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Cat Networks
04/Services

Public and private cloud, engineered end to end

There is no single right answer to where a workload should run. Elastic and unpredictable loads belong on public cloud, where you pay for flexibility. Steady and predictable loads usually run better and cheaper on a platform you own.

We work on both sides of that line. As partners of the major public clouds and builders of open source private clouds, we help you place each workload where it earns its keep.

01

Public Cloud

We partner with Microsoft Azure, Google Cloud Platform, and Amazon Web Services to design the optimal cloud environment for your business.

  • Microsoft Azure
  • Google Cloud Platform
  • Amazon Web Services
  • Architecture Consulting
  • Application Development
  • Operation & Maintenance
02

Private Cloud

We build private cloud platforms on Proxmox VE, OpenStack, and VMware, designed and operated as infrastructure your own team fully controls.

  • Proxmox VE
  • OpenStack
  • VMware
  • Infrastructure Consulting
  • Platform Deployment
  • Operation & Maintenance

Why Cat Networks

01

The right platform per workload

Public cloud where elasticity pays for itself, private cloud where it does not. We model the costs honestly and recommend placement based on your numbers, not our preferences.

02

Open source foundations

Proxmox VE, OpenStack, Ceph and Kubernetes mean no per-core license shocks and no proprietary lock-in. The platform we build for you is one your team could operate without us.

03

Operated, not handed over

We run what we build. Monitoring, patching, capacity management and upgrades are part of the service, watched by the same NOC that watches our network.

Example of use

A media company rendered video on public cloud GPUs and stored its archive on S3. Costs grew every quarter even though the rendering load itself was stable and predictable.

We built a private cloud for the steady rendering pipeline and kept the public cloud for spikes, with S3 compatible storage on both sides so the tooling did not change.

Outcomes
  • Cost per render job dropped sharply at steady load
  • The team kept its existing tools, APIs and pipelines
  • Burst capacity remains one API call away in the public cloud

What to expect

  • A clear placement rule for every workload, backed by cost modeling
  • Cloud bills that track real usage instead of habit
  • A private platform your team understands and could operate
Ready to get started?
Tell us about your project and requirements. We will respond promptly with an estimate and a deployment plan.
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