Trax is the driving force of the store of the future. The world’s top consumer goods companies and retailers use the Trax cloud platform to gain the power to see what happens at shelf and the agility to delight shoppers in new ways. Armed with Trax data and insights, retailers gain granular, SKU-level visibility to changing store conditions. Trax is a global company with hubs in the United States, Singapore, China, France and Israel, serving customers in more than 90 countries worldwide.

The Challenge


Trax operates a complex, multi-cloud platform that currently runs on both AWS and Google Cloud. The company has several accounts on each cloud. The environments themselves are complicated, with Kubernetes clusters and numerous microservices. There are a lot of moving parts that are not easily tracked. The cloud providers’ native tools fall short of Trax Retail’s needs to closely manage cloud costs at the workload level.

The Solution


Anodot for Cloud Costs Management provides the ability to measure the different workloads that happen inside a single server in the cloud. This allows Trax to measure a critical KPI, the “cost per image processing,” which shows how effectively the Trax system is operating. Anodot Cloud delivers real-time alerts for unexpected changes in cloud usage and recommendations for cost savings.

Key Use Case Drove Requirements for a Cloud Cost Monitoring Tool


A key function of the Trax platform is to take photos of store shelves, upload the images to the cloud, process them through various engines, and deliver information back to the customer. This gives rise to one of Trax Retail’s most important KPIs: the cost to process each of those images. This cost is calculated based on the time it takes to run various applications in the cloud, i.e., cloud usage. With large volumes of images processed every day, this system represents a large source of Trax’s cloud costs.

Mark Serdze is Director of Cloud Infrastructure at Trax Retail. Serdze says that when they began looking for a cloud cost management tool, they were very focused on this particular use case. “This KPI gives us a good idea of how effectively our system operates,” he says. “When we moved into Kubernetes, because of the way this platform operates as a cluster with scaling up and down, we lost the ability to break down the billing through the native cloud tools. We used to invest a lot in tracking instances but we never had an ability to measure the different workloads that happen inside a single server in the cloud.”

Serdze says this was the main motivation behind looking at Anodot Cloud. “Getting to the level of detail that we need is just part of what this tool offers. In the end, Anodot Cloud won our business,” says Serdze. “In addition to meeting our requirements really well, Anodot Cloud is a SaaS offering, so we didn’t need to install and maintain any kind of infrastructure within our cloud environment. Also, Anodot can keep up with our crazy scale usage patterns. We crashed the other tool with our large volume of images.”

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Cloud Cost Monitoring is Critical to the Business


Serdze calls cloud cost monitoring “super critical” to Trax Retail’s business. “One aspect of our business is to replace manual in-store labor at various retailers with our automated solution. Anodot Cloud is an AI-based automated solution. We constantly need to make sure that whatever algorithms we develop can be operated in the most efficient way, cost wise, so it is crucial for us to track them,” says Serdze. 

Anodot Cloud allows Trax to monitor cloud costs in a very granular way. “Anodot can detect in real time the anomalies in different services and new deployments that, for example, affect costs of specific microservices,” according to Serdze. “In contrast, the native tools from the cloud providers don’t give as much visibility. We can monitor our services but only retroactively and not with the level of granularity that we want.”

The Benefits Are Myriad


There are several teams within Trax Retail that are the main users of Anodot Cloud. The infrastructure team does the day-to-day tracking of cloud costs and resources. The data services team implements the API connections. “In general, Anodot Cloud allows us to be more responsive to trends because the data is more updated and live than what we were previously used to,” says Serdze. “In the past we would pull this data and aggregate it once per month. Now we are doing it continuously. Mostly it reduces the toll on our DevOps team and allows us to focus on optimizing our production environment rather than creating cost tracking systems.”

Serdze says there is one key thing they can do with Anodot Cloud that they could not do before. “The most important thing is that we can connect between the usage patterns of our microservices inside the Kubernetes clusters and their actual costs, which is something that’s very hard to do in the native cloud tools.”

Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

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