks that are not time-sensitive, as well as for use in batch processing jobs and fault-tolerant applications.

However, there are limitations to using preemptible VMs and spot instances. These instances are not suitable for workloads that require consistent and uninterrupted computing power, as they can be terminated at any time. Additionally, while the cost savings can be significant, there is a risk of the platform reclaiming the instance before the task is complete, which can lead to data loss or an incomplete operation.

Both AWS and GCP offer services to help users take advantage of preemptible VMs and spot instances.

• In GCP, users can use the Cloud Scheduler to automate the creation and deletion of preemptible VMs at specific times. This can help ensure that the VMs are only used when they are needed, reducing unnecessary costs.
• In AWS, users can use EC2 Auto Scaling groups to automatically launch and terminate spot instances based on demand. Additionally, AWS offers Spot Fleet, which allows users to request a combination of instance types, sizes, and pricing models to meet their specific needs. This can help maximize the availability of instances while minimizing costs.

Automating Cost Management

Cost management is one of the most important factors for cloud optimization, and automation is one way to achieve that. Automating cost management involves setting up processes and services to monitor, track, and optimize cloud spending, reducing the risk of unexpected bills and wasted resources. This strategy can help organizations of all sizes save money and maximize their cloud investment.

Google Cloud Platform provides several tools to automate cost management, including scheduling VMs, budgeting, and alerts. Organizations can schedule their VMs to start and stop automatically based on usage patterns, reducing idle time and saving costs. GCP budget alerts enable organizations to track spending against budgeted amounts and receive notifications when costs exceed set thresholds.

On the other hand, AWS provides its users with the Cost and Usage Report (CUR) to help automate cost management. This service provides detailed information about the usage and costs of AWS resources, enabling organizations to track usage patterns, identify cost drivers, and forecast future costs.

Conclusion

By leveraging various cost optimization techniques and tools available in AWS and GCP, organizations can minimize their cloud costs while still meeting their business needs.

Having a FinOps culture also promotes accountability, transparency, and collaboration across teams, which can lead to better decision-making and cost optimization.

It is essential to continuously monitor and adjust your cloud resources to ensure they are aligned with your business needs and goals. Organizations must recognize the benefits of implementing a FinOps strategy and take steps toward optimizing cloud costs to improve business performance and drive innovation.

If your organization faces rising monthly expenditure of your cloud bills, opting for one of the industry-leading cloud cost management tools can help you automate the tedious cost optimization process.

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