Dev and UAT migrated
Better on throughput & RAM
Hardware available on-demand
Overview
E42 needed a Kubernetes-native, high-performance storage environment capable of supporting its growing multi-cloud AI infrastructure. Following a failed deployment with another provider that impacted performance and reliability, the company turned to AceCloud for a solution. AceCloud successfully designed and deployed a scalable, resilient storage architecture that optimized performance, simplified Kubernetes operations, and ensured the reliability needed to power E42’s AI-driven workloads across multiple cloud environments.
Cost, Kubernetes performance, and a support team that actually shows up. This combination made us move our infrastructure to AceCloud.
Use Case
Is heavily dependent on block storage and Kubernetes resources to support high performance compute for AI workloads
Runs every workload on managed Kubernetes, with its entire architecture built around K8s
Operates multi-cloud across AWS, GCP, and now AceCloud
Challenges
An earlier attempt to run Kubernetes workloads on a different provider surfaced persistent block storage instability and performance issues, stalling their rollout before it could scale.
As an AI-native, multi-cloud organization, E42 needed a provider that could match hyperscaler performance without the cost premium attached to it.
Solutions
AceCloud delivered managed Kubernetes infrastructure built for cost efficiency, performance, and reliability at AI scale.
Performative, production-ready K8s that cleared E42’s bar after POC evaluation.
Newer-generation hardware delivers better RAM/CPU performance without the separate enterprise agreements required on GCP.
Stable, high-throughput block storage that resolved the exact reliability gaps that blocked their earlier migration attempt.
Hands-on support that resolved early deployment issues quickly.