Shutterstock capitalizes on the cloud’s cutting edge

When you store and deliver data at Shutterstock’s scale, the flexibility and elasticity of the cloud is a huge win, freeing you from the burden of costly, high-maintenance data centers. But for the New York-based provider of stock photography, footage, and music, it’s the innovation edge that makes the cloud picture perfect for its business.

“The speed of innovation is really starting to accelerate,” says Jefferson Frazer, director of edge compute, delivery, and storage at Shutterstock, which is headquartered in the Empire State Building. “If you’re not keeping up, you’re getting left behind.”

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

The company, which customizes, sells, and licenses more than one billion images, videos, and music clips from its mammoth catalog stored on AWS and Snowflake to media and marketing companies or any customer requiring digital content, currently stores more than 60 petabytes of objects, assets, and descriptors across its distributed data store.

But it’s the ability to tap sophisticated analytics and AI in the cloud, combined with the “democratization of data” enabled by data lakes, that is not only accelerating innovation at Shutterstock but also facilitating new products and services, Frazer says.

“The expectation from developers is that they can go faster than they’ve ever gone before and that every part of the lifecycle around this data needs to be elastic, scalable,” he says. “Nothing can be held back from giving everyone in your business democratized equal access to this information so they can leverage it to do their part of the job.”

The challenge for any enterprise, he says, is finding a centralized path to access disparate stores.

“We think we found a good balance there. We use Snowflake very heavily as our primary data querying engine to cross all of our distributed boundaries because we pull in from structured and non-structured data stores and flat objects that have no structure,” Frazer says. “Then coupling with AWS’ strong authentication mechanisms, we can say with certainty that we have security and restrictions around who can access data.”

This level of development is very complex and only possible with a skilled CIO who has a deep understanding of all business processes and new cloud technologies as soon as they are made available, Frazer says.

Cloud-first, cloud-fast

Frazer believes Shutterstock CIO Hugues Hervouet has just the right blend of tech know-how and business acumen to pinpoint which parts of the company are using data to its full potential, which could capitalize more, and where opportunities for expansion and cross-functional use reside.  

“Our CIO is particularly invested in pushing forward data consumption,” Frazer says. “As soon as new cloud features come out, they are immediately consumed.”

Hervouet himself says he is driving his developers to innovate faster and develop new classes of applications as soon as new cloud capabilities are released. Shutterstock’s current focus, for instance, is generative AI — considered by many to be a bleeding-edge application.

“We have been able to reallocate engineers to work on value-add activities, such as implementing a generative AI solution that enables our customers to create compelling images using the platform by describing what they are looking for in just a couple of sentences,” Hervouet says, noting this enables customers to find and create content they need much faster.

Frazer says Shutterstock has a dedicated team building AI algorithms and new machine learning models that are integrated into all aspects of the customer lifecycle, such as an engine that learns from customer consumption patterns and makes recommendations. To do so, the team leverages tools from AWS and Databricks, as well as custom Jupyter notebooks.

For Shutterstock, the benefits of AI have been immediately apparent. Storage intelligence, for example, has reduced the duplication of images, an issue that occurs after acquisitions. And generative AI has helped reduce the time required to prepare custom images for customers.

“What we’ve seen from the cloud is being able to adapt to the complexities of different data structures much faster,” Frazer points out. “Previous tasks such as changing a watermark on an image or changing metadata tagging would take months of preparation for the storage and compute we’d need. Now that’s down to a number of hours.”

Shutterstock is also working with OpenAI, using their “models to generate content now trained off of our datasets,” Frazer says.

Optimizing for innovation

Analytics in cloud is also proving key to Shutterstock operations. The company relies on Amazon QuickSight and Athena to add visualizations and perform deep queries on its data to ensure optimal performance across the application lifecycle, Frazer says.

“Analytics doesn’t just stop at performance,” he says. “We want to understand everything that the customer is doing on our website. Why didn’t they click on this button? The customer hovered for two seconds and didn’t click that type of data. That is invaluable when optimizing your site.”

Other services such as Amazon CloudFront enable Shutterstock customers to enhance their content-on-demand networks, and Lambda — a serverless compute service that runs code without having to provision or manage servers — benefits Shutterstock customers wherever they are in the world, he says.

For Shutterstock, the cloud has led to faster innovation, but few enterprises are capable of exploiting sophisticated features out of the gate and ought to proceed cautiously with advanced cloud services, says IDC analyst Dave McCarthy.

While “the cloud gives enterprises access to the latest technologies with the ability to provision new resources in minutes, cloud providers are releasing new capabilities faster than enterprises can consume them,” McCarthy says.

Gartner analyst Arun Chandrasekaran adds that accelerated innovation in the cloud offers a high risk/reward ratio “disruptors can leverage” and creates a dynamic work environment to attract top talent. But there are pitfalls to innovating too quickly, particularly if the enterprise lacks a cohesive strategy and direction, he says.

“It can lead to too much experimentation and lack of clear business value from such projects,” Chandrasekaran says, as well as “potentially lower reliability and more firefighting than true innovation.”

Even those organizations with the talent to tackle cutting-edge technologies in the cloud can be slowed by the nature of their business environments, McCarthy says. “Many companies find themselves in a hybrid architecture where they have one foot in the old world and one in the new,” he says. “That creates some unique challenges in how to manage both environments consistently.”

Still, the drumbeat for innovation marches on. “CIOs need to think of digital transformation in the context of continuous innovation,” McCarthy says. “It should not be considered a one-time exercise, but rather an ongoing process where new technology becomes embedded into the business as it becomes available.”

For Shutterstock, that process is a facet of the company’s culture, thanks to strong IT leadership, a robust cloud infrastructure, a diverse toolset, and talent, Frazer says.