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DataStream Inc: Multi-Cloud Infrastructure Migration
Client: DataStream Inc.Industry: Technology / Data InfrastructureDuration: 5 months
Overview
Migrated DataStream's on-premise data pipeline infrastructure to a multi-cloud architecture on AWS and Azure with zero downtime and 40% cost reduction.
DataStream Inc. provides real-time data streaming and analytics infrastructure to financial services and e-commerce companies. Their platform processes over 5TB of data daily, and their customer base was growing 20% quarter-over-quarter. But DataStream's infrastructure was entirely on-premise — a collection of bare-metal servers in a single colocation facility that had been scaled organically over 6 years. Hardware procurement lead times of 4-6 weeks meant they were constantly firefighting capacity issues. A single facility also meant a single point of failure, a growing concern for their financial services clients who required multi-region redundancy. DataStream needed to migrate to the cloud without any downtime, maintain their strict 99.99% uptime SLA, and ideally reduce their infrastructure costs in the process. KumoDevs designed and executed a multi-cloud migration strategy that moved DataStream from on-premise to a resilient AWS-Azure architecture.
Challenge
DataStream's aging on-premise infrastructure was hitting capacity limits, with hardware lead times causing 4-6 week delays in scaling their data processing pipelines to meet customer demand.
Solution
Designed and executed a multi-cloud migration strategy using AWS for primary compute and Azure for disaster recovery, with automated failover, infrastructure-as-code provisioning, and a 3-phase cutover plan that maintained 100% uptime.
Results
Infrastructure costs reduced by 40% through right-sized cloud resources and reserved instance pricing
Provisioning time for new data pipelines dropped from 6 weeks to 15 minutes
Achieved 99.99% uptime with automated multi-region failover across cloud providers
Key Features
Multi-cloud architecture with AWS as primary compute and Azure as disaster recovery with automated failover
100% infrastructure-as-code via Terraform with reusable modules, code review workflows, and security scanning
Zero-downtime cutover using dual-write pattern with real-time consistency validation dashboards
Kubernetes-based workload orchestration on EKS and AKS with service mesh for cross-cluster communication
Unified observability with Datadog — custom dashboards, SLO tracking, and cross-cloud alerting
Automated CI/CD with GitHub Actions — infrastructure plan validation, cost estimation, and policy-as-code enforcement
Our Approach
KumoDevs took a phased, risk-minimising approach. Phase one was discovery and architecture design: we audited every workload running in DataStream's colo, categorised them by migration complexity, and designed the target architecture on AWS (primary) and Azure (DR). Phase two was the 'parallel runway' — we provisioned the entire target infrastructure using Terraform, set up data replication from on-prem to AWS, and ran the workloads in parallel for 4 weeks to validate correctness and performance. Phase three was the cutover: we used a dual-write pattern where writes went to both old and new systems simultaneously, with real-time comparison dashboards validating consistency. Once validation passed for 72 hours, we switched production traffic to AWS with Azure standing by as hot-standby DR. The entire migration was completed with zero customer-facing downtime.
Process
1
Discovery & Workload Audit
Audited all 60+ workloads running in the colocation facility, mapped dependencies, measured resource utilisation, and categorised migration complexity.
2
Target Architecture Design
Designed the multi-cloud architecture on AWS (primary) and Azure (DR), including network topology, security boundaries, and data flow diagrams.
3
Infrastructure Provisioning
Developed Terraform modules for VPC, EKS, AKS, RDS, Azure SQL, S3, Blob Storage, and observability stacks with policy-as-code validation.
4
Data Replication & Parallel Run
Set up real-time data replication using Kafka MirrorMaker and AWS DMS, ran workloads in parallel for 4 weeks, and validated output consistency with automated comparison tooling.
5
Zero-Downtime Cutover
Executed the dual-write cutover pattern over a weekend, with real-time consistency monitoring, automated rollback procedures, and 24/7 on-call engineering support.
6
Optimisation & Handover
Right-sized cloud resources based on 3 weeks of production metrics, implemented reserved instances and savings plans, and delivered operations runbook with training sessions.
Client Testimonial
“Migrating from on-premise to cloud is one of those projects that keeps CEOs up at night — the risk of downtime, data loss, or performance degradation is terrifying when your customers rely on your platform 24/7. KumoDevs made it look effortless. The zero-downtime cutover was remarkable, and the cost savings were a bonus we didn't fully believe was possible until we saw the first bill.”
Technologies Used
AWSAzureTerraformDockerKubernetesPythonGitHub ActionsDatadog
Screenshots
Technical Details
Infrastructure provisioned entirely through Terraform with reusable modules for VPC networking, Kubernetes clusters, managed databases, and observability stacks on both AWS and Azure. GitHub Actions powers CI/CD with infrastructure plan validation, security scanning, and automated deployment. Kubernetes clusters run on EKS (AWS) and AKS (Azure) with a service mesh for cross-cluster communication. Datadog provides unified monitoring with custom dashboards and alerting across both clouds.
Future Plans
Implement a cloud cost optimisation engine with automatic resource right-sizing recommendations, expand the disaster recovery design to support active-active multi-cloud traffic, and build an internal developer portal for self-service infrastructure provisioning.