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E42 gets Hyperscaler-Grade Kubernetes Performance at a Fraction of the Cost
From a stalled Kubernetes rollout to a stable, scalable AI infrastructure with AceCloud.
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
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.
