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.

Cloud & DevOps PracticeEKS · AKS · GKE · OpenShift30+ Years in Enterprise IT
Cloud-Native PlatformKubernetes / v1.37
EKSAKSGKEOpenShift
CDBuild & Supply ChainGitOps · SBOM · Signing
K8Clusters & Node PoolsMulti-AZ · Autoscaling
NWGateway API · MeshmTLS · Traffic Policy
SPPolicy & Runtime SecurityAdmission · Secrets
AIGPU Scheduling · InferenceDRA · Kueue · vLLM
TerraformHelmArgo CDPrometheus
30+Years engineering enterprise infrastructure
10k+Projects delivered
4Distributions in production: EKS, AKS, GKE, OpenShift
24×7Managed cluster operations

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.

  1. 01

    Discover & assess

    Inventory applications, dependencies, and runtime constraints — with owners and real usage attached to each one.

  2. 02

    Architect the target

    Cluster topology, tenancy model, networking, storage, and security standards agreed before anything is built.

  3. 03

    Build the platform as code

    Clusters, GitOps delivery, observability, and policy guardrails as reusable Terraform and Helm — not console clicks.

  4. 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.

  5. 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.

01

Dynamic Resource Allocation

GPU scheduling that reasons about hardware instead of counting it — GA since Kubernetes 1.34.

02

Inference Gateway

Gateway API Inference Extension routes by model and load, not by round robin.

03

Queued, shared accelerators

Kueue, MIG slicing, and quota so one team cannot strand an H100 fleet.

04

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.

Global Fine Jewelry Retailer

ZeroDowntime through the cutover
Rackspace → AWSCloud migration
EKSContainer orchestration
PeakHoliday traffic absorbed on demand

Retail transformation on AWS Kubernetes and MuleSoft Enterprise Edition.

A Rackspace Cloud environment that could not scale with global expansion, MuleSoft Community Edition 3.8 with no enterprise support, and no centralized performance monitoring to catch problems before customers did.

XTIVIA ran a phased lift-and-shift to AWS, introduced Amazon EKS for containerized workloads, upgraded MuleSoft to Enterprise Edition 3.9, added AppDynamics and Nagios monitoring, and load-balanced every external connection.

Zero downtime across the transition, on-demand scaling through peak promotional traffic, lower infrastructure cost through managed services and Kubernetes-based allocation, and proactive visibility into system health.

AWSAmazon EKSMuleSoft AnypointAPI ManagerAppDynamicsNagios
Read the full success story →

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