Kubernetes Consulting & Implementation
Enterprise Kubernetes, engineered to run AI
XTIVIA plans, builds, secures, and operates Kubernetes platforms on EKS, AKS, GKE, and OpenShift — from cluster architecture and migration through GPU scheduling for production inference.
The platform
Reinvent your organization with Kubernetes
Move to an architecture that autoscales, fails over, and heals itself — and stop treating every service as its own silo with its own deployment story.
One orchestration layer
Autoscaling, automated failover, and self-healing across every business service — not a set of silos.
Cloud-agnostic by design
The same manifests, pipelines, and policies run on EKS, AKS, GKE, or OpenShift.
Secure from cluster zero
Signed images, admission policy, network policy, and secrets management wired in at build time.
Cost under control
Right-sized node pools, bin-packing, and spot strategy that keep cloud spend flat as you grow.
Offerings
Where we plug in
A fixed-scope health check, a greenfield platform build, or an embedded team beside yours — choose the level of support that matches where you are today.
Architecture & Roadmap
A target cluster architecture, landing zones, and a costed roadmap built around the workloads you already run.
Platform Build
Production clusters, GitOps delivery, observability, and policy guardrails stood up in the first sprints.
Migration & Containerization
Move VMs, monoliths, and legacy middleware onto containers without pausing the business.
Cluster Health Check
A hands-on review of a running platform: bottlenecks, single points of failure, and a prioritized fix list.
Managed Kubernetes
24×7 operations, version upgrades, patching, and capacity tuning by certified engineers.
AI Infrastructure Enablement
GPU scheduling, inference routing, and the guardrails a production model platform needs.
Ready to get more from Kubernetes?
Talk to an XTIVIA architect about your clusters, your migration, or your GPU strategy — no obligation, no pressure.
Capabilities
From cluster zero to day two
Our engineers cover the whole platform — architecture, delivery, networking, security, and operations — so the design decision is never constrained by which layer we happen to know.
Cluster Architecture
Multi-cluster, multi-region topologies sized for your workloads and the blast radius you can accept.
Platform Engineering
Golden paths, Helm charts, and self-service templates your developers actually want to use.
GitOps & CI/CD
Argo CD and pipeline automation, so every cluster change is reviewed, versioned, and reversible.
Networking & Gateway API
Gateway API, ingress, service mesh, and mTLS that hold up under real traffic patterns.
Security & Compliance
Admission policy, image signing, SBOMs, runtime detection, and secrets and key management.
Observability & SRE
Prometheus, OpenTelemetry, and SLOs that put latency, saturation, and cost in one view.
Stateful Workloads
Databases, brokers, and CSI storage run on Kubernetes without surprise data loss.
FinOps & Right-Sizing
Bin-packing, autoscaling policy, and spot strategy that cut idle spend without risking capacity.
GPU & Accelerator Scheduling
Dynamic Resource Allocation, MIG slicing, and queueing across a shared accelerator fleet.
Why it works
Four things every rollout gets right
The difference between a platform that pays off and one that stalls after the first cluster is rarely the technology.
Architected first
Topology, tenancy, and blast radius agreed before the first cluster is built.
Secure by default
Policy, signing, and network controls from cluster zero — not after the audit.
Cost under control
Right-sizing and autoscaling policy that hold spend flat as workloads grow.
AI-ready
GPU scheduling and inference routing on a platform your SREs already run.
Signature offering
Migrating onto Kubernetes.
Virtual machines, a monolith you have outgrown, or a first cluster that is already fighting you — the destination is the same and so are the landmines. We have run this enough times to know where they sit.
- 01
Discover & assess
Inventory applications, dependencies, and runtime constraints — with owners and real usage attached to each one.
- 02
Architect the target
Cluster topology, tenancy model, networking, storage, and security standards agreed before anything is built.
- 03
Build the platform as code
Clusters, GitOps delivery, observability, and policy guardrails as reusable Terraform and Helm — not console clicks.
- 04
Migrate in waves & validate
Containerize and cut over by domain, run in parallel, and load-test peak traffic before anyone is asked to switch.
- 05
Operate, optimize & hand over
Upgrade cadence, cost tuning, runbooks, and a team trained to run the platform without us.
AI on Kubernetes
Kubernetes is where inference runs now
Two-thirds of organizations hosting generative AI models already serve at least some inference on Kubernetes. The primitives moved into the core — Dynamic Resource Allocation, Kueue, the Gateway API Inference Extension — so AI runs on the platform your SREs already operate, not a second estate beside it.
Dynamic Resource Allocation
GPU scheduling that reasons about hardware instead of counting it — GA since Kubernetes 1.34.
Inference Gateway
Gateway API Inference Extension routes by model and load, not by round robin.
Queued, shared accelerators
Kueue, MIG slicing, and quota so one team cannot strand an H100 fleet.
AI Conformance
We build to the CNCF Certified Kubernetes AI Conformance baseline, so workloads stay portable.
Success stories
Real-world delivery, at enterprise scale.
A global retailer moved off Rackspace onto AWS and Amazon EKS during peak season — without a minute of downtime.
Resources
Guides & field notes
Practical writing from the architects and engineers who run the assessments, the migrations, and the day-two operations.
Blog
Kubernetes, cloud native, and the future of software
Blog
What is the business value of deploying Kubernetes?
Blog
A comprehensive guide to key management services in Kubernetes
Blog
Comparing Azure and AWS for Kubernetes
Blog
Kubernetes vs. Docker: understanding the differences
Success Story
Retail transformation with AWS Kubernetes (PDF)
Let's Talk Today!
No obligation, no pressure. We're easy to talk with and you might be surprised at how much you can learn about your project by speaking with our experts.
XTIVIA CORPORATE OFFICE
304 South 8th Street, Suite 201
Colorado Springs, CO 80905 USA
Additional offices in New York, New Jersey, Texas, Virginia, and Hyderabad, India.
USA toll-free: 888-685-3101, ext. 2
International: +1 719-685-3100, ext. 2
Fax: +1 719-685-3400
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