A developer platform for services, jobs, databases and pipelines that sits between a simple PaaS and raw Kubernetes, with BYOC (bring-your-own-cloud) support.
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Northflank is a managed developer platform for deploying containerized services, jobs, cron tasks, managed databases, and GPU/AI workloads from Git to production. It abstracts away Kubernetes behind CI/CD pipelines, preview environments, and built-in observability, and can run either on Northflank's own cloud or inside your own cloud account (bring-your-own-cloud on AWS EKS, GCP GKE, Azure AKS, Oracle OKE, Civo, CoreWeave, bare-metal, or any CNCF-certified cluster).
Key features
Git-push CI/CD with build pipelines, releases, and rollbacks
Preview and staging environments generated from pull requests
Managed databases and addons, including PostgreSQL with pgvector
GPU workloads for inference, fine-tuning, and training, with per-second billing, GPU sharing (time-slicing), and spot instances
Bring-your-own-cloud deployment into your own AWS, GCP, Azure, or Kubernetes account
Autoscaling, secrets and config management, backups, and observability
Specs
Category
Managed PaaS
Pricing model
tiered
Free tier
Yes โ Free Sandbox tier exists, but a payment method is required to create any resources.
Managed database
Yes
Regions
10+
Self-hostable
No
Docker-native
Yes
Git deploy
Yes
Open source
No
Last reviewed 2026-07-16 โ see our methodology. Specs, pricing and free tiers change often, so confirm current details on the provider before deciding.
Pros & cons
Our editorial assessment โ not vendor-stated facts.
Pros
Broad workload coverage in one platform: web services, jobs, cron, databases, and GPU/AI all in the same place
Kubernetes-grade capabilities such as autoscaling and multi-region without operating Kubernetes directly
Bring-your-own-cloud lets teams keep their existing cloud billing and data residency while using Northflank's control plane
Strong fit for AI/ML teams thanks to native GPU provisioning, GPU sharing, and spot orchestration
Usage-based billing prorated to the second, with no per-seat charges
Cons
A payment method is required to create any resources, even on the free Sandbox tier
The free tier is limited (two services, two jobs, and one addon) and explicitly not intended for production
Usage-based pricing across CPU, memory, GPU, storage, and egress is harder to predict than a flat monthly plan
The broad feature surface and configuration options mean a steeper initial learning curve than minimalist git-push hosts
Smaller vendor and community than the major hyperscalers, so less third-party tooling and fewer tutorials
Pricing
Pricing is consumption-based and prorated to the second, billed per vCPU, memory, GPU, storage, and egress rather than per seat, across Sandbox (free), Pay-as-you-go, and Enterprise tiers. The free Sandbox tier suits hobby and evaluation use, but a payment method is required up front on every plan. With bring-your-own-cloud, infrastructure bills directly to your own cloud account while Northflank adds a management fee on top.
Who should use Northflank?
Teams that want a single platform to ship containerized apps, databases, and GPU/AI workloads with CI/CD and preview environments without operating Kubernetes themselves. It is especially well suited to organizations that need bring-your-own-cloud deployment for cost, compliance, or data-residency reasons.
Frequently asked questions
Does Northflank have a free tier?
Yes. Free Sandbox tier exists, but a payment method is required to create any resources.
How much does Northflank cost?
Pricing is consumption-based and prorated to the second, billed per vCPU, memory, GPU, storage, and egress rather than per seat, across Sandbox (free), Pay-as-you-go, and Enterprise tiers. The free Sandbox tier suits hobby and evaluation use, but a payment method is required up front on every plan. With bring-your-own-cloud, infrastructure bills directly to your own cloud account while Northflank adds a management fee on top.
Who should use Northflank?
Teams that want a single platform to ship containerized apps, databases, and GPU/AI workloads with CI/CD and preview environments without operating Kubernetes themselves. It is especially well suited to organizations that need bring-your-own-cloud deployment for cost, compliance, or data-residency reasons.