How an E-commerce Platform Cut Infrastructure Costs 58% with Zero-Downtime AWS EKS Migration

When RetailHub (name changed for confidentiality) experienced their fastest growth year in 2025, their infrastructure became their biggest constraint.

During their annual Black Friday sale, they had to turn away customers because their legacy infrastructure couldn’t handle the traffic spike. The outage cost them $340,000 in lost revenue in just 6 hours.

The CEO’s directive was clear: “Fix this before next Black Friday. We can’t afford another failure.”

After completing their AWS EKS migration with our team, RetailHub successfully handled 10x their normal traffic during the following Black Friday—with zero downtime and 58% lower infrastructure costs.

This is their transformation story.

Company Background: RetailHub E-commerce

Industry: B2C E-commerce (fashion and accessories) Company size: 180 employees, 45-person engineering team Infrastructure: 40+ microservices, ~120 EC2 instances, AWS-based Revenue: $45M ARR, growing 120% YoY Daily orders: 50,000 average, 500,000+ on peak days Why Kubernetes: Reduce costs, improve scalability, eliminate deployment bottlenecks

Initial challenge: Survive next Black Friday without losing customers

The Breaking Point: Black Friday 2024

What Happened (November 29, 2024)

RetailHub’s Black Friday started strong at midnight. By 2 AM, everything went wrong:

Timeline of the outage:

• 2:00 AM: Traffic reaches 5x normal levels
• 2:15 AM: First EC2 instances start crashing from memory exhaustion
• 2:30 AM: Manual scaling attempted—takes 15 minutes per instance
• 2:45 AM: Database connections maxed out (connection pool not sized for load)
• 3:00 AM: Site completely down—customers see “Service Unavailable”
• 3:30 AM: All-hands emergency response—CEO woken up
• 5:00 AM: Infrastructure scaled up, but damaged instances need rebuilding
• 8:00 AM: Site partially restored with reduced capacity
• 8:30 AM: Full service restored—6 hours of lost revenue

The damage:

• $340,000 in lost Black Friday revenue (estimated from traffic analytics)
• 125,000 customers unable to complete purchases
• 8,400 abandoned carts from frustrated shoppers
• Negative social media backlash (trending on Twitter with #RetailHubDown)
• Trust erosion with customers who switched to competitors
• Team burnout from overnight crisis response

CTO’s assessment:

“Our infrastructure was built for steady-state operations. We had no elastic scaling, no failover strategy, and our deployment process was so slow we couldn’t push fixes during the outage. We need Kubernetes—yesterday.”

The Assessment: Understanding RetailHub’s Infrastructure (Week 1)

Our Kubernetes consulting team conducted a comprehensive infrastructure audit. Here’s what we found:

Critical Infrastructure Problems

1. Manual Scaling—Too Slow for E-commerce

• Current state: Engineers manually launch EC2 instances during traffic spikes
• The problem: Takes 15-20 minutes to scale, by which time customers are gone
• Black Friday impact: Lost 6 hours trying to scale fast enough
• EKS solution: Cluster Autoscaler + HPA scales in 90 seconds automatically

2. Over-Provisioned for Peak, Wasting Money at Trough

• Current state: Running 120 EC2 instances 24/7 to handle potential spikes
• The problem: $18,000/month for capacity used only 5% of the time
• Actual utilization: 15% CPU average, 80% during peaks
• EKS solution: Autoscaling from 20 to 180 pods dynamically, spot instances for cost savings

3. Slow Deployments Blocking Innovation

• Current state: 45 minutes to deploy a single service (CodeDeploy with rolling updates)
• The problem: Can’t do multiple daily releases, slow emergency fixes
• Developer frustration: “By the time deployment finishes, I’ve forgotten what I deployed”
• EKS solution: GitOps with ArgoCD—8 minute automated deployments

4. No Fault Tolerance—Single Points of Failure

• Current state: Services run on single EC2 instances, no health checks
• The problem: Instance crash = service down until manual intervention
• Downtime cost: $12K/hour during business hours
• EKS solution: Multi-pod replicas across AZs, self-healing, automatic restart

5. Monitoring Gaps—Blind During Incidents

• Current state: CloudWatch basic metrics, no application-level observability
• The problem: Can’t diagnose issues fast enough during outages
• Black Friday: Took 90 minutes just to identify the root cause
• EKS solution: Prometheus + Grafana with custom dashboards and pre-configured alerts

Cost Analysis: EC2 vs EKS

Current EC2 infrastructure costs (monthly):

• 120 x m5.xlarge instances (24/7): $14,400
• 8 x r5.2xlarge for high-memory services: $3,200
• NAT Gateways, Load Balancers, Data Transfer: $1,200
• Total: $18,800/month

Projected EKS costs with optimization:

• 20-40 pods normal load, 180 pods peak (80% spot instances): $4,800
• EKS control plane: $144
• NAT Gateways, ALBs optimized: $800
• Monitoring stack (Prometheus, Grafana): $200
• Total: $5,944/month

Savings: $12,856/month (68% reduction)

ROI calculation:

• EKS migration cost: $95,000
• Monthly savings: $12,856
• Payback period: 7.4 months
• 3-year savings: $463,000

The Migration Plan: Zero-Downtime Strategy (Weeks 2-12)

We designed a phased migration approach prioritizing safety and business continuity:

Phase 1: Foundation & Architecture (Weeks 2-4)

Week 2: EKS Cluster Setup

• Designed multi-AZ production cluster (us-east-1a, 1b, 1c)
• Implemented network architecture (VPC, private subnets, security groups)
• Configured autoscaling (Cluster Autoscaler + Horizontal Pod Autoscaler)
• Set up spot instance node groups for 70% of capacity
• Established bastion architecture for secure access

Week 3: Core Infrastructure

• Deployed Istio service mesh for traffic management
• Set up Application Load Balancer with path-based routing
• Implemented AWS Secrets Manager integration
• Configured external-dns for automated DNS management
• Established RDS connection pooling optimizations

Week 4: Observability Stack

• Deployed Prometheus for metrics collection
• Built custom Grafana dashboards for e-commerce KPIs
• Set up Loki for centralized logging
• Configured alerting rules (PagerDuty integration)
• Established distributed tracing with Jaeger

Internal team involvement: DevOps engineers learned Kubernetes fundamentals through hands-on implementation alongside us

Phase 2: Application Containerization (Weeks 5-7)

Week 5-6: Containerize Microservices

• Dockerized all 40+ microservices (Node.js, Python, Java)
• Optimized container images (multi-stage builds, 60% smaller images)
• Created Helm charts for standardized deployments
• Implemented health checks and readiness probes
• Wrote Kubernetes manifests with resource limits

Key optimization: Reduced average container image size from 1.2GB to 480MB through multi-stage builds and Alpine base images

Week 7: Establish GitOps Workflows

• Set up ArgoCD for declarative deployments
• Created Git repository structure for infrastructure-as-code
• Implemented automated sync from Git to cluster
• Built CI/CD pipelines (GitHub Actions → ECR → ArgoCD)
• Configured progressive rollout policies

Developer experience win: Developers now push to Git, ArgoCD handles deployment automatically

Phase 3: Blue-Green Migration (Weeks 8-10)

Migration strategy: Blue-Green for Zero Downtime

Blue Environment (Existing): Legacy EC2 infrastructure Green Environment (New): AWS EKS cluster

Week 8: Migrate Non-Critical Services

• Migrated 15 internal/admin services to EKS
• Tested failover procedures
• Validated monitoring and alerting
• Load tested individual services

Week 9: Migrate Customer-Facing Services

• Migrated 20 customer-facing microservices
• Implemented traffic splitting (90% EC2, 10% EKS initially)
• Monitored performance metrics closely
• Gradually shifted traffic to 50/50, then 100% EKS

Week 10: Complete Migration & Decommission

• Migrated remaining 5 high-risk services (payment, checkout)
• Ran both environments in parallel for 72 hours
• Validated all integration points
• Decommissioned EC2 instances progressively

Critical success factor: Blue-green approach allowed instant rollback if issues emerged (we never needed it)

Phase 4: Optimization & Enablement (Weeks 11-12)

Week 11: Cost & Performance Optimization

• Right-sized pod resource requests and limits
• Configured autoscaling policies based on real traffic patterns
• Implemented pod disruption budgets for high availability
• Tuned spot instance strategies (70% spot, 30% on-demand)
• Optimized database connection pooling

Week 12: Team Enablement & Documentation

• Comprehensive runbooks for common operations
• Disaster recovery procedures and tested failover
• Team training on Kubernetes operations
• Documentation of architecture decisions
• Post-migration support plan

Results: Black Friday 2025 Success

One year after the disastrous Black Friday 2024 outage, RetailHub’s Black Friday 2025 was flawless:

Black Friday 2025 by the Numbers

Traffic handled:

• Peak traffic: 10x normal load (500,000 simultaneous users)
• Orders processed: 485,000 in 24 hours (vs 0 during 2024 outage)
• Downtime: 0 minutes
• Customer complaints: 0 related to performance

Automatic scaling in action:

• Starting pods: 20 (normal load)
• Peak pods: 178 (automatically scaled during traffic surge)
• Scaling time: 90 seconds from traffic spike to additional capacity
• Scaling events: 47 automatic scale-ups and scale-downs throughout the day

Infrastructure costs during Black Friday:

• Previous year (failed): $18,800/month + $340K lost revenue = $358,800 cost
• This year (success): $8,200 for the month (slightly higher due to Black Friday) + $0 lost = $8,200 cost
• Savings: $350,600 (97% reduction including prevented revenue loss)

CEO’s reaction:

“Last year, Black Friday was a nightmare. This year, I slept through it. When I checked in the morning, sales were up 240% from last year and our infrastructure had scaled automatically. That’s the kind of boring reliability I want.”

Beyond Cost Savings: Business Transformation

Developer Velocity Improvements

Before EKS:

• Deploy time: 45 minutes per service
• Deployment frequency: 2-3 times per week
• Failed deployments: 15% (required rollback)
• Hotfix time: 2+ hours
• Developer satisfaction: 3.2/10

After EKS:

• Deploy time: 8 minutes per service
• Deployment frequency: 8-12 times per day
• Failed deployments: 2% (automatic rollback)
• Hotfix time: 15 minutes
• Developer satisfaction: 8.7/10

Developer testimonial:

“I used to dread deployments. Now I deploy multiple times a day without thinking about it. If something breaks, it automatically rolls back. I spend my time building features instead of babysitting deployments.”

Operational Improvements

Reduced manual interventions:

• Before: 3-5 manual scaling events per week
• After: 0—all automatic

Reduced incident response time:

• Before MTTR: 2 hours average
• After MTTR: 12 minutes average
• Improvement: 90% faster recovery

Improved reliability:

• Before uptime: 99.2% (58 hours downtime/year)
• After uptime: 99.95% (4.4 hours downtime/year)
• Customer impact: 92% fewer outages experienced

Business Impact

Revenue growth enabled:

• 2024 revenue: $45M (growth limited by infrastructure)
• 2025 projected revenue: $95M (infrastructure no longer bottleneck)
• Infrastructure now supports: 5x current traffic without redesign

Competitive advantage:

• Faster feature delivery than competitors (8-12 deploys/day)
• Reliable flash sales (competitors still have outages)
• Can test new markets without infrastructure concerns

Organizational confidence:

• Engineering team morale improved dramatically
• Sales team confidently promises uptime SLAs
• Board confidence in technical leadership restored

Cost Breakdown: Final Numbers

Total Migration Investment

Consulting services: $75,000 (architecture + implementation + training) Internal team time: $18,000 (3 engineers, 20% capacity during migration) Infrastructure costs during migration: $12,000 (running both environments in parallel) Tools and software: $2,000 (Terraform, Helm, monitoring tools)

Total migration cost: $107,000

Ongoing Monthly Savings

Before (EC2): $18,800/month After (EKS): $7,500/month Monthly savings: $11,300

Annual savings: $135,600

ROI Calculation

Payback period: 7.9 months 3-year ROI: 380% 5-year savings: $570,000 (infrastructure costs alone)

Not included in ROI calculation but equally valuable:

• Prevented Black Friday 2025 outage: $340K+ saved revenue
• Developer productivity improvement: $200K+ value/year
• Reduced operational overhead: $80K+ value/year
• Customer trust and brand protection: Priceless

Key Technologies & Architecture Decisions

AWS EKS Configuration

Cluster setup:

• Kubernetes version: 1.28
• Multi-AZ deployment: us-east-1a, 1b, 1c
• Node groups: 70% spot instances (c5.xlarge, c5.2xlarge), 30% on-demand for stability
• Autoscaling: 5 minimum nodes, 80 maximum nodes
• Network: Private subnets with NAT Gateways

Why spot instances:

• 70% cost savings on compute
• Stateless microservices tolerate interruptions
• Mixed on-demand/spot ensures stability during spot reclaims
• Never experienced impact from spot termination during production

Service Mesh & Networking

Istio service mesh:

• Automated mTLS between services
• Traffic splitting for canary deployments
• Circuit breaking for fault tolerance
• Distributed tracing integration

Application Load Balancer:

• Path-based routing to services
• SSL termination at ALB
• WAF integration for security
• Health checks for automatic failover

Monitoring & Observability

Prometheus stack:

• 10-second scrape interval
• 30-day metric retention
• Custom metrics for business KPIs (orders/min, cart abandonment, checkout latency)
• Alerting rules for proactive incident detection

Grafana dashboards:

• Business metrics (orders, revenue, customer journey)
• Infrastructure metrics (CPU, memory, network)
• Application metrics (request rate, error rate, latency)
• Cost tracking (spot vs on-demand usage)

Lessons Learned: What Made This Migration Successful

1. Blue-Green Strategy Eliminated Risk

What we did right:

• Ran both environments in parallel for 2 weeks
• Gradually shifted traffic to validate performance
• Could instantly roll back if problems emerged

Why it mattered:

• Zero business disruption during migration
• Built confidence with each successful service migration
• Never had “big bang” moment of risk

2. Spot Instances Require Careful Planning

What we learned:

• 100% spot = risky, 70% spot + 30% on-demand = optimal
• Spread across multiple instance types for diversity
• Pod disruption budgets critical for graceful handling
• Savings worth the complexity (70% compute cost reduction)

Best practice:

• Always run critical pods (payment, checkout) on on-demand nodes
• Use spot instances for scale-out capacity
• Configure autoscaling to backfill with on-demand if spot unavailable

3. Observability Must Come First

What we did right:

• Set up monitoring before migrating applications
• Built dashboards matching existing EC2 dashboards (for comparison)
• Configured alerts before they were needed

Why it mattered:

• Caught performance issues during migration, not in production
• Team trusted metrics when making go-live decisions
• Debugging was 10x faster with proper observability

4. Team Enablement Prevents Consultant Dependency

What we did right:

• Engineers implemented alongside us (learning by doing)
• Comprehensive documentation and runbooks
• Post-migration support for first 30 days

Why it mattered:

• Team fully independent after 3 months
• No ongoing consultant dependency
• Internal expertise enables continuous improvement

When to Migrate to Kubernetes for E-commerce

Based on RetailHub’s experience, migrate to Kubernetes when:

✅ Definitely Migrate If:

1. Traffic is unpredictable or spiky (flash sales, seasonal peaks)
2. Infrastructure costs are growing faster than revenue (over-provisioning for peaks)
3. Deployment velocity is limiting feature releases (slow, manual deployments)
4. Downtime is expensive (>$10K/hour revenue impact)
5. Scaling manually during traffic spikes (operations team bottleneck)
6. Team is large enough to operate Kubernetes (3+ DevOps engineers)

⚠️ Consider Alternatives If:

• Traffic is steady and predictable (simple autoscaling sufficient)
• Infrastructure costs are <$5K/month (migration cost may not justify savings)
• Team is <2 DevOps engineers (operational complexity may exceed benefit)
• Applications are monolithic (containerize first, then migrate)

RetailHub’s situation:

• ✅ Highly spiky traffic (10x on peak days)
• ✅ $18K/month infrastructure waste
• ✅ Deployments blocking releases
• ✅ $12K/hour downtime cost
• ✅ 45-person engineering team

They were ideal candidates for Kubernetes migration.

Get Your Free E-commerce Kubernetes Assessment

Don’t wait for a Black Friday disaster. Get expert guidance on your Kubernetes migration.

Our AWS EKS consulting team offers a free migration assessment that includes:

✅ Infrastructure audit – We analyze your current AWS setup and traffic patterns ✅ Cost analysis – Detailed breakdown of EC2 vs EKS costs for your workload ✅ Migration roadmap – Phased plan with zero-downtime strategy ✅ Risk assessment – Identify potential issues before migration ✅ ROI calculation – Business case with payback period ✅ Fixed-price proposal – Know your costs upfront

Schedule your free assessment →

Or book a 30-minute consultation to discuss your e-commerce infrastructure challenges.

Three EKS Migration Options for E-commerce

1. Full-Service Migration ($75K - $180K)

Best for: Teams with no Kubernetes experience, complex microservices architecture

• We design and implement your entire EKS infrastructure
• Blue-green migration with zero downtime
• Complete observability stack setup
• Post-migration support and optimization
• Team training and knowledge transfer

Timeline: 10-16 weeks Risk level: Very low (<2% failure rate)

2. Hybrid Migration ($40K - $100K)

Best for: Teams with container experience, moderate complexity

• We design production-ready EKS architecture
• Your team implements with our oversight
• We handle complex components (service mesh, monitoring, autoscaling)
• Weekly check-ins and code reviews

Timeline: 16-24 weeks Risk level: Low (5% failure rate)

3. Architecture + Advisory ($20K - $50K)

Best for: Experienced teams who need validation

• We design your EKS architecture
• Your team executes migration independently
• Monthly check-ins and troubleshooting support
• On-demand help when stuck

Timeline: 24-36 weeks Risk level: Moderate (requires strong internal team)

Not sure which is right? Our free assessment recommends the best approach for your situation.

Related Resources

• Kubernetes Consulting Services: Complete Guide
• AWS EKS Architecture Best Practices
• Kubernetes Cost Optimization Strategies
• Cloud Migration Services
• DevOps Consulting

Questions about your migration? Our team has successfully migrated 80+ e-commerce platforms to Kubernetes. Let’s talk →