Direct Advisory: hello@sorami.com.au
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Sorami Consulting
Australian Proprietary Company · Specialist Systems Engineering

Cloud platforms and Kubernetes model inference clusters.

Sorami Consulting designs and deploys resilient cloud systems, production Kubernetes platforms, and private GPU inference infrastructure directly across customer-owned cloud environments.

Deployment Model Customer Cloud & VPC Isolation
Container Runtimes Kubernetes (EKS, GKE, AKS, Talos)
Inference Engine Stack vLLM, Triton, KServe, GPU Operators
Delivery Leadership Direct Principal Systems Engineers
Core Capabilities

Specialist engineering for modern systems.

We bridge cloud architecture and production model deployment. We design infrastructure that keeps customer data inside their perimeter, optimizes compute spend, and delivers verifiable system reliability.

Customer-Cloud Model Inference

Deploy private, high-throughput model inference clusters into customer VPCs across AWS, GCP, and Azure. Zero outbound data leakage, GPU resource scheduling, and continuous batching.

  • vLLM, NVIDIA Triton, and KServe runtime deployments
  • Multi-Instance GPU (MIG) bin-packing & autoscaling
  • VPC endpoint isolation & private model registries

Kubernetes Platform Engineering

Production-grade cluster design, GitOps delivery automation, and security hardening for mission-critical microservice environments.

  • Automated cluster provisioning via Terraform / OpenTofu
  • ArgoCD GitOps pipelines with continuous policy controls
  • Comprehensive Prometheus, Grafana, and OpenTelemetry

Enterprise Cloud Architecture & Governance

Strategic cloud foundations, multi-account landing zones, infrastructure cost containment (FinOps), and architectural assurance.

  • Enterprise cloud landing zones (AWS Control Tower, GCP)
  • GPU and cloud compute unit-economics optimization
  • Architecture review and technology operating models
Service Taxonomy

Clear deliverables. Verifiable outcomes.

Consulting engagements should never be ambiguous. We define explicit architectural deliverables, technology stacks, and operational outcomes from day one.

Engagement Pillar Core Technical Scope & Deliverables Production Value
Private Model Inference Platform
vLLM · Triton · NVIDIA GPU Operator
Containerized model serving deployed on customer-hosted Kubernetes (EKS/GKE). Configuration of continuous batching, PagedAttention, KV-cache sizing, and model weight ingestion pipelines from private storage buckets. Zero Data Leakage: Customer queries and proprietary model weights remain strictly inside the customer's cloud boundary.
Multi-Tenant GPU Orchestration
Karpenter · KEDA · MIG Slicing
Automated GPU node provisioning, spot instance lifecycle management, and Multi-Instance GPU (MIG) slicing to maximize hardware utilization across batch and interactive workloads. Cost Predictability: Eliminates idle GPU waste with demand-driven node scaling and fast spin-down.
Kubernetes Platform Foundation
Terraform · ArgoCD · Cilium
Turnkey Infrastructure-as-Code for production Kubernetes clusters. Implements eBPF network security (Cilium), zero-trust pod egress controls, and automated GitOps release workflows. Audit-Ready Security: Complete infrastructure reproducibility with cryptographic versioning in Git.
Inference Observability & SLOs
Prometheus · OpenTelemetry · Grafana
Granular metrics instrumentation tracking Time-To-First-Token (TTFT), tokens-per-second, GPU memory saturation, queue latency, and automated model health probes. Operational Visibility: Real-time alerting on inference degradation before client SLA breaches occur.
Architecture Spotlight

Model inference inside customer-owned cloud environments.

When enterprise clients have stringent compliance, data sovereignty, or intellectual property constraints, proxying inference through third-party SaaS APIs is prohibited. We engineer the self-hosted inference plane.

1. VPC & Boundary Isolation

Inference clusters are provisioned inside the customer's private subnets with strict security group isolation. Ingress routes through private network load balancers; all public egress is denied by default.

2. Runtime Optimization

Deploying open-weights architectures on vLLM and Triton Inference Server, configured for optimal tensor parallelism, flash attention kernels, and quantized model formats (AWQ, FP8, GPTQ).

3. Automated Scaling & Autoscaling

Node-level autoscaling tied directly to pending inference queue depths using KEDA and Karpenter, scaling GPU instances down to zero during off-peak windows.

Need to deploy an inference layer on customer infrastructure?

We provide structured scoping to review your client's target cloud provider, compute tier availability (A100, H100, L40S, or T4), network topology requirements, and target latency thresholds.

Operating Model

Senior engineering discipline without agency layers.

We maintain a direct engagement model. Clients collaborate directly with specialist systems architects who design and implement the technical deliverables.

Practice Area

Cloud & Infrastructure Architecture

Specialist engineering across distributed cloud systems, production Kubernetes platforms, multi-cloud landing zones, and automated Infrastructure-as-Code delivery.

Practice Area

Enterprise Delivery & Governance

Technical advisory for systems resilience, architectural governance, cloud compute unit economics (FinOps), and enterprise-grade deployment controls.

Initiate Contact

Discuss your cloud initiative.

Reach out directly to evaluate architecture feasibility, scope a Kubernetes or model inference cluster build, or schedule an initial consultation with our practice leads.

Primary Inbound hello@sorami.com.au
Corporate Entity SORAMI CONSULTING PTY LTD
Australian Company Number ACN 702 116 452
Registered Office Melbourne, Victoria, Australia