cluster
Cloud Migration
Moving AI workloads off hyperscalers: AWS exit paths, expired-credit playbooks and bring-your-own-cloud questions.
17 articles
Subclusters
Articles
May 11, 2026
Egress Fees: The Hidden Cost of GPU Cloud Infrastructure
You provisioned an H100 cluster based on the hourly rate. Then the invoice arrived, and data transfer charges had overtaken your compute estimate. Here is how to model the true cost of AI infrastructure.
May 7, 2026
Migrate ML Workloads from Legacy Clouds to an EU GPU Cloud
Hyperscaler credits expiring? Facing constrained GPU capacity and high egress fees? AI startups are moving to sovereign European infrastructure to regain control over costs and compliance.
May 6, 2026
Hyperscaler Credits Expired: Next Steps for AI Startups
Your first year of subsidized GPU compute masked the true cost of your infrastructure. When those credits expire, unit economics become your immediate engineering priority. This guide breaks down the technical roadmap for migrating workloads and securing GDPR-compliant compute.
May 5, 2026
Surviving the GPU Cloud Cost Cliff: Transitioning from Startup Credits to Paid Infrastructure
Startup cloud credits mask the true cost of AI infrastructure. When those subsidies expire, engineering teams face a significant challenge: hyperscaler GPU pricing is unsustainable for continuous training and inference workloads.
May 4, 2026
Hyperscaler GPU Alternatives in Europe: The Infrastructure Guide
Expiring cloud credits and chronically underused GPU capacity are breaking unit economics for AI startups. Engineering leaders are migrating to specialized European infrastructure to cut costs and guarantee GDPR compliance.
May 2, 2026
The AWS SageMaker Alternative: EU Sovereign GPU Infrastructure
European AI teams face a dual mandate: scale model deployment while navigating strict EU data sovereignty laws. Relying on US-based hyperscaler ML platforms exposes organizations to unsustainable costs and compliance risks.
May 2, 2026
Azure GPU Pricing Alternatives 2026
The initial wave of hyperscaler credits has dried up. Discover how AI startups are cutting compute costs while maintaining strict EU data sovereignty.
February 23, 2026
AWS Credits Expired: A Strategic Guide for AI Infrastructure
When AWS Activate credits vanish, AI startups often face a sharp spike in infrastructure costs overnight. Transitioning from subsidized compute to a sustainable COGS model requires a fundamental shift in how ML engineers manage GPU orchestration and data residency.
February 23, 2026
Egress Fees GPU Cloud Comparison: The Hidden Cost of AI
For AI teams, the sticker price of a GPU hour is often a distraction from the true cost of operations. Egress fees can add thousands of dollars to a single month of moving massive datasets or model weights between providers, creating a financial moat that stifles multi-cloud flexibility.
February 23, 2026
The Engineer's Guide to GPU Clouds with No Egress Fees
Egress fees are a quiet line item on an AI project's budget, and they create a financial barrier to data mobility. For ML teams moving terabytes of checkpoints and datasets, choosing a GPU cloud with no egress fees is a strategic necessity for maintaining cost-efficiency and operational flexibility.
February 23, 2026
ML Training Without AWS: A Guide to Sovereign GPU Infrastructure
Hyperscalers often trap ML teams with high egress fees and complex orchestration that leads to chronically low GPU utilization. Transitioning to a sovereign GPU cloud allows for better resource efficiency, support for GDPR compliance, and a significant reduction in the total cost of compute.
February 23, 2026
Best Startup GPU Credits Alternatives for Scaling AI Infrastructure
Hyperscaler credits eventually expire, leaving AI startups with massive bills and inefficient infrastructure. Discover how to transition to specialized GPU clouds that offer better utilization, data sovereignty, and predictable costs.
February 23, 2026
Switching from AWS to a European GPU Cloud: A Technical Guide
Many AI teams find themselves locked into AWS due to initial credits, only to face recurring egress fees and utilization waste later. Transitioning to a European GPU cloud like Lyceum offers higher utilization and European data centers in Spain, Paris and the Nordics, without the hyperscaler tax.
February 13, 2026
Migrating from AWS to Dedicated GPUs: A Performance and Cost Guide
Legacy cloud providers often throttle high-performance workloads through hypervisor overhead and restrictive orchestration. For AI engineers, migrating to dedicated GPUs is no longer just a cost-saving measure; it is a technical necessity to unlock the full throughput of H100 and B200 clusters.
February 11, 2026
Beyond the Big Three: Optimizing ML Training on Alternative Clouds
Legacy hyperscalers charge a premium for general-purpose infrastructure that often leaves GPUs idle and budgets drained. Moving to specialized ML infrastructure reduces egress fees and eliminates the DevOps tax while maximizing hardware efficiency for large-scale training runs.
February 9, 2026
High-Performance Alternatives to AWS SageMaker for AI Teams
Managed ML platforms often trade performance for convenience, leading to ballooning costs and vendor lock-in. For AI-first startups, moving to a specialized European GPU cloud can materially reduce compute spend while raising hardware utilization.
February 6, 2026
AWS Credits Expired? High-Performance GPU Alternatives for AI Startups
The AWS Activate cliff is a silent killer for AI-first startups. When those six-figure credits vanish, the reality of hyperscaler margins and egress fees can stall your model development indefinitely.