Building Your Own Snowflake Optimization Solution Will Cost You More Than You Think

Every IT department faces the “build vs. buy” question at some point. But the question is rarely a strict binary. At some level, all organizations use both approaches. For some use cases, it’s more cost-effective to build. For others, it’s better to buy. 

When it comes to Snowflake optimization solutions, 99% of the time it’s best to buy. Building a solution that’s both automated and adaptable to dynamic cloud environments can be both time- and resource-intensive. At the end of the day, you don’t want to spend more building the solution than it saves you. 

In this article, we’ll walk through some hidden costs of building your own Snowflake optimization solution and how third-party solutions help you overcome them. 

What all goes into building a Snowflake optimization solution? 

Optimizing Snowflake isn’t a one-and-done deal. The cloud is ever-changing, which means the “ideal” state for your Snowflake environment changes with it. Shifting user demands, over- and under-use of specific warehouses, varying query design efficiency—all of these factors (and more) impact Snowflake performance and cost effectiveness. 

As such, any Snowflake optimization solution, whether built or bought, must account for this reality. You can’t just optimize for today. You have to optimize for tomorrow, the next day, and every day after that. 

For example, let’s say you have a warehouse that experiences a sudden uptick in queries. If the warehouse doesn’t have enough resources provisioned to handle those queries, you’ll end up with two problems: increased latency (the query takes longer to run) and query queuing (where new queries wait to be executed until enough resources are available to handle them). 

Depending on the specifics, you can speed up query performance and queuing time by provisioning additional resources. In Snowflake, this means upgrading your warehouses to a larger size (e.g. XS to M). 

However, once user demands revert to their normal state, you don’t want to keep that warehouse running at a larger size and spend credits unnecessarily. So you’ll want to revert the warehouse to its smaller size as quickly as possible. 

And here’s the rub: these surges in user activity can happen at any time, and last for as little as seconds at a time. A human engineer can’t react that quickly, nor can they be on-call 24/7 to handle every single change as it happens. 

But as you can imagine, building a Snowflake optimization solution that’s built to take optimization actions in real time is far more complex than building a machine that just gives advice and recommendations. Here are some of the biggest factors that increase costs: 

• AI/ML model design and training—not only is this time-consuming and data-heavy, but it often requires specialized skill sets that are expensive to hire for, especially if you use advanced techniques like reinforcement learning (RL)
• Acquiring the data needed to accurately train that model to work well in live environments, as well as adequate precautions to protect and secure those data
• Ongoing modifications, retraining, and fine-tuning as your Snowflake environment changes as new data comes in
• Development of optimization features and techniques to account for more instances where you can improve performance and reduce costs

Not only do all of these factors increase overall costs, but they can also take a long time to build and implement. Every day that passes without a solution in place, that’s money you’re leaving on the table. 

Why it’s important to use a third-party Snowflake optimization solution

All told, building your own Snowflake optimization solution can be expensive and time-consuming. But is a third-party solution any better? Yes! And here are some reasons why. 

Pre-trained AI model

The most obvious benefit of using a third-party Snowflake optimization solution is that the AI model is already built and trained to solve your specific problem. And because the third party is able to repackage and scale that model, they can charge you a fraction of what it cost to build it in house. 

Vetted on a variety of use cases

Additionally, a third-party will have a variety of customers and clients that use their model. While you obviously won’t have access to their data (in fact, the third party may not even have that access themselves for security purposes), the model will be trained on a variety of scenarios and datasets.

By learning from more real-world scenarios, the model becomes more adept at making optimization decisions. Additionally, by handling a greater variety of use cases, a pre-trained model is more adept at handling unique situations, which improves its utility across the board. 

More features & functionality

Unlike an IT department within a broader organization, a third-party software company is able to devote the bulk of their resources to product development, these solutions will often have more features and functionality that are beta tested and easy for users to deploy. 

Security & privacy features

Building your own AI model requires large datasets to be trained effectively. However, large datasets can put a target on your back when it comes to security and privacy, which often require costly protection. A third party will often absorb and distribute these costs across their client base, resulting in lower per-user costs. 

Integration with existing in-house infrastructure

If you’ve already built a first-party solution to handle one aspect of Snowflake optimization, that doesn’t mean you should avoid third-party solutions altogether. Remember: it’s all about using the best tools for the best use cases. In fact, if you’re working with a high-quality partner, they should be able to help you find the best way to integrate their technology with yours. 

How to price out a third-party Snowflake optimization solution

Pricing out a third-party Snowflake optimization solution can be tricky, especially if you’re comparing it with the cost of generating your own solution. When you consider not only the hard dollars, but also the opportunity cost of both options, it can feel a bit like you’re comparing apples and oranges. 

Keebo is priced to make that decision a no-brainer. We charge a percentage of the actual dollars you save through Snowflake optimizations. This means that you’re guaranteed an ROI no matter what. 

See how Keebo saves money and boosts performance through real-time, automated Snowflake optimizations here.