SECURE CLOUD
Modernize your application estate. Strengthen your compliance posture. Don’t choose.
Insurance organizations run some of the most sensitive workloads in the world: claims data, health records, policyholder PII, actuarial models - on infrastructure that regulators scrutinize and attackers target. At the same time, the pressure to modernize is relentless: containerize legacy applications, rationalize a VMware estate that just got a lot more expensive, adopt AI for underwriting and claims processing, and do all of it without introducing new exposure.
Most cloud platforms ask you to trade control for speed. Mirantis k0rdent AI Enterprise doesn’t.
The infrastructure challenge is different for insurance.
Most enterprises can tolerate some ambiguity about where their data lives or how their clusters are configured. Insurers can’t. A misconfigured Kubernetes cluster isn’t just a security risk, it’s a compliance event. A workload running in the wrong environment isn’t an inconvenience, it’s a regulatory violation.
The complexity compounds quickly:
A legacy VM estate that can’t be abandoned overnight. Your core policy and claims systems have run in virtualized environments for years. Containerizing them requires a disciplined, risk-managed approach, not a rip-and-replace that disrupts production or creates new audit surface.
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Multi-cloud sprawl that creates inconsistent security posture. Every cloud, every data center, every edge location is another set of configurations to manage, another set of policies to enforce, another set of audit trails to maintain. Divergence between environments isn’t just operational friction. In a regulated industry, it’s risk.
Platform teams re-solving the same problems, over and over. When adding a new cloud or data center requires rebuilding your platform stack from scratch, your best infrastructure engineers aren’t building value; they’re fighting fires. And every divergent codebase they create expands your attack surface.
AI workloads that can’t go to public cloud. The case for AI in insurance is compelling: claims triage, fraud detection, underwriting risk scoring. The problem is that running inference models against HIPAA-regulated health data or PII-rich claims records on shared public cloud infrastructure isn’t a risk most carriers can accept.
Your cloud. Your data. Your compliance posture.
Mirantis k0rdent AI Enterprise gives insurance providers a single control plane for managing Kubernetes clusters and services across on-premises data centers, hybrid clouds, and public clouds, with security, governance, and data sovereignty built into the provisioning model itself, not bolted on afterward.
Hardened infrastructure, by design
Security in a regulated environment can’t depend on people remembering to do the right thing. Mirantis k0rdent AI Enterprise enforces it declaratively. Cluster configurations, security policies, and service deployments are defined as versioned, immutable templates and applied consistently across every environment in your estate. Configuration drift triggers automatic reconciliation before it becomes a gap. Audit logs are continuous and complete. Access is governed by RBAC and enforced cluster-wide.
k0rdent AI Enterprise is built for security-conscious, regulated environments, combining a secure software supply chain with the controls organizations need to support compliance programs, like signed artifacts, SBOMs, CVE reporting, RBAC/IAM, custom CA support, and airgapped or private-registry deployment options, all backed by relevant Mirantis corporate and component-level certifications. The platform runs in your environment, under your control, with your data staying exactly where your regulators and your own policies require.
Securing Kubernetes at enterprise scale means making dozens of intersecting decisions: node hardening, API protection, etcd security, supply chain integrity, admission control, east-west TLS, runtime security, pod security policy, secrets management, and more. It’s easy to get most of it right and miss something consequential. Our Kubernetes Enterprise Security Checklist walks through the full terrain, a practical framework for every security decision your platform and security teams will face.
Modernize from where you are: not from a greenfield fantasy
Most insurance IT estates have relied on VMware for over a decade, and they carry years of application logic, data dependencies, and compliance-tested configurations that can’t simply be discarded. The question isn’t whether to containerize; it’s how to do it selectively without disrupting production systems or creating new regulatory exposure in the process.
k0rdent manages both Kubernetes clusters and virtualized workloads from a single control plane, so your platform team isn’t running two separate estates under two separate security models. VMs and containers coexist. Workloads migrate at the pace your business and your risk tolerance can sustain.
If your infrastructure team is staring at a VMware estate and trying to figure out where to begin, From Virtualization to Containerization: A Guide for VMware Admins and Other Smart People is the field guide. It’s written for teams that know virtualization well and need a clear-eyed path to cloud native, covering the full journey from hypervisor concepts through Kubernetes orchestration, microservices architecture, and practical migration steps, without pretending VMs are going away.
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One platform. No more re-work.
Every time your platform team adds a new cloud, a new data center, or a new edge location, they face a familiar trap: build a new platform stack for that environment, or stress an existing stack that may not be fit for this new use-case. Either path creates divergence (different tooling, different automation codebases, different security configurations), and in a regulated environment, divergence is risk.
k0rdent provides a single API and control plane that spans every environment in your estate. ClusterTemplates define how clusters are built. ServiceTemplates define what runs on them. Both are versioned, immutable, and applied consistently everywhere. Your platform engineers stop re-solving infrastructure problems across environments and start building the self-service capabilities that actually enable your application teams.
Multi-cloud can underminey your platform team’s ability to add strategic value, turning them into infrastructure firefighters rather than platform builders. It happens gradually, and by the time it’s obvious, you’re carrying a dozen overlapping codebases and a security model nobody can audit end to end. Platform Engineering: Challenges and Solutions maps exactly how this failure mode develops, and what a real solution looks like. Required reading for any CTO or VP of Infrastructure evaluating their Kubernetes strategy across a hybrid estate.
Enterprise AI: inference on regulated data, on your terms
The insurance use cases for AI are real: automated claims triage, fraud pattern detection, underwriting risk scoring, policyholder-facing automation. The obstacle isn’t the models; it’s the infrastructure. Most AI platforms assume your data can move freely to wherever the GPUs happen to be. For an insurer handling HIPAA-regulated health data or PII-rich claims records, that assumption is unacceptable.
k0rdent AI Enterprise provides everything needed to run GPU-optimized inference workloads on your own infrastructure: bare metal GPU servers in your own data center, under your own security controls, with the same hardened compliance posture as the rest of your k0rdent estate. Your models run on your hardware. Your data doesn’t leave your environment. Your AI applications operate under the same audit and governance framework as everything else.
Hard multi-tenancy at the GPU level: hardware-enforced isolation between business units, application environments, or external partners sharing infrastructure
Fractional GPU provisioning: NVIDIA MIG and vGPU support for efficient sharing of GPU resources across teams and workloads, maximizing utilization without compromising isolation
Everywhere Inference: a turnkey inference PaaS that deploys models and routes traffic with ultra-low latency, with per-second billing and real-time cost visibility
Sovereign by default: data residency, on-premises deployment, and compliance controls are first-class architectural features, not options you configure after the fact
DOWNLOAD THE k0RDENT AI ENTERPRISE OVERVIEW
Migration support: from inventory to production, with governance at every step
Deciding to move workloads to a new platform is one thing. Actually getting there requires methodology: inventory your applications, classify migration complexity, build the migration catalogue, run validated pilots, and confirm production readiness before cutover. And in a regulated environment, every step needs to be auditable.
Mirantis has done this for some of the most demanding enterprise environments in the world, across finance, healthcare, and government. Our structured migration approach moves in three phases (Discovery and Planning, Analysis and Design, and Migration and Validation), with our engineers working alongside yours throughout, not just handing off documentation.
The Mirantis Workload Migration Overview lays out the full process, phases, and governance model. If your team is evaluating whether a migration is feasible and what it actually involves operationally, start here.
Proven in the world’s most demanding
regulated environments
Reduced application time-to-market from 18 months to 5 months. Improved customer and employee experience through modernized, containerized application delivery at scale.
Running 1,000+ applications across 33,000 containers on 9,000 cores globally, with Mirantis engineers operating alongside their team day-to-day. "When doing major upgrades or complex incidents, we work with Mirantis experts."
GPU-accelerated infrastructure for risk analysis model execution. "Developers realized they could focus on core development without traditional operational issues. ROI was visible early."
700 applications migrated to containers. 200,000 containers in production. 50% increase in developer productivity. "We are deprecating 15 years of toolsets and building a consistent operating model across multiple clouds."
The numbers behind the platform
30+
YEARS
Of infrastructure expertise, from OpenStack through Kubernetes to GPU clouds
SECURITY-FIRST
BY DESIGN
Signed artifacts, SBOMs, CVE reporting, RBAC/IAM, custom CA support, and airgapped or private-registry deployment options for regulated environments
100+
ENGINEERS
In 15 countries, available 24/7 for support and managed operations
Ready to talk specifics?
Your compliance requirements, your migration priorities, your AI roadmap: none of it is generic, and neither should the conversation be. Talk to a Mirantis solutions architect and we’ll map k0rdent’s capabilities to what’s actually on your plate.
We see Mirantis as a strategic partner who can help us provide higher performance and greater success as we expand our cloud computing services internationally.
— Aurelio Forese, Head of Cloud, Netsons
900 E Hamilton Avenue
Suite 650
Campbell, CA 95008
+1-650-963-9828