Infrastructure fleet management
One platform for every cluster, cloud, and environment. Take control of your Kubernetes infrastructure — from bare metal to cloud — with full-stack lifecycle management that scales.
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The scale of the problem
Infrastructure operations can’t keep up
Organizations have standardized on Kubernetes. But scaling it across clouds, data centers, and bare metal — without a unified way to manage the full stack — is creating real operational strain.
Platform teams are spending more time on maintenance than on enabling developers. Every environment has its own tooling and workflows. Provisioning takes days instead of minutes. And day 2 operations — patching, upgrading, compliance — across hundreds or thousands of clusters is where things stall.
The traditional options don’t solve this.
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DIY with open source tools works until you need to scale past a handful of clusters — or until the engineer who built it moves on.
Managed Kubernetes from a single cloud provider leaves gaps in your data center and bare metal environments. You end up running multiple control planes anyway.
Legacy point solutions manage only the Kubernetes layer, treating the OS, networking, storage, and application services as someone else’s problem.
What you need is a single operational model that works across every environment, manages the entire stack, and scales without multiplying headcount.
Where can we help you?
Multi-cluster, multi-environment Kubernetes
You’re running clusters across public clouds, private data centers, and hybrid environments — each set up differently, each with its own tools. You need a single orchestration plane that brings consistency and lifecycle management to the entire fleet.
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Kubernetes in the cloud
You’ve standardized on AWS EKS, EC2, or another managed service. But the full lifecycle — upgrades, compliance, add-ons — still takes too much manual effort. You want cloud convenience with the operational control that providers don’t offer out of the box.
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Bare metal Kubernetes
You’re running Kubernetes directly on physical servers for performance, cost, or to eliminate the hypervisor. The challenge: you own the entire stack from the OS up, and need a platform that manages it as a single unit.
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Virtual machines on Kubernetes
You want to consolidate VM and container workloads onto one platform — to cut VMware licensing costs, simplify operations, or both. You need a migration path that doesn’t require a full rewrite, and gives your VMs the same lifecycle automation your containers already have.
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Cloud-native infrastructure for AI
Your AI teams need GPU-enabled clusters provisioned fast and managed consistently. The underlying Kubernetes environment needs to be reliable and scalable — and something your platform team can operate without specialized AI expertise.
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How Spectro Cloud helps
Our Palette platform provides full-stack orchestration for your entire Kubernetes infrastructure fleet. Instead of managing each layer separately — OS, Kubernetes distribution, networking, storage, security, application services — Palette treats the whole stack as a single, declarative unit.
With Cluster Profiles, platform teams blueprint the entire stack and deploy it consistently to AWS, Azure, Google Cloud, VMware, bare metal, or hybrid environments.
Developers get self-service access to production-ready infrastructure. Operations teams get governance, cost visibility, and automated lifecycle management across every cluster.
For organizations running virtual machine workloads, Palette’s Virtual Machine Orchestrator brings VMs to bare metal Kubernetes as first-class citizens using KubeVirt, with automated migration tooling that has helped customers move thousands of VMs off VMware in months.
For regulated industries, Palette VerteX provides FIPS 140-3 compliance with the same operational model.
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Go deeper
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State of Production Kubernetes 2025
Five years of independent research into how enterprises use Kubernetes in production. 455 respondents, statistically rigorous, vendor-neutral.
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GigaOm Radar for Managed Kubernetes
See why GigaOm rated Spectro Cloud a leader and outperformer for the third consecutive year.
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Day 2 operations for Kubernetes
What happens after deployment — and why lifecycle management is where most platforms fall short.
Talk to us about your infrastructure
Whether you’re consolidating a multi-cloud estate, migrating off VMware, deploying bare metal for performance-intensive workloads, or building the Kubernetes foundations for AI — we can help you bring operating costs under control without sacrificing flexibility.
FAQs
Got questions? We’ve got answers. And if you don’t see the info you need here, get in touch and we’d be happy to help.
Palette is the full-stack Kubernetes management platform for any workload — traditional applications, microservices, VMs, and the infrastructure that AI runs on. PaletteAI adds capabilities specific to AI practitioners: GPU as a Service, Model as a Service, and NVIDIA AI Enterprise integration. If your focus is managing infrastructure fleets, start with Palette. If you’re building AI factories or offering AI as a service, PaletteAI extends it.
No. Palette can import and manage existing clusters provisioned with EKS, AKS, GKE, Rancher, or other tools. You don’t need to rebuild anything. Palette gives you a single pane of glass while progressively bringing clusters under full lifecycle management.
Many organizations assemble platforms from open source components: Cluster API, Argo CD, Terraform, custom scripts. This works at small scale but becomes a bottleneck as you grow. Palette provides production-ready fleet management with built-in governance, so your engineers focus on outcomes rather than platform maintenance.
Yes. Palette supports upstream Kubernetes, EKS, AKS, GKE, RKE2, K3s, and its own CNCF-conformant distribution, PXK. You can standardize on one or run multiple, all managed through the same platform.
Most Kubernetes tools manage only the Kubernetes layer, leaving you to handle the OS, networking, storage, and add-ons separately. Palette manages everything as one declarative unit. When you update a Cluster Profile, changes roll out across every layer — from OS patches to add-on upgrades — consistently, without drift. This matters most on bare metal, where there’s no cloud provider handling the lower layers.
Many organizations have initial clusters running in Palette within days. For large-scale fleet management across multiple environments, we typically work through architecture planning and a pilot phase over a few weeks before expanding. VMware migration timelines depend on estate size, but Palette’s automation handles the heavy lifting.
Yes. This is core to what Palette does. Deploy and manage clusters across AWS, Azure, Google Cloud, VMware, bare metal, and edge locations — all through one platform with a single operational model.