Cloud Fabric
Compute, storage, managed K8s, GPUaaS, and multi-cloud management across on-prem, public cloud, and edge — with FinOps and IaC.
What Cloud Fabric is
The Cloud Fabric unifies compute, storage, AI acceleration, data platforms, and security controls into one hybrid operating model — on-premise infrastructure, public cloud resources, and edge locations managed under a single policy and tooling plane rather than three separate estates with distinct procurement cycles, cost models, and operational tools. Infrastructure is provisioned as code from day one, GPU accelerators are available on demand for AI/ML workloads without capital commitment, FinOps controls provide per-workload and per-team cost visibility that prevents bill shock, and sovereign India-located zones accommodate workloads with data residency requirements. We operate the platform so your engineering team deploys and scales applications rather than patching hypervisors and managing storage controllers through maintenance windows.
How Cloud Fabric is composed
The Cloud Fabric is where workloads run. It brings on-premise infrastructure, public cloud tenancy and edge locations under one operating model, so that a decision about where a workload lives is a design decision rather than a procurement consequence.
Compute, storage and orchestration
Virtual and bare-metal compute, block and object storage, and managed Kubernetes, provisioned as code rather than ticketed. Cluster upgrades and node pools are handled inside the platform maintenance window.
GPU and AI platform services
GPU acceleration on demand for training and inference, notebook workspaces for the data science team, and the data integration and governance layer that feeds models. Capacity is drawn on per workload instead of being bought and left idle between projects.
Sovereign and residency-constrained zones
Cloud regions located in India for workloads that carry residency obligations under Indian regulation, with the same tooling and operating model as an unrestricted public region so the residency choice does not force a separate stack.
Multi-cloud management and FinOps
A single management plane across AWS, Azure and Google Cloud, with per-workload and per-team cost attribution. Cost visibility sits with the consuming team, which is what makes spend a design input rather than a monthly surprise.
Platform engineering and DevOps
CI/CD pipelines, infrastructure as code, environment promotion and secrets handling as a managed platform, so application teams ship through a governed path instead of maintaining their own deployment scripts.
Resilience and continuity
Backup, replication and disaster recovery designed against a stated recovery objective, with the failover path tested on a schedule. An untested recovery plan is a document, not a capability.
How we run it
Design is the smaller half of the work. These are the operating practices that keep Cloud Fabric behaving as designed once it is live.
Patch and version management
Hypervisor, container runtime, Kubernetes and managed service versions are kept current on a defined cadence with rollback paths prepared, so a security patch is routine work rather than an outage risk deferred indefinitely.
Capacity and cost review
Consumption against forecast is reviewed with the cost attribution data each cycle. Rightsizing, reservation purchase and architectural change are proposed as options with numbers attached.
Migration and modernisation sequencing
Migrations run in waves with the dependency graph mapped first, so workloads move in an order that keeps each wave independently verifiable and reversible.
FinOps governance
Budgets, tagging standards and anomaly alerts are enforced at the platform level. Untagged or unowned resources surface as exceptions rather than accumulating quietly in the bill.
Products on Cloud Fabric
Each product is available as a managed service on this fabric.
AI Cloud Platform
View productEnterprise Cloud
View productMulti-Cloud Management
View productGPU as a Service
View productCloud Consulting
View productCloud Migration & Modernization
View productCloud Managed Services
View productCloud Implementation
View productDisaster Recovery
View productDevOps
View productExpert AWS Solutions
View productAWS Migration
View productAWS AI Services
View productAWS Storage
View productAWS for SMB
View productAWS CloudOps
View productAWS Well-Architected Review
View productGoogle Cloud Platform
View productGoogle Workspace
View productMicrosoft Azure Services
View productMicrosoft 365
View productFrequently asked questions
Can we keep workloads on-premise and still use the Cloud Fabric?
Yes, and most customers do. The fabric is a single operating model across on-premise, public cloud and edge, not a mandate to move everything. Workloads with residency constraints, high-throughput data gravity or legacy integration requirements commonly stay where they are while the rest moves or stays hybrid.
How is GPU capacity provisioned for AI workloads?
GPU capacity is drawn on per workload rather than purchased as standing infrastructure. Training runs and inference services get capacity for the period they need it, which suits the burst pattern that most model work follows. For teams with a steady inference load we will size dedicated capacity and show you where the crossover sits.
Do you take over an existing cloud tenancy, or is this greenfield only?
Existing tenancies are onboarded. We start with an assessment of what is running, how it is tagged and where the cost concentrates, then bring it under the management plane without a forced rebuild. Resources that should not be rebuilt are left alone; the ones that are costing more than they return are proposed for change with the numbers shown.
Who holds responsibility for the cloud provider relationship?
We do. Support cases, architecture reviews and commitment planning with AWS, Azure or Google Cloud sit with us. Your team deals with the platform and the applications on it, and the hyperscaler conversations happen on our side of the line.
Architect on the right fabric
Tell us your workload — we will map the right products across the fabric.