Achieving Near-Zero Downtime and Powering Generative AI Using Amazon EKS with Ada
Customer service automation company Ada migrated its Kubernetes clusters to Amazon EKS and now runs a generative AI reasoning engine for customer conversations, raising automated resolution rates from 20-30 percent with its prior declarative agents to up to 77 percent.
Overview
Customer service automation company Ada migrated its Kubernetes clusters to Amazon EKS and now runs a generative AI reasoning engine for customer conversations, raising automated resolution rates from 20-30 percent with its prior declarative agents to up to 77 percent.
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Inspect the highlighted sourceThe challenge
Ada's self-managed Kubernetes clusters (seven clusters with up to 700 nodes each) were complex and costly to maintain: two or three full-time engineers took up to 5 months to complete a Kubernetes version upgrade, and upgrades consumed up to 30% of the yearly error budget under a 99.9% availability SLA.
The solution
Ada migrated its self-managed Kubernetes clusters to Amazon EKS, using AWS Global Accelerator and a blue/green deployment strategy to incrementally route traffic with near-zero downtime, adopted GPU slicing for its ML inference workloads, used Argo CD to keep application sets in sync, and now runs a generative AI reasoning engine (using ML models and LLM calls) for its customer service automation product.
Reported business value
Ada cut compute costs 15%, increased compute efficiency 30%, increased GPU usage cost efficiency 20%, increased deployment velocity 70%, and cut Kubernetes upgrade time from up to 5 months to 5 days; its shift to a generative AI agent lifted automated resolution rates from 20-30% with declarative agents to up to 77%.
Sources
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