MLOps & Infrastructure SoftBrixAI Stack

Enterprise Kubernetes Engineering

The industry-standard container orchestration platform, powering resilient model serving at scale. We design, optimize, and deploy production-grade architectures utilizing the full capabilities of the Kubernetes ecosystem.

Missing SVG Kubernetes

Kubernetes

Production Certified

Architectural Overview

Kubernetes is our primary orchestration tool for deploying and scaling containerized machine learning models. We configure clusters to manage high-throughput inference runtimes, schedule GPU resources, and automate rolling model updates with zero downtime.

Capabilities

Our Kubernetes Engineering Services

We deliver highly specialized, production-ready systems tailored to your technical requirements.

developer_board

GPU Scheduling & Scaling

We configure Kubernetes GPU schedules, dividing node pools and taints to ensure ML workloads target active hardware accelerators.

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KServe Model Deployments

We deploy serverless model endpoints utilizing KServe, enabling automated scaling based on traffic requests.

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GitOps Infrastructure Management

We manage cluster configurations using GitOps (ArgoCD), ensuring staging and production configurations remain synchronized.

monitoring

Prometheus Monitoring & Alerting

We set up Prometheus and Grafana dashboards to track GPU temperatures, memory utilization, latency, and throughput.

Ecosystem

Kubernetes Tooling & Stack Integrations

We operate across the entire modern ecosystem surrounding Kubernetes, deploying optimized dependencies and configurations.

MLOps Tools on K8s

Specialized Kubernetes tools used to orchestrate model lifetimes.

KServe Kubeflow Seldon Core Triton Operator

Cluster Management

Core services used to deploy and sync cluster configurations.

Helm Charts ArgoCD Kustomize Calico CNI

Observability Stack

Monitoring stacks capturing cluster telemetry and health.

Prometheus Grafana Kube-State-Metrics FluentBit
Why Choose SoftBrixAI

Production-Grade Engineers

01
engineering

Top 1% Seniority

Certified Kubernetes Administrators (CKA) managing cluster configurations.

02
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Immediate Velocity

Expert knowledge in GPU resource allocation, node pools, and taint configurations.

03
gavel

Compliance Native

Comprehensive MLOps integration with KServe, Kubeflow, and Prometheus monitoring.

Case Studies

Proven Results with Kubernetes

Explore how we leverage Kubernetes to build business-critical platforms and achieve operational milestones.

SaaS Verified Output

Kubernetes Cluster Hosts 50+ Custom LLM Inferences Securely

We designed a multi-tenant Kubernetes cluster that schedules PyTorch models across A100 GPU pools, reducing hosting costs by 35%.

#Kubernetes #KServe #Triton #Terraform
Logistics & Supply Verified Output

Automated OCR Ingestion Engine Auto-Scales to Process Spike Workloads

Configured KPA autoscaling on a Kubernetes cluster, allowing OCR container runtimes to scale from 2 to 30 nodes during peak hours.

#Kubernetes #TensorFlow #Prometheus #Helm
Flexible Cooperation

Flexible Engagement Models

Scale your engineering capacity dynamically. We integrate seamlessly into your operations with three battle-tested engagement models.

Model 01

Staff Augmentation

Inject senior AI and MLOps engineers directly into your active squads. Rapidly scale resources with dedicated support under your management.

Scale in 48 Hours chevron_right
Model 02

Dedicated Team

A self-governing team of engineers, project managers, and QA specialists built specifically to design, build, and support your proprietary AI pipelines.

Turnkey Operations chevron_right
Model 03

Full Build & Deliver

Fixed-scope or milestone-driven development. We take ownership from requirements definition and MVP design to final production handoff.

Milestone Guaranteed chevron_right
Enterprise Trust & Security

Compliance-First Deployment Standards

We integrate safety controls natively. Every Kubernetes application is architected to satisfy strict global compliance and privacy policies.

verified_user

SOC 2 Type II

Logical isolation & logs

health_and_safety

HIPAA PHI

PHI data de-identification

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ISO/IEC 27001

International safeguards

FAQ

Common Kubernetes Questions

Why do you use Kubernetes for model deployment? expand_more
Kubernetes provides robust scaling, resource isolation, auto-healing, and declarative configurations. It prevents cloud vendor lock-in.
How do you handle GPU sharing in Kubernetes? expand_more
We configure NVIDIA Multi-Instance GPU (MIG) or fractional GPU sharing, allowing multiple containers to share a single GPU card safely.
Do you support Helm for MLOps configurations? expand_more
Yes. We build modular Helm charts to package and version model deployments, including ingress setups, environment configurations, and metrics endpoints.
How do you monitor model latency in Kubernetes? expand_more
We route metric targets from KServe to Prometheus, tracking p95/p99 latency, active throughput, and error codes in Grafana.
What GitOps tools do you use? expand_more
We standardise on ArgoCD, linking it to your private git repositories to automate deployments and prevent manual drifts.

Accelerate Your AI Project with Kubernetes

Schedule an architectural blueprint review session with our senior Kubernetes engineers to map your database, compliance, and MLOps strategies.

Schedule Architecture Session