Cloud strategy
Target-state architecture, workload placement, and a migration and modernization roadmap tied to your budget and risk profile.
Core Services
Cloud Services
Cloud that runs the business today and is ready for the AI workloads that will run it tomorrow.
The cloud is no longer a destination. It is the operating environment your business runs on, and the foundation every new AI capability depends on. Spruce's Cloud Services practice covers the full lifecycle of enterprise cloud: strategy, migration, modernization, managed operations, and the AI-ready environments that support MLOps, GPU workloads, and production model serving. We work across Azure, AWS, and Google Cloud, and we design for the hybrid and edge environments most of our clients actually run, not the textbook cloud-native ideal. Whether you need a disciplined migration off aging infrastructure, a modernized application platform, a right-sized cost profile, or a cloud environment engineered for your first production AI workload, this is the practice that delivers it.
What our Cloud Services practice covers
Spruce's cloud work spans the decisions and capabilities that keep enterprise IT performing, secure, and ready for what's next:
Migration
Lift-and-shift, re-platform, and re-architect moves to Azure, AWS, and Google Cloud, with parallel running and staged cutovers for risk control.
Application modernization
Refactoring monoliths into services, containerizing workloads, and adopting managed platform services where they pay off.
Managed cloud services
Day-two operations, patching, monitoring, and incident response for the environments we or others have built.
DevOps and platform engineering
CI/CD, infrastructure-as-code, internal developer platforms, and the guardrails that make speed safe.
FinOps and cost optimization
Visibility, forecasting, tagging discipline, and the hard work of right-sizing, reserved-capacity planning, and unused-resource cleanup.
Cloud security foundations
Identity, network segmentation, encryption, and governance, typically anchored in Microsoft Entra in the enterprise environments we build for.
AI-ready cloud
Infrastructure engineered for AI workloads, including MLOps pipelines, GPU compute, and model-serving patterns.
Multi-cloud and hybrid by design
Most enterprise cloud programs span more than one platform, whether by choice or by accident of acquisitions, partner requirements, and data-sovereignty obligations. We design for that reality. Our patterns work on Azure as the primary enterprise anchor, AWS, and Google Cloud, and we design hybrid architectures that keep sensitive data on-premise while allowing compute to scale in the cloud. Where regulatory requirements (CJIS, HIPAA, FedRAMP) or operational distribution (transportation, healthcare delivery, logistics) call for edge deployment, we extend the architecture to the edge as well.
Spruce is platform-agnostic. We hold no reseller or formal partnership commitments to any cloud provider. Our recommendations reflect your workload mix, regulatory environment, and existing skill profile, not a sales quota.
Migration and modernization, without the stalls
Most migration programs stall for the same few reasons: unclear dependencies, underestimated data work, and application debt that the cloud won't magically fix. Our migrations start with a portfolio assessment that surfaces those issues early. We group workloads by migration pattern (retire, retain, rehost, re-platform, refactor), sequence the waves to match your risk tolerance and budget calendar, and run each wave with parallel environments and cutover rehearsals so go-live is a non-event.
Modernization work follows the same discipline. We refactor monoliths into services where the business case is real, containerize workloads on AKS, ECS, or GKE, adopt managed databases where operational burden outweighs portability concerns, and leave the rest alone. The measure of a successful modernization is not how much we changed. It's how much easier the application is to run, extend, and secure a year later.
Managed operations, DevOps, and FinOps
Cloud services don't end at go-live; that's where they start paying back. Our managed-services engagements cover day-two operations, patching, monitoring, incident response, and the governance controls auditors expect, sized to the criticality of the system. We build DevOps practices (CI/CD, infrastructure-as-code, internal developer platforms, policy-as-code) that give your teams speed without sacrificing safety. And we treat cost as a first-class engineering concern:
- Visibility and tagging discipline so spend is attributable to the team, product, and environment that incurred it.
- Forecasting tied to release and growth plans, not last month's invoice.
- Right-sizing, reserved-capacity and savings-plan discipline, and spot mix for elastic workloads.
- Unused-resource detection and cleanup, with guardrails against recurrence.
- Architectural cost reviews, because the biggest savings are design decisions, not knob-twisting.
AI-ready cloud
Production AI lives on infrastructure, and the infrastructure choices you make now will shape what's possible for the next five years. Our AI-ready cloud work stands up environments engineered for real AI workloads:
Cloud architecture for AI workloads
Compute, storage, networking, and model-serving patterns designed for production on Azure OpenAI, Azure AI Foundry, Azure Machine Learning, AWS Bedrock and SageMaker, and Google Vertex AI.
MLOps pipelines and automation
Continuous integration and deployment for models, datasets, and applications, with model registries and lineage tracking.
GPU-based training and inference infrastructure, with cost-optimized use of reserved, spot, and on-demand capacity.
Serverless and containerized AI deployment on Azure Functions, Azure Container Apps, AKS, Kubernetes, AWS Lambda, and Google Cloud Run.
Observability for AI
Monitoring for drift, latency, cost, and accuracy, with feedback loops that capture real-world performance.
Security, identity, and governance controls tailored to your regulatory environment, designed to pass audit, not just check a box.
Security, compliance, and governance
Cloud security is architected in, not bolted on. We build identity-centric designs anchored in Microsoft Entra for enterprise clients, with network segmentation, encryption in transit and at rest, private endpoints, audit logging, and policy-as-code. Our architectures respect HIPAA, FERPA, GLBA, CJIS, SOC 2, FedRAMP, state privacy regimes, and GDPR for global clients. Compliance review is part of every engagement, and the control evidence your auditors ask for is a byproduct of how we operate, not a separate project.
Who we serve
- Public-sector agencies modernizing citizen-facing and back-office systems, often under mandate.
- Enterprise technology leaders consolidating from legacy data centers onto a disciplined multi-cloud footprint.
- Healthcare and financial services organizations that need cloud agility without loosening compliance.
- Education systems supporting distributed learning platforms and administrative systems.
- Transportation and logistics clients operating across edge, hybrid, and cloud environments.
Ready to move forward?
Every Spruce engagement begins with a short conversation about your goals, constraints, and timeline.