Why Migrate to Valohai?

TL;DR: Migrate to Valohai in phases starting with one high-impact project. Most organizations see 50% faster experimentation within weeks and achieve full adoption in 3-6 months. Zero vendor lock-in and your code stays yours.

Why Teams Migrate to Valohai

Your ML teams are likely battling at least one of these challenges:

Infrastructure Overhead Is Killing Productivity

• Data scientists spending 40% of time on DevOps tasks

• "Works on my machine" blocking production deployments

• Each team maintaining their own MLOps stack

• Cloud costs spiraling due to idle resources

Experiments Aren't Reproducible

• Can't recreate that model from 6 months ago

• Missing dependency versions breaking reruns

• Audit requirements forcing manual documentation

• Teams re-running identical experiments unknowingly

Scaling Hits a Wall

• Single-machine limits blocking larger experiments

• Manual provisioning creating bottlenecks

• No resource sharing between teams

• Every new project starts from zero

Teams Can't Collaborate Effectively

• Models trapped in individual laptops

• No standard deployment pipeline

• Knowledge lost when people leave

• Integration nightmares between team tools

The Strategic Migration Path

Phase 1: Prove Value Fast (Weeks 1-4)

Start with one team's biggest pain point. Get a working project in hours, not weeks.

Choose Your Pilot:

• High-impact project with clear metrics

• 3-5 person team eager for better tools

• Existing code that runs today

Success Looks Like:

• First execution running within 2 hours

• 50% reduction in experiment setup time

• Zero infrastructure debugging by data scientists

• Team asking "can we migrate more projects?"

Deliverables:

• Working project with automated tracking

• Before/after metrics showing time saved

• Initial cost analysis

• Team testimonial for internal buy-in

Phase 2: Standardize Your Workflows (Months 2-3)

Scale what works. Move from individual wins to team transformation.

Expand Scope:

• Full project lifecycle (data → training → deployment)

• Advanced features (pipelines, hyperparameter optimization)

• Team-wide best practices

Success Metrics:

• All team projects using Valohai

• 70% reduction in "plumbing" work

• Models deploying in hours, not weeks

• 30% infrastructure cost reduction

Deliverables:

• Reusable templates for common workflows

• Automated CI/CD pipelines

• Team playbook documented

• Quarterly cost savings report

Phase 3: Scale Across the Organization (Months 4-6)

Transform ML from cost center to innovation engine.

Organization-Wide Impact:

• All ML teams onboarded

• Cross-team model sharing

• Enterprise governance active

• Executive visibility enabled

Success Metrics:

• 60% faster model delivery to production

• 90% experiment reproducibility

• Full compliance audit trail

• 50% reduction in total ML infrastructure costs

Common Migration Scenarios

"We Need to Replace Our Existing Platform"

Your current platform promised the world but delivered complexity.

Migration Strategy:

• Run Valohai parallel to existing platform

• Migrate your most painful workflows first

• Compare metrics side-by-side

• Sunset old platform once value proven

Timeline: 2-3 months for complete transition

"We're Drowning in Tool Sprawl"

Different teams, different tools, zero standardization.

Migration Strategy:

• Map current tool landscape and overlaps

• Identify common workflows across teams

• Replace tool-by-tool with unified platform

• Calculate maintenance hours saved

Timeline: 3-4 months to consolidate

"We Can't Get Models to Production"

Research breakthroughs dying in deployment purgatory.

Migration Strategy:

• Start with research workflow

• Add deployment in same platform

• No handoffs between teams

• Measure time-to-production improvement

Timeline: 1-2 months for first production model

"We're Starting Our ML Journey"

Green field opportunity to build it right.

Migration Strategy:

• Implement best practices from day one

• Avoid accumulating technical debt

• Scale gradually as team grows

• Learn from others' mistakes

Timeline: Immediate value, scales with growth

Addressing Executive Concerns

"What About Lock-In?"

Reality Check:

• Your code runs unchanged—no Valohai SDK required

• Standard Docker, Git, and YAML throughout

• Full API access to export everything

Your migration path out is as easy as your path in.

"How Do We Justify the Investment?"

Measurable Returns:

Month 1:

• 50% reduction in experiment setup time

• Infrastructure debugging eliminated

• First cost optimizations visible

Months 2-3:

• 30-50% infrastructure cost reduction

• 2x faster development cycles

• Tool consolidation savings

Months 4+:

• 60% faster time-to-market

• 5x improvement in asset reuse

• Complete compliance coverage

"Will Our Teams Actually Adopt This?"

Why Teams Love Valohai:

• Keep using familiar tools (Python, notebooks, Git)

• No new languages or frameworks

• Less time on plumbing, more on ML

• Success spreads organically

Early adopters become internal champions.

"What If Something Goes Wrong?"

Risk Mitigation Built In:

• Enterprise SLAs with 24/7 support (by separate agreement)

• Gradual migration reduces risk

• Your code remains portable

• Professional services available

Making the Decision

Key Decision Factors

Cost of Delay: Every month without proper ML infrastructure costs you:

• Lost innovation opportunities

• Accumulated technical debt

• Growing compliance risk

• Widening competitive gap

Why Valohai Over Alternatives:

• Only true bring-your-own-code platform

• Managed service = zero maintenance

• Proven with enterprises like yours

• Scales from startup to enterprise

Next Steps

1. Technical Validation

   • Review the technical migration guide

   • Run proof-of-concept with pilot team

   • Benchmark against current setup

2. Business Case Development

   • Calculate current infrastructure + maintenance costs

   • Estimate productivity gains from metrics above

   • Factor in compliance and risk reduction

3. Get Expert Input

   • Schedule migration assessment with Valohai

   • Connect with similar organizations who've migrated

   • Review security and compliance requirements

---

Ready to transform your ML operations? Start with our technical migration guide or contact our team at [email protected] for a migration assessment.