E2E Networks Alternative

The E2E Networks alternative built on a proprietary stack — not OpenStack.

Purpose-built for GPU. True fractional GPU from 12.5%. Developer SDK, CLI and REST API. INR billing. ISO 27001. DPDP-ready. And uniquely — you can license the whole platform.

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Why ML teams pick PodStack over E2E

Proprietary GPU stack

E2E runs OpenStack — general-purpose VMs with GPU bolted on. PodStack is purpose-built for GPU sharing and scheduling.

True fractional GPU

Allocate 12.5%–100% of an A100 or H100. Stop paying for capacity you do not use.

Developer-first tooling

SDK, CLI, REST API, and podstack.yaml. Push to git, deploy a Pod. No Horizon dashboard required.

Platform license available

License the same stack that powers PodStack and run it in your own DC. Enterprises and government only.

PodStack vs E2E Networks — feature by feature

FeaturePodStackE2E Networks
Platform stackProprietary, purpose-built for GPUOpenStack-based
Platform licenseAvailable — license + run in your own DCNo — managed only
Fractional GPU12.5% – 100% via PodVirtFull GPU only
Developer toolingSDK, CLI, REST API, podstack.yamlPortal + Horizon dashboard
Billing currencyINR — incl. taxesINR
Per-second billingYesPer-hour on most plans
Data residencyIndia (Bengaluru DCs)India
ComplianceISO 27001, DPDP-readyISO 27001

Pricing side-by-side

E2E prices shown for on-demand GPU plans as published. Subject to change.

GPUPodStackE2E Networks
NVIDIA L40S 48GB₹100/hr (incl. taxes)~₹130/hr
NVIDIA A100 40GB₹208/hr~₹250/hr
NVIDIA A100 80GB₹292/hr~₹325/hr
NVIDIA H100 80GB₹333/hr~₹400/hr

Migrating from E2E in under an hour

  1. Step 1
    Push your Docker image
    docker tag my-llm:latest registry.podstack.ai/<org>/my-llm:latest
docker push registry.podstack.ai/<org>/my-llm:latest
  2. Step 2
    Sync model weights and datasets
    aws s3 sync ./weights/ s3://my-bucket/weights/ \
  --endpoint-url https://s3.podstack.ai
  3. Step 3
    Launch a Pod
    # podstack.yaml
gpu: a100-80gb
gpuFraction: 0.5
image: registry.podstack.ai/<org>/my-llm:latest
volume:
  bucket: my-bucket
  mountPath: /workspace
    podstack pod create -f podstack.yaml

Frequently asked questions

Why look for an E2E Networks alternative?+

E2E Networks is a credible Indian cloud provider, but its GPU offering runs on an OpenStack-based stack designed for general-purpose VMs, not GPU-first workloads. Teams running serious ML want true fractional GPU (pay for 12.5% of a card), per-second billing, a real developer SDK/CLI, and the option to license the platform itself for in-house deployment. PodStack is built ground-up around those needs.

Is PodStack built on open-source like OpenStack or Kubernetes?+

No. PodStack is a proprietary, purpose-built platform — our own control plane, scheduler, and virtualisation layer (PodVirt) designed specifically for fractional GPU sharing. We do not stitch together OpenStack, Slurm, or vanilla Kubernetes. This is why we can offer 12.5% fractional GPU allocation and sub-second scaling that OpenStack-based stacks struggle to deliver.

Can we license the PodStack platform to run our own GPU cloud?+

Yes. PodStack is sold both as a managed cloud and as a licensable platform. Enterprises, government departments, and operators can license the full PodStack stack and deploy it in their own data centres. Contact sales@podstack.ai for licensing terms.

Does PodStack support fractional GPU like E2E?+

E2E offers full-GPU instances. PodStack supports true fractional GPU from 12.5% to 100% of a card via PodVirt, which means your inference workload that uses 15% of an A100 only pays for 15%. This typically cuts effective $/hr by 3–5× for sub-utilised workloads.

How do I migrate from E2E Networks to PodStack?+

Three steps: (1) push your Docker image to PodStack's registry, (2) sync model weights and datasets to a PodStack S3-compatible bucket, (3) launch a Pod via the portal or with `podstack pod create -f podstack.yaml`. Most teams migrate in under an hour.

Does PodStack have an SLA?+

Yes. PodStack offers enterprise SLAs on Pods, VMs, and Baremetal GPU. Every PodStack GPU runs on operator-owned hardware inside Indian data centres.

Is PodStack DPDP and government-empanelment ready?+

Yes. PodStack is ISO 27001 certified and DPDP-compliant. All compute and storage stay inside Indian data centres. PodStack is sovereign and government-empanelment ready for defence and regulated workloads.

Built for GPU. Licensable for scale.

Launch your first Pod in under 60 seconds — or talk to us about licensing.

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