Amazon Athena - Capacity reservations
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Capacity reservations introduces a new billing model and feature that allow customers to reserve, assign, and manage dedicated query processing capacity for their workloads at any scale. Athena is ranked #24 of 200 most trafficked AWS service.
My team’s vision for this feature is to help our customers:
Improve performance in their workloads
Control cost with hourly pricing and have a more predictable monthly bill
Timeframe:
May 2022 - November 2022; Launched GA, April 2023
August 2023 - November 2023: Launched integration with Amazon CloudWatch metrics (Observability), November 2023
IMPACT
Crossed $1 million annual revenue run rate threshold within 6 months
Drove end-to-end user journeys for GA and future vision
Influenced engineering and product decisions
#1 key topic in customer meetings
THE PROBLEM
Only have on-demand billing model
Charged based on amount of data scanned per query
Struggle to forecast monthly spending and predictable performance
THE SOLUTION
New pricing plan – billed at a flat, hourly rate
Performance-focused customers can ensure important workloads have capacity and can maintain a desired level of performance
Cost-focused customers can control cost with hourly pricing and have a more predictable monthly bill
MULTIPLE USER FLOWS BUILT
Create
Add Workgroups
Remove Workgroups
Add / Remove DPUs
Cancel
EXAMPLE SCREENS IN PRODUCTION
CHALLENGES
Learning technical constraints and negotiating with engineering team
Learning how to design for data visualization - it’s a different skillset
Using metaphors on how we designed our experience to get stakeholder buy-in
Working around technical limitations and exploring multiple solutions
IF I HAD MORE TIME…
Recommendation system using AI to analyze workloads
WHAT I LEARNED
Continue to question and learn more about why something may not work - especially on a technical level
Continue to push engineering to raise the bar on user experience
How to design and critique for data visualization graphs