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Tailor Brands is an automated platform that uses AI to enable small businesses to launch and run their business, starting with a logo and branding, and includes all of their online presence such as domain, website, business mailbox, social media assets, and more. The system simply requires answering a few questions on the company’s user-focused website. Over 26,000,000 companies currently use the service.
The AI system learns from every customer. It uses their likes, dislikes, and adjustments to fine-tune what it offers similar customers with similar businesses the next time the platform is used. The AI technology ensures all the assets are high-quality, professional, and unique to the customer.
Tailor Brands is a tech-savvy company that does most of its own development work and has plenty of in-house technical expertise in its engineering team of 30 people. The company has a strong DevOps culture and a focus on fast product development and improvement, with system updates happening multiple times a day.
The company wanted to get the most out of its team. So, to avoid wasting staff time on everyday maintenance, the company turned to Amazon Web Services (AWS).
For specialized projects, Tailor Brands chose to work with AWS Advanced Consulting partner DoiT International. DoiT offered deep cloud expertise and helped the company get the most cost-effective use from its AWS investment.
“We do look at lots of new AWS services as they launch,” says Nadav Shatz, chief technology officer at Tailor Brands. “But DoiT’s knowledge and insight is really valuable.”
“They have a broader view, with lots of clients in different scenarios so it’s really helpful, especially if we’re starting something new,” he adds.
Tailor Brands has a relatively small technical team so it is important that they can concentrate on business and application development and not waste time on day-to-day infrastructure issues.
DoiT recently helped Tailor Brands move most of their Amazon Elastic Compute Cloud (Amazon EC2) workloads to Amazon EC2 Spot Instances (Spot Instances) to improve efficiencies and reduce costs.
It was a big project that covered multiple production environments. Today, most of Tailor Brands’ computing is done using cost-effective Spot Instances. DoiT and Tailor Brands worked together to achieve a smooth migration to Spot Instances from more expensive on-demand instances.
The project achieved a cost reduction of 35 percent for the company at time of deployment, with hopes for even higher reductions as the system is fine-tuned.
DoiT has also helped with operational expenditure by providing tools to give Tailor Brands improved transparency into its AWS spending.
DoiT worked with the Tailor Brands finance team to use monitoring tools including Amazon CloudWatch (CloudWatch) and CloudHealth for AWS. This means they can warn engineering teams about excessive expenditures in specific areas rather than just making a general statement that costs are too high.
The team can dig into why figures are high for that period and provide the details for an informed conversation, enabling them to consider what can be done to reduce costs without disrupting performance or product development. This helps make sure the company is making the best use of different AWS instance types to get the best value for its money.
Being part of the DoiT portfolio also improves Tailor Brands’ access to AWS support and helps determine which issues are better dealt with internally and which would benefit from AWS guidance.
As a web-based business, Tailor Brands experiences fluctuating demand. So basing its infrastructure on AWS means not having to worry about having insufficient capacity to meet unexpected peaks in demand.
Tailor Brands runs most of its systems on Amazon Elastic Kubernetes Service (Amazon EKS).
It uses Amazon EKS to manage clusters, something it previously did on its own but found to be a burden on the team. Moving its development functions to Amazon EKS has given its engineers low-cost access to a production-like environment.
Tailor Brands relies on Amazon ElastiCache to reduce request demands on its databases. The company uses Amazon Athena running on Amazon Simple Storage Service (Amazon S3) as part of its data lake. It also uses Amazon Redshift for deeper analytical work and Amazon SageMaker for machine-learning programming.
Tailor Brands keeps a close eye on SageMaker and other AWS machine-learning services with the aim of exploring a move to more managed services. This will reduce management overhead and focus everyone on business value.
It is also evaluating AQUA (Advanced Query Accelerator) for Amazon Redshift (AQUA), which is a hardware-accelerated cache that can speed up some queries by as much as 10 times.
Tailor Brands is increasing its use of machine learning to further refine its customer offerings and improve its one-stop-shop business services. Its systems constantly analyze how users customize their assets. The company uses that data to inform and fine-tune the next iteration of its design and personalization engine.
Moving forward, Tailor Brands wants to expand the number of services it provides to small businesses. It also aims to improve existing offerings that include website design, social media marketing, printing services, and other marketing support.
Having already achieved savings of 35 percent thanks to more strategic purchasing of Spot Instances, Tailor Brands now has the tools for closer analysis of its spending in close to real-time that should lead to an ever greater return on their AWS investment.
The company is also considering offering its own customers access to the sort of analytics it has been using internally as a separate business service.
“We use AWS because it provides expert services and frees us from the routine tasks of managing our tech to focus on higher-value matters for the business,” says Shatz.
