Cloud storage costs are impacted by factors such as data volume, transfer fees, computing resources, dev/test environments, data management, location, and SLAs, necessitating effective cost management for budget optimization.
To minimize cloud storage expenses, QA and DevOps teams can analyze storage, implement lifecycle management, use compression and deduplication, leverage different storage tiers, optimize data transfer, automate resource provisioning, and explore cost-saving options.
Adopting data-driven testing and optimizing test data management helps QA and DevOps teams significantly cut cloud storage costs and improve resource utilization in the cloud.
Launchable's Predictive Test Selection uses machine learning to predict failing tests, reducing execution times and cloud storage costs without shifting left, providing faster feedback to developers.
Cloud storage has revolutionized the way businesses store and manage their data. However, managing cloud storage costs has become a critical concern as data volumes grow. Paired with rising cloud costs overall, understanding the factors that contribute to these costs and implementing effective strategies has become essential for businesses to maximize their value.
In this article, we’ll cover the most common reasons your cloud storage costs may be so high — and some common approaches to bring them back within reason.
Managing cloud storage costs is critical for businesses to avoid overspending and optimize their budget. Excessive cloud storage costs can significantly impact your finances without effective cost management, which is never good. Let’s take a look at the most common factors that can affect your cloud:
As you probably know, most cloud providers will charge you for how much data you store on their services. Typically it’s done with a pay-as-you-use system, meaning that there’s a risk that an error or high usage can skyrocket your cloud storage costs. You may also need to fork over more if you need to access that data immediately, which can further impact your costs. Essentially, the more data you store or access, the more it’ll cost you.
Your cloud provider most likely also charges you for transferring data in and out of their platform. If your systems need to interact with your cloud data frequently, it could seriously impact your bottom line. This is especially true for large files or high-traffic parts of your application, and it doesn’t matter if that data is leaving the cloud or just going to different parts of the cloud: it’ll still charge you.
Virtual machines, containers, serverless functions, and anything else in that category within your cloud network are using resources to operate. Resources like processing power, CPU cycles, and memory are all important factors you need to track, as they can result in skyrocketing prices. Keeping track of these virtualizations and the resources they use needs to be vital to ensuring your cloud storage costs stay within your budget.
More than likely, your company uses one, if not multiple virtual environments for development and testing in the pipeline. Like computing resources, running these virtual instances of servers, databases, and other software will eat up those resources from your cloud provider. You’ll also need to keep an eye on what resources these use and how many of them are running to keep costs low.
A key aspect of maintaining large amounts of data is to make sure it’s well taken care of and readily accessible if needed. That means you’ll need to ensure redundancy in your system and have adequate plans to make data backups. That means you need to have plans to keep your data backed up regularly in case of an incident or data loss. But if these plans aren’t optimized properly, they can have a massive impact on your cloud storage costs.
Home is where the….cloud is? And wherever that cloud originates from can impact your cloud storage costs. Depending on the region you’re connecting to your cloud provider from, it can affect prices. More popular regions may have higher overall costs due to availability or demand, and transferring data between locations can also come with a cost you should be aware of.
Depending on how big your company is (or how vital your software may be), you may be under an SLA that determines your performance, level of support, and guaranteed uptime. However, these can often increase costs, especially at higher tiers. Keeping a close eye on your company’s cloud usage can help show you if you need a higher-tier SLA or a potential downgrade if you can get similar performance at a lower price.
Your organization may need various resources to function, and managing how they’re utilized can be more impactful than you may think. Monitoring individual resources per instance (like CPU cycles) is one thing, but you should keep an eye out for the bigger picture, too — are you scaling up and down as necessary? Are there unused instances still spinning up? Are you paying for resources that are never used? All of these questions should be taken into account to optimize your cloud storage costs.
Over-provisioning goes hand-in-hand with resource management and is equally important too. If you’re provisioning large instances that are mostly unused or have more storage capacity that you’re not using, you’re most likely throwing money down the drain. You should be factoring these thoughts into your overall cloud storage strategy to ensure you only pay for what your teams need.
As you can see, there are a ton of different factors that can affect your cloud storage costs. And trying to keep these costs low may not be as obvious as you may initially think, with so many factors at play. Let’s take a look at some of the most common ways your teams can use so they don’t need to bust out their piggy banks:
Analyze your storage. Your teams should assess your data and remove any redundant, unused, or outdated files. Regularly pruning your data can help keep cloud storage costs lower while also making your data easier to parse.
Implement lifecycle management. Setting up policies that can automatically transfer older and less-used data to cheaper storage tiers can be an effective way of managing costs. You should also consider setting up policies around data expiration or deletion as well.
Utilize data compression and deduplication. Rules should be set up to automatically compress data before storing files in the cloud, as they can significantly reduce storage costs. This also helps keep duplicate, redundant files out of storage space.
Use different storage tiers. Setting up multiple tiers and classes based on how often teams need to access data can keep costs low. Anything that needs to be accessed frequently or requires high performance can be stored on more expensive tiers, while less popular data can be pushed to more cost-efficient tiers.
Optimize data transferring. Teams should strive to minimize unnecessary data transfers with incremental backups and only transfer the changed files. You can also set up other techniques like delta encoding or binary diff algorithms to help reduce how much is transferred.
Automate when you can. Automation can help prevent unnecessary costs by provisioning resources on an as-needed basis. You can also do the same in reverse — removing instances once they’re no longer needed, so you only use what you need. This applies to resources, too, as proper monitoring and automation can help you automatically scale these up or down.
Look into budget options. Cost optimization tools, savings plans, and reserved instances can all help trim your budget. Reserved instances and savings plans differ between cloud providers but can offer massive savings when utilized properly.
Keeping cloud storage costs from exceeding budget is becoming increasingly harder, even with these typical approaches. One way developers and QA engineers can contribute to cloud storage cost savings is by reducing the number of test cases executed and, therefore, the amount of test data generated and stored.
Testing can consume a significant portion of the cloud budget due to the time and resources required to run test suites. Traditional testing methods, particularly those involving Selenium, UI, Mobile, and Integration tests, can result in wasted spending when tests pass before a failure is detected.
Launchable's Predictive Test Selection harnesses machine learning to predict which tests are likely to fail based on the incoming commits. This risk-based approach allows teams to run only the tests that are predicted to fail, reducing test execution times and cloud costs without compromising the quality or speed of delivery.
By dynamically generating subsets of tests that are likely to fail, Launchable reduces test execution times in-place while lowering cloud costs, without having to shift left. This approach shortens the feedback time for developers, allowing you to get faster feedback on your changes.
By adopting data-driven testing practices and optimizing the management of your test data, QA and DevOps teams can effectively cut cloud storage costs and ensure efficient use of resources in the cloud environment.