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When it comes to storage, Google Cloud has a wide range of services and configuration options available. This is a crucial step in your cloud journey: the storage option you choose will have major impacts on your operations and your overall Google Cloud pricing.
In Google Cloud, block-storage is often synonymous with Persistent Disk, a managed block storage service with both HDD or SSD based storage volumes that are stripped across several physical hardware disks to provide out of the box redundancy and high performance.
However, this is just the tip of the iceberg. In this article, we will cover Google Cloud disk storage options and how we can find and optimize its cost.
Jump to the relevant section:
- Understanding Google Cloud Disk Types and Costs
- Google Cloud Cost Monitoring, Storage Usage, and Related Costs
- Google Cloud Cost Optimization
- How to Optimize Google Cloud Disk Storage Even More
Understanding Google Cloud Disk Types and Costs
Of all the storage offerings on Google Cloud, Persistent Disk is the go-to option for high performance storage. While by default each persistent disk is located in a single geographic location (aka, “Google Cloud zone,”), that setting can be reconfigured to be a regional persistent disk replicated across two or more geographical zones to ensure a higher level of availability and protection.
There are another two, lesser-known block-storage options: Google Cloud Local SSDs and Hyperdisks.
Google Cloud Local SSDs are physical drives directly attached to the hardware where your virtual instance is running. This is an option that ensures better performance but no persistence capabilities. These disks are ephemeral and are therefore deleted once your virtual instance is terminated.
Hyperdisk volumes are a type of network-based storage available for Google Cloud Compute Engine that combines fast redundancy capabilities with flexibility options such as dynamic resizing or different levels of performance choices.
Key Difference Between HDDs, SSDs and Hyperdisks
HDDs (hard disk drives), SSDs (solid state drives), and Hyperdisks are all types of storage options that can be used in computing systems.
- HDDs are the oldest, most widely used storage format. They use spinning disks to store data magnetically, and are less expensive than other types of storage. However, they are significantly slower than SSDs and have a higher risk of mechanical failure due to their moving parts.
Persistent Disk is the only Google Cloud disk option that offers HDD storage. HDDs are suitable for use cases such as personal virtual desktops and to store large amounts of data, such as backups, logs, and archives.
- SSDs are newer and faster than HDDs. Using flash memory, SSDs can provide access times and data transfers that far outpace HDDs. They are also more reliable than HDDs, as they have no magnetic or moving parts. However, they are more expensive than HDDs and they won’t last as long: SSDs come with a finite number of read and write cycles (usually in the thousands or tens of thousands), which limits their overall lifespan.
SSDs, available in Persistent Disk and Local SSDs, are suitable for use cases such as high-performance storage for web applications, databases, caching, and logging workloads.
- Hyperdisks are a type of storage device that is unique to Google Cloud. They are designed to provide ultra-fast, low-latency storage for workloads that require high-performance storage.
Hyperdisks use NVMe (non-volatile memory express) technology to achieve extremely fast read and write speeds, and they are designed to be used with Google Cloud's compute instances. They are also fully managed by Google, which means that customers do not need to worry about managing the underlying infrastructure.
Hyperdisks, available with Google Cloud Compute Engine, are suitable for use cases such as real-time analytics systems and machine learning model training systems.
In short, HDDs are the oldest and cheapest type of storage, but they are slower and less reliable than other options. SSDs provide an edge over HDDs when it comes to speed and reliability, but they are more expensive and have a limited lifespan. Hyperdisks are the fastest option and are designed for high-performance workloads, but they are also the most expensive and are only available in Google Cloud.
Cost Factors in Google Cloud Disk Storage
In any Google Cloud disk storage option, the cost varies significantly based on a number of different factors. It is important to have a good understanding of the different cost factors.
- Local SSDs costs are based on the provisioned space (per GB per month) and region by default. However, customers can opt for spot pricing (dynamically adjusted once every 30 days with a discount up to 60-91% off the on-demand price), or long term commitments (1 or 3-year) for potential and predictable savings and cost optimization.
- Persistent Disk has four disk types to choose from: Standard, SSD, Balanced, and Extreme. With the exception of Standard (which is HDD-based), all other options are backed by SSD. The main difference in costs between these types comes down to price per GB used. However, in the Extreme type, customers can instead choose to specify the amount of provisioned IOPS.
With the exception of Extreme, persistent disks are provisioned in a single zone. Yet, with a higher cost per GB, customers can instead provision them at a regional level with built-in high availability across two zones.
- Hyperdisk Extreme is highly available by default within a region and the cost is driven by either the amount of provisioned space or IOPs.
Google Cloud Cost Monitoring, Storage Usage, and Related Costs
Monitoring and keeping track of storage usage in Google Cloud is crucial for effective cost management. By tracking your storage usage, you can identify opportunities to optimize your storage infrastructure and reduce costs. Google Cloud offers several tools to help you monitor and manage your storage usage, including Google Cloud Monitoring’s disk metrics and billing reports.
- Disk metrics collected in Google Cloud Monitoring provides detailed information about your disk usage, including the amount of storage used, IOPS, and throughput. You can analyze this data to identify areas where you can optimize your storage usage and reduce costs, such as identifying underutilized disks that can be resized to reduce costs.
- Billing reports in Google Cloud Monitoring provide a detailed breakdown of your cloud usage and associated costs. You can use this tool to track your storage costs over time and pinpoint overspending areas. For example, you can identify storage types or regions that are contributing to high costs and adjust your storage infrastructure accordingly.
By using these tools to monitor and manage your storage usage, you can optimize your storage infrastructure and reduce costs. Additionally, keeping track of your storage usage and costs over time can help you make informed decisions about future storage investments and ensure that you get the most out of your Google Cloud deployment.
Google Cloud Cost Optimization
When it comes to optimizing Google Cloud disk storage costs, it’s important to look at both OS and application-level optimization techniques. Below, we will highlight the most important factors to consider in order to help reduce your cloud spending without sacrificing performance or functionality.
OS Level Storage Optimization
- Use the right storage type: Google Cloud offers a range of storage types, including HDDs, SSDs, and Hyperdisks. Choosing the right storage type for your application can help to ensure that you are getting the performance you need while also minimizing costs. For example, you may want to use HDDs for less frequently accessed data, and SSDs or Hyperdisks for more frequently accessed data.
- Implement RAID (Redundant Array of Independent Disks): RAID configurations can improve your storage system’s performance, reliability, and availability. RAID allows you to combine multiple physical disks into a single logical volume, providing more redundancy and better performance than a single disk.
By distributing data across multiple persistent disks or Local SSDs, a RAID 0 configuration (a setup without redundancy) provides a maximum amount of IOPS without having to pay extra for provisioned IOPS. RAID is supported by many operating systems and can be configured at the OS level, making it a cost-effective and easy-to-implement storage optimization approach.
Application Level Storage Optimization
Optimizing storage at the application level in Google Cloud can help to improve your applications’ performance and efficiency, while reducing costs. Here are some ways to optimize storage at the application level in Google Cloud:
- Optimize data storage: One way to optimize data storage is to compress and deduplicate your data set to reduce the space it uses. For example, you can use Gzip compression to compress HTTP responses, or use deduplication to eliminate duplicate data in backups or archives. NetApp Cloud Volumes ONTAP offers these kinds of built-in storage efficiency features, which can combine to reduce Google Cloud storage footprint by 70% or more in some cases.
- Implement caching: Caching technology keeps frequently accessed data in memory or fast storage for quick access. Implementing caching in your application can help to reduce the number of requests to your storage backend, which can improve performance and reduce costs.
Google Cloud offers a range of caching solutions, including Cloud Memorystore and Cloud CDN. Cloud Volumes ONTAP and BlueXP edge caching make it even easier to cache data and make it accessible to all your users.
- Use data tiering: Data tiering is the process of storing data in different tiers of storage based on its access frequency or other criteria. For example, you can store frequently accessed data in fast storage, and less frequently accessed data in slower storage. You can explore moving certain datasets from disk to object storage (Google Cloud Storage), implement automated data lifecycle rules and delete unnecessary data.
Cloud Volumes ONTAP makes this possible with data tiering. Data tiering automatically tiers infrequently used data between block storage to object storage on Google Cloud, and when it’s needed again, seamlessly tiers it back.
By implementing these techniques, you can optimize storage at the application-level in Google Cloud, improving the performance and efficiency of your applications while also reducing costs. It's important to carefully consider the needs of your application and choose the right storage options for your specific use case. With the right storage strategies in place, you can ensure that your applications are running at their best and providing the best possible experience for your users.
How to Optimize Google Cloud Disk Storage Even More
Optimizing storage disks in Google Cloud requires a comprehensive understanding of the costs associated with different storage options. With Google Cloud's wide range of storage types—HDDs, SSDs, and Hyperdisks—it's important to know each with its own associated tradeoffs in terms of performance, reliability, and cost.
To optimize storage at the OS and app level, it's important to explore methods such as caching, data compression, deduplication and data tiering.
For NetApp users, there are even more cloud storage solutions to help reduce disk costs and improve performance on Google Cloud. NetApp Cloud Volumes ONTAP is an enterprise-grade data management layer for Google Cloud, as well as AWS and Azure, providing built-in capabilities that significantly improve the performance, mobility, reliability, and overall total cost of ownership for cloud resources.
Check out how a native Google Cloud disk deployment compares to deploying with Cloud Volumes ONTAP using our TCO calculator here.
