Google Cloud Platform (GCP) is organizations' preferred data storage solution for numerous factors. In addition to its reputable customer support, GCP stands out by providing state-of-the-art storage features with a subscription pricing model. However, costs can escalate if the services remain unmonitored. This is why it is crucial to prioritize the implementation of GCP cost optimization strategies.
Our extensive blog will explore the complexities of the GCP, such as Google cloud billing and pricing models. Furthermore, our primary focus is helping you with practical and efficient cost optimization strategies for GCP. By the end of this blog, we will ensure that you have sufficient knowledge to manage your budget effectively in the short run and establish solid groundwork for long-term cost savings.
Despite entering the arena later than some other players, GCP has made a remarkable impact in cloud computing. With its efficient infrastructure and budget-friendly services, GCP has gained a significant market presence, currently holding an impressive 11% share.
With versatility and a diverse ecosystem that caters to various applications like managing big data and storing distributed files, It's no wonder GCP has secured its position as one of the top three cloud service providers.
Even though GCP has clear benefits, users sometimes struggle with the complex cost dynamics of its services. The platform's intricacies can cause cloud expenses to increase, so it's essential to take a focused approach to optimize GCP costs.
But before diving in, we must comprehensively understand what factors drive the GCP cost, how GCP pricing works, and why GCP cost optimization is essential.
What is GCP Cost Optimization?
GCP cost optimization means effectively managing and minimizing costs while getting the most value out of Google Cloud services. The aim is to balance performance, resource usage, and expenses.
Cost optimization in GCP includes using different strategies to control and decrease cloud spending while meeting your organization's operational and performance needs.
GCP cost optimization strategies include:
Using cloud cost management tools
Right-sizing resources
Optimizing compute resources
Optimizing storage resources
Monitoring and logging networking traffic
Tuning data warehouse
What Factors Drive The GCP Cost?
Several factors play a vital role in the costs involved in using GCP. Organizations need to understand these factors to manage and optimize their expenses effectively. The main elements that impact GCP costs include:
Compute resources- Virtual Machines (VMs): The type, configuration, and duration of VM usage significantly impact costs. Opting for higher-performance VMs or more significant instances with more resources may increase costs.
Storage resources Data storage: The costs are influenced by the amount of data stored, the type of storage (Standard, Nearline, Coldline), and how long the data is stored. Data transfer: Expenses are incurred for transferring data within and between GCP and external networks.
Networking Network bandwidth: The cost can be influenced by the amount of data transferred over the network. Additional egress and ingress data expenses might be incurred if the application experiences high traffic or involves significant data transfer. Load balancers and networking services: Expenses can be affected by using networking services like load balancers or premium network tiers.
Services and API usage: Charges are incurred based on the specific GCP services and APIs used. Moreover, using more services increases associated costs.
Data processing: Costs are influenced by the quantity and complexity of data processing tasks such as BigQuery queries or data transformation using Cloud Dataflow.
Location of resources Region-based pricing: The costs can vary depending on the geographic location where resources are provisioned. Prices vary in regions, so choosing a particular region can affect your overall expenses. Infrastructure availability: Factors like infrastructure availability and local regulations can lead to price fluctuations across different regions.
Monitoring and logging: Costs are associated with the amount of monitoring and logging data generated, especially when utilizing services like Stackdriver.
License and software: Using specific licenses and software, like Windows Server licenses or extra software components, can add to the total expenses.
Committed use discounts and sustained use discounts: Taking advantage of committed use discounts for long-term commitments and sustained use discounts for continuous resource usage can impact costs.
How Does GCP Pricing Work?
To use GCP to your advantage while simultaneously ensuring cost-efficiency, you need to be well acquainted with the GCP pricing and how it works. By understanding these pricing mechanisms, you can make the most of your resource allocation, select affordable options, and efficiently handle the overall spending within the GCP ecosystem. Here are the key aspects of how GCP pricing works.
Pay-as-You-Go model: This means that you will only be billed for the actual resources you use. You'll only pay for the computing, storage, and other resources you consume within a billing period.
Sustained use discounts: GCP offers sustained use discounts for virtual machine instances that run for extended periods. As you continue to use a VM, the per-hour cost automatically decreases, ensuring you get the best value for your money.
Committed use discounts: GCP offers committed use discounts wherein by committing to a specific amount of resources, such as virtual machines, for a one or 3-year term, you can enjoy significant discounts compared to pay-as-you-go rates.
Free tier: GCP provides a free tier with limited resources. You can use this opportunity to test out various services completely free.
Why Is GCP Cost Optimization Important?
Considering the diverse factors influencing GCP costs, as outlined earlier, it becomes evident that optimizing expenses within the GCP is imperative for organizations seeking to derive optimal value from their cloud investments. This optimization balances financial considerations and operational needs and fosters a culture of responsible resource utilization.
By embracing GCP cost optimization, businesses position themselves strategically for sustained success. Let us look at the detailed significance of GCP cost optimization.
Cost efficiency: GCP cost optimization guarantees that your organization utilizes cloud resources wisely, avoiding unnecessary expenses. By optimizing costs, businesses can accomplish more within their designated budget, making the most of their allocated resources.
Budget control: Effective cost optimization grants better control over cloud spending, allowing your organization to stay within budget boundaries. This prevents unexpected or inflated cloud bills, enabling businesses to manage their financial resources efficiently.
Resource utilization: Optimization guarantees that resources are utilized to their utmost potential. Overprovisioning is avoided by appropriately sizing and configuring resources, allowing organizations to only pay for what they require. This helps businesses maximize their utility and achieve cost savings without compromising efficiency.
Scalability: With GCP cost optimization, you can quickly scale your operations without worrying about skyrocketing costs. Optimized resource usage ensures smooth scalability as your business grows without unexpected expenses.
Performance enhancement: When you optimize costs, you also improve the performance of your resources. By fine-tuning resource configurations to match your application requirements, you'll experience enhanced performance and efficiency.
Financial predictability: Predictable costs are crucial for effective financial planning. By adopting cost optimization practices, you can accurately forecast and manage your expenses, reducing any financial uncertainty that may arise.
Long-term savings: Committing to reserved instances or utilizing sustained-use discounts are clever tactics that lead to long-term savings. You'll enjoy reduced costs throughout your cloud journey by investing time in cost optimization.
Enhanced visibility: Cost optimization tools and practices offer a better perspective on how resources are used and where money is spent. This visibility will empower your organizations to make well-informed decisions regarding resource distribution and future investments.
Continuous Improvement: Adopting cost optimization is an ongoing journey. By consistently reviewing and enhancing resource usage, your organization can refine cost management practices and improve overall efficiency over time.
GCP Cost Optimization Strategies For Holistic Benefits
Now that we have a comprehensive understanding of the intricacies concerning GCP costs let us dive into different GCP cost optimization strategies you can implement to ensure high-end performance without escalated costs.
1. Understand The Bill & Cost Management Tools
The first step to understanding GCP costs is to understand cloud bills and how cost management tools can help optimize GCP costs.
GCP Billing
Google Cloud Billing is a handy service that handles all your financial needs when using GCP. It gives you a detailed breakdown of the costs associated with the different GCP resources and services you use. Let's dive into the key components and features you get with Google Cloud Billing:
Usage tracking: You can closely monitor your consumption of GCP resources and services. We'll monitor and track it all for you.
Cost reporting: You can easily generate detailed reports to see the costs tied to different GCP resources. The reports also provide valuable insights into usage patterns, cost trends, and expenses related to specific resources.
Budgets: You can take control of your spending on GCP by setting budget thresholds. You will get alerts whenever your actual costs come close to or exceed the limits you define.
Cost allocation: Need to divide costs among various departments, projects, or teams? The cost allocation feature lets you easily categorize resources based on labels and tags. This way, you can analyze costs more detailed and granularly.
Forecasting: With the help of historical billing data, the forecasting feature can predict costs for future periods. It assists in budget planning and helps anticipate potential cost changes.
With its wide range of features, GCP billing will provide profound insight into cloud spending and also help your organization with future planning.
Cloud Cost Management Tools
Cloud cost management tools are software solutions that help organizations monitor, analyze, and maximize the budget for cloud resources and services. Cloud cost optimization tools prove beneficial in the following ways.
These tools will give your business a clear view of the use and spending on cloud infrastructure, empowering you to make smart decisions to optimize their spending.
These tools will help your organization optimize its cloud spending, ensuring that resources align with business goals, and ensure that you get the most bang for your buck with cloud infrastructure and services.
To help you narrow your search, we have compiled a list of the top 24 cloud cost management tools that will assist your organizations in making the most out of your various cloud services, including GCP service, in 2024. Some GCP-dedicated tools mentioned in the blog are:
CloudZero: A modern cloud cost intelligence platform, CloudZero will help you ingest, analyze, and report on data from multiple sources, including Snowflake and Google's BigQuery.
Harness: Harness.io, famous for its expertise in CI/CD, chaos engineering, and security testing, has expanded its capabilities to include cost monitoring and management. This integration allows you to easily aggregate, analyze, and optimize your GCP costs in one user-friendly platform.
Apptio Cloudability: Cloudability provides comprehensive cost visibility across multiple cloud services, such as GCP, regardless of scale. It also offers powerful tools for budgeting, forecasting, and allocating costs while allowing the creation and maintenance of cost governance policies effortlessly.
2. Pay Only For The Compute Resources You Actively Use
Once the cloud management tools and the billing reports give you an insight into the cloud spending, you need to focus on computing resources you are not using since idle resources due to overprovisioning might continue to incur charges even when they are not being actively used.
Follow the tips mentioned below to save on computing resources costs.
Identify Idle VMs: Google Cloud offers a range of Recommenders, including Idle VM Recommender. This tool uses advanced analysis of usage patterns to identify any inactive VMs. If you want to know more about how Recommenders can help, read it here.
Automate VM Schedules For Cost Savings: Wouldn't it be great if your virtual machines (VMs) only ran when you needed them? In production, VMs run non-stop to keep your systems running smoothly. However, VMs often sit idle outside of business hours in development, testing, or personal environments.
By automating the start and stop schedules of your VMs, you can:
Ensure they only run when you're actively using them, and turn them off during those idle periods.
Stay organized and save significant costs in the long run.
Rightsize VMs: The workload requirements can change over time, and initially, well-suited instances might have more resources than necessary due to decreased user and traffic demands.
To use your resources efficiently, consider right-sizing recommendations. This means adjusting the type of machines you use, matching the virtual CPU and RAM to your current needs, and optimizing how you use resources overall. It helps you get the most out of what you have.
Use Preemptible VMs: Preemptible VMs offered by GCP are an option for those seeking cost-effective and temporary computing resources. These virtual machines (VMs) are tailor-made for tasks that can withstand interruptions and are resilient to technical glitches.
The features mentioned below make implementing Preemptible VMs an absolute necessity for GCP cost optimization:
Cost-Effective: Preemptible VMs offer a great way to save money compared to regular on-demand instances. They are significantly cheaper, saving you substantial costs for specific use cases.
Short-Lived: Preemptible instances are designed for short-lived workloads or can be spread across multiple instances. They have a maximum runtime of 24 hours, making them suitable for tasks that don't require long-running durations.
Fixed, Predictable Pricing: With preemptible VMs, you get the advantage of fixed and predictable pricing. This makes it convenient for users to estimate and manage costs for their workloads without any surprises.
Flexible Deployment: Preemptible instances seamlessly integrate with your existing infrastructure alongside regular non-preemptible instances. This flexibility lets you maximize both options, ensuring a smooth and efficient deployment.
3. Monitor And Log Network Traffic
Robust logging and monitoring ensure effective network and security operations. However, in intricate setups encompassing multiple clouds and on-premises systems, gaining a clear and comprehensive view of network usage can be as tough as figuring out how much electricity your microwave consumed last month. Fortunately, Google Cloud has a set of user-friendly tools that offer valuable insights into your network traffic, such as
VPC Flow Logs: VPC flow logs capture and save information about network flows within a Virtual Private Cloud (VPC). Key feature: It records essential details like source and destination IP addresses, ports, protocols, etc. This information can be used for troubleshooting, security analysis, and performance monitoring.
Stackdriver Logging: Stackdriver Logging collects and stores logs from various Google Cloud services, which include networking components. Key features:
This service provides centralized logging, making analysis and troubleshooting a breeze.
It also supports custom log filters and allows the exporting of logs to external systems.
Stackdriver Monitoring: Stackdriver Monitoring closely monitors the performance and availability of applications and infrastructure, including network-related metrics. Key features:
With easy-to-understand dashboards, it allows visualizing network performance effortlessly.
It supports proactive issue detection through alerting based on custom conditions.
Having discussed the tools, let us now talk about some tips for configuration changes that you can implement to lower the network cost.
Identify Which Services Are Taking Up Bandwidth: The GCP SKUs (Service Key Units) provide a user-friendly way to quickly determine how much you're spending on a specific Google Cloud service.
Know Your Network Layout And How Traffic Flows: The Network Topology module in the Network Intelligence Center gives a detailed understanding of your worldwide GCP setup and how it connects to the internet.
It offers a complete view of the organization's network structure and provides metrics to assess its performance.
This feature empowers you to pinpoint inefficient deployments, enabling you to optimize regional and intercontinental network egress costs strategically.
You can learn about Network Topology and Network Intelligence Center through this video.
Choose The Right Network Service Tier: When using Google Cloud, you can choose between premium and standard options.
Premium tier: You'll enjoy exceptional global performance by choosing the premium tier.
Standard tier: The standard tier provides a suitable alternative for specific cost-sensitive tasks, although it delivers slightly lower performance.
Enable Sampling: Sampling selectively stores a portion of log entries instead of logging every single one. It's a useful feature that will allow you to manage the amount of log traffic generated, making the most of resources while gaining valuable insights into network activities. There are two primary use cases in context with networking cost- VPC flow logs and cloud load balancing. VPC Flow Logs: VPC Flow Logs provide valuable information about network flows within a Virtual Private Cloud (VPC).
Sampling Option: You can enable sampling for VPC flow logs and choose a sampling rate ranging from 1.0 (keeping 100% of log entries) to 0.0 (keeping no logs).
Benefits: Sampling effectively handles and controls the volume of log data generated by VPC Flow Logs, especially when retaining every single log entry is unnecessary. Cloud Load Balancing: Cloud Load Balancing is a helpful service that cleverly distributes incoming network traffic across multiple backend instances. This guarantees that resources are utilized optimally and your application stays always available.
Sampling Option: It works just like VPC Flow Logs. By setting a sampling rate between 1.0 and 0.0, you can control how many log entries you want to keep. A rate of 1.0 means you retain 100% of log entries, while a rate of 0.0 indicates no logs are kept.
Benefits: It captures a representative subset of log entries, giving you valuable insights into load-balancing activities. Moreover, it reduces the overall log volume without compromising those essential insights. So, you get fewer logs and no compromise on keeping track of your load-balancing activities.
4. Streamline Your Data Warehouse
Optimizing your data warehouse for GCP cost efficiency is vital to balance performance, scalability, and budget. It guarantees that your cloud resources align with your requirements, preventing unnecessary expenses and fostering a cost-effective and responsive infrastructure. Incorporate the tips mentioned below in your GCP to ensure cost efficiency.
Enforce Control: Enforcing control is crucial in optimizing GCP costs. By setting up controls, you can ensure resources are used efficiently, avoid unnecessary expenses, and improve overall cost management. GCP cost control can be achieved in the following ways:
Monitor and control queries: Use query monitoring and enforcement policies to prevent queries that consume excessive resources and inflate costs.
Managing costs: Set time limits and cost controls for query execution to avoid unexpected high costs caused by inefficient queries.
Partition And Cluster Datasets: Partitioning and clustering tables within GCP services, especially in services like BigQuery, can substantially affect cost and performance. It can help in the following ways:
Organizing large datasets: Optimize data processing by partitioning large datasets into smaller segments using table partitioning. This helps reduce the amount of data processed for specific queries, making it more manageable.
Enhancing query performance: Improve query performance and minimize data scanning by implementing table clustering. It organizes the data physically in storage, leading to faster retrieval and analysis.
Check For Streaming Inserts: If you use streaming inserts to continually add data to services such as Google BigQuery, it may result in extra costs compared to loading data in batches. You can reduce the cost of streaming inserts when you:
Opt for batch data loading: Switch from real-time streaming inserts to batch-loading data. Batch-loading is not only more cost-effective but also helps in avoiding additional expenses associated with real-time streaming.
Implement Flex Slots For Ultimate Flexibility: Flex Slots is GCP's new feature, allowing you to purchase BigQuery slots for as short as 60 seconds, giving you unparalleled control over your analytics. It ensures:
Easy and Budget-Friendly Scaling: By combining on-demand and flat-rate pricing with Flex Slots, you can scale quickly and cost-effectively to meet your ever-changing needs.
Effortless Cost Optimization: With Flex Slots, you can easily adjust your slot commitments based on your analytics workload, ensuring optimal cost management without hassle.
5. Optimize Cloud Storage Cost &Performance
Storage is one of the most overlooked aspects when the organization plans cloud cost optimization. However, studies suggest otherwise. According to “State of Hybrid Cloud Storage,” a study done by Virtana on over 350 cloud decision makers, it was found that:
94% of the respondents expressed concern over their cloud storage cost increasing.
54% said that their storage cost was increasing at a faster rate than the overall cloud bill.
We also conducted an independent survey on over 100 enterprises using GCP and discovered that block storage, aka the persistent disk, contributed significantly to the overall cloud bill. We also found out that:
Average disk utilization was low.
Despite overprovisioning, organizations were facing at least one downtime per quarter.
Similar to compute resources, network traffic, and data warehouse, optimizing cloud storage cost and performance to promote a cost-effective and efficient cloud infrastructure is important. Below are some strategies you can use to enhance cloud storage cost optimization.
Monitor The Storage Resources
The first step to ensuring you are heading towards the right path of storage cost optimization is monitoring which resources are idle or overprovisioned.
We’d advise against going the manual route or using monitoring tools because they are limited by tedious DevOps efforts or the additional cost of deployment.
An easy-to-use three-click process for quick and actionable insights, Lucidity Storage Audit, provides the following information.
Spending Analysis: The Lucidity Storage Audit helps you save on costs with a detailed spending analysis. It pinpoints areas where you can significantly reduce your storage expenses.
Identification of Wastage: It detects inefficiencies related to overprovisioning and helps you create an optimized and cost-effective storage environment.
Identifying Performance Hurdles: The audit tool identifies performance bottlenecks, allowing you to address them promptly. This ensures operational continuity and prevents any financial or reputational concerns.
Once you have identified the idle or unused resources, you can delete or right-size them.
Auto-Scale Storage Resources
Overprovisioning has a significant cost-related impact since you are paying for resources that you are not using.
Then why do organizations overprovision storage resources instead of optimizing storage resources?
Upon investigating, we found out:
Challenges in Creating Custom Tools: The limited capabilities of Cloud Service Providers (CSPs) prompt the need to develop a specialized tool to enhance storage optimization. However, this approach demands substantial DevOps effort and time investment, adding more complexity to the process.
Drawbacks of CSP Tools: Using only CSP tools can result in labor-intensive and resource-heavy workflows. The manual nature of these tools makes it impractical for daily optimization efforts.
No live shrinkage of storage resources available: While increasing the size of the persistent disk to accommodate growing requirements is easy in GCP, there is no direct process for shrinkage of the same. You will have to follow manual steps, which are susceptible to errors and misconfigurations. Moreover, manual processes lead to downtime and performance degradation.
The challenges associated with CSP tools and the impact of the abovementioned approaches on day-to-day business operations make overprovisioning a trade-off for reliability.
The challenges organizations face necessitate an automated solution for optimizing cloud storage cost and performance. Lucidity has come up with one such solution- Block Storage Auto-Scaler.
An industry’s first autonomous storage orchestration solution, Lucidity’s Block Storage Auto-Scaler offers seamless and automatic expansion and shrinkage of the storage resources without any downtime or performance issues.
The cutting-edge technology effortlessly adapts to your changing storage needs, always ensuring the perfect capacity. With the help of the Block Storage Auto-Scaler, your storage resources will be efficiently scaled, guaranteeing top-notch performance while accommodating your dynamic storage requirements.
Lucidity’s Block Storage Auto-Scaler offers the following benefits:
Automated Block Storage Scaling: With Lucidity's Block Storage Auto-Scaler, your resources are always optimized for seamless availability. It adapts effortlessly to fluctuating demands, simplifying expansion and contraction in real-time.
Storage Cost Savings (Up to 70%): Say goodbye to overprovisioning and hello to up to 70% cost savings with Lucidity's Block Storage Auto-Scaler. It maximizes disk utilization, efficiently from 35% to 80% of your storage space.
ROI Calculator: Use Lucidity's user-friendly ROI Calculator to estimate potential savings. Simply input your disk spend, growth rate, and utilization to explore how cost-effective our solution can be for your business.
Zero Downtime Operation: Ensure uninterrupted operation with Lucidity's dynamic storage resource adjustments. Thanks to the innovative technology, you can be confident that your system will never experience downtime during configuration changes.
Customized Policy Configuration: Easily create policies tailored to your needs, like specifying a name, desired utilization, maximum disk size, and buffer size with the “Customized Policy” feature.
Configure Lifecycle Policy
By properly setting up and utilizing lifecycle policies, you can ensure your storage resources are used efficiently and economically while meeting the data access and retention needs. This helps create a more seamless, automated, and budget-friendly method of managing data at every stage of its lifecycle within GCP.
Configuring lifecycle policies has the following benefits:
Data Transition and Archiving:
Lifecycle Stages: With lifecycle policies, you can set different stages for your data's lifecycle – from transitioning data from hot to cold or from active to archival.
Automatic Transition: You can easily configure policies to automatically move data between storage classes based on specific criteria. This way, less frequently accessed data can be shifted to more cost-effective storage classes, helping you save on storage costs.
Reduced Storage Costs:
Data Deletion: Say goodbye to unnecessary data clutter! Lifecycle policies can be set to automatically delete or expire data that is no longer needed or relevant.
Avoiding Accumulation: By getting rid of obsolete or expired information, you can avoid accumulating storage costs. This way, you only pay for what you actually use and need.
Improved Resource Utilization:
Resource Cleanup: The automatic deletion feature in lifecycle policies removes obsolete or outdated resources, ensuring efficient resource utilization.
Rightsizing: With the help of lifecycle policies, you can optimize your storage resources by removing any unneeded objects. That means you can make the most out of your storage capacity and save valuable resources.
6. Adopt And Implement FinOps
FinOps, or Financial Operations, is a powerful framework that enables organizations to boost their cloud financial management by combining financial accountability, cloud expertise, and cutting-edge technology.
By embracing FinOps practices, you can significantly enhance your ability to manage and optimize costs on the GCP. This results in improved financial efficiency and ensures alignment with business goals.
Financial Accountability: FinOps fosters a mindset of being financially responsible, ensuring your team understands their cloud expenses and has the duty to manage them efficiently.
Showback and Chargeback: FinOps practices often include implementing showback or chargeback mechanisms, which will help your team become more conscious of their resource usage and the associated costs.
Promoting Collaboration Across Teams:
Cross-Functional Collaboration: FinOps promotes collaboration among finance, operations, and engineering teams. This collaborative approach ensures that cloud spending aligns with your business objectives and that cost considerations are part of the decision-making process.
Enhancing Resource Optimization:
Right-sizing Resources: It ensures that instances and services are provisioned with the right capacity to meet performance requirements without unnecessary overprovisioning.
Identification of Idle Resources: It regularly identifies and addresses idle resources in FinOps to avoid unnecessary costs. By doing this, you eliminate any wastage and ensure that resources are actively utilized.
Enabling Continuous Optimization:
Automation and Policies: This includes implementing policies for automatic scaling, shutting down during idle periods, and other measures to optimize costs. Automating these processes makes it easier for you to manage your resources efficiently.
Continuous Review: This is done based on changing business needs, adopting new services, and understanding evolving cloud usage patterns. Doing so ensures that your cost management strategies always align with your current requirements.
Make Way For Cost-Effective Cloud Environment With GCP Cost Optimization Strategies
Optimizing your GCP costs is not a one-and-done task but an ongoing process that adapts to your organization's requirements. By implementing the strategies we discuss in this blog, you can embark on a journey toward efficiency, improved performance, and significant savings. Keep checking your cloud architecture, adjusting resource allocations, making the most of automation, and staying up-to-date with the latest cost management tools. It's essential to t balance between cost-effectiveness and operational excellence, ensuring that your GCP resources seamlessly align with your business goals.
If optimizing your cloud service feels like a challenge due to a lack of clear insights, the culprit might be lurking in your storage usage. Reach out to Lucidity for a demonstration. Experience firsthand how our automation can identify storage wastage and proactively prevent its recurrence. Let Lucidity guide you toward a more streamlined and efficient cloud cost optimization journey.