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Control Plane vs Koyeb

ComparisonKoyeb
Last updated
First published
4 min read
Control Plane
vs
Koyeb
Runs across clouds
Yes
Can run in your account
Enterprise only (BYOC on request)
Yes
Scale-to-zero
Yes
Yes
VM workloads
No
PCI DSS L1, SOC 2, HIPAA
Compliance built in
ISO 27001, SOC 2 (Enterprise)

Choose Control Plane when where your workloads run matters: your accounts, your regions, several clouds and your own hardware as one virtual cloud, with enterprise compliance. Choose Koyeb for fast serverless deploys of containers (GPUs included) on infrastructure Koyeb runs. Short version: Koyeb hosts you on its cloud; Control Plane composes yours.

Koyeb does the serverless-container pitch well: push a container or connect a repo, and it runs across Koyeb's global infrastructure with scale-to-zero and GPU options. If you don't care where your workloads live, that is genuinely convenient. Control Plane is for when you do care: because the audit says your accounts, the customer says Frankfurt, or the architecture spans AWS, GCP, Azure, and a rack of your own GPUs. It composes all of that into one virtual cloud you deploy to like a single platform.

The core difference: whose infrastructure answers the audit

On Koyeb, the infrastructure is Koyeb's unless you negotiate Enterprise bring-your-own-cloud or custom regions. That is the source of its simplicity, and of its ceiling. Placement means choosing among Koyeb's locations; compliance means whatever Koyeb's platform posture gives you (ISO 27001 and SOC 2 on the Enterprise plan; no HIPAA or PCI documented); native AWS or GCP services sit outside the walls, reached with credentials you manage. For straightforward apps and inference endpoints, none of that may matter.

On Control Plane, the infrastructure is whatever you choose to compose: managed regions by default, your own AWS, GCP, or Azure accounts, neoclouds, Kubernetes clusters, or SSH-reachable servers. Workloads (containers and full VMs) get one network with mTLS, credential-free access to 600+ native cloud services through Universal Cloud Identity, scale-to-zero with Capacity AI right-sizing, and a compliance posture (PCI DSS Level 1, SOC 2 Type II, HIPAA, GDPR) that survives an enterprise procurement review.

Which one should you pick?

Choose Control Plane if...

  • Workloads must run in specific accounts, regions, or your own hardware.
  • You depend on native cloud services and want them credential-free.
  • You need VMs beside containers, or regulated-grade compliance.
  • You're composing several providers (including GPU neoclouds) into one platform.

Choose Koyeb if...

  • You want the fastest path from container to global URL and don't need to own where it runs.
  • Serverless GPUs for inference on someone else's infrastructure fit the bill.
  • ISO 27001 and SOC 2 on Koyeb's Enterprise plan cover your compliance requirements.
  • The app is self-contained and light on native cloud service dependencies.

Control Plane vs Koyeb, side by side

58 capabilities, scored from each vendor's public documentation with the same rules applied to both columns. Hover a capability for what it measures, or a verdict for the reason behind it.

Workload placement & topology5
Can one logical environment span two different cloud providers at once?Yes: One environment spans locations across AWS, GCP and Azure; a workload deploys to all of them at onceNo: CSP is Koyeb's choice per location
Number of publicly published regions or locationsYes: Around 30 managed regions across AWS, GCP, and Azure, plus any location you bringYes: 6 core plus 1 in preview
Can you attach your own Kubernetes cluster as a managed target?Yes: Registers a customer's own Kubernetes clusters as first-class locations, equal to native onesNo: None
Automatic failover of a running workload to another locationYes: DNS geo-routing drops unhealthy locations automaticallyPartial: Multi-region services
Fine-grained traffic steering across locations (priority, latency bias)Yes: routingTier priority groups, latency offset and tolerance per locationNo: Fixed edge routing
Getting to first deploy6
Git push to a branch triggers build and deploy with no external CIYes: Builds directly from a connected GitHub or GitLab repositoryPartial: GitHub only
Built-in image builder (no Dockerfile required)Yes: CLI build using Buildpacks with language auto-detection; Heroku, Google and Paketo builders; builds locally or remotelyYes: Git build
Named framework guides (Next.js, Django, Rails, Laravel…)Partial: Buildpack language conventions for Node, Python, Go, Java, Ruby, PHP, Rust — not per-framework guidesYes: 24 quick-start framework guides
One-click template or app catalogYes: Template catalog, 87 entries (databases, queues, analytics, and more); deployable from the UI, CLI, Terraform, or PulumiYes: One-click deploy catalogue, ~150+ entries
Documented free tierYes: The account is free to create and set up, with no cloud account required; you pay only once workloads use computeNo: Free entry withdrawn for new users
Local development story (emulator, local run, tunnel)Partial: Deploys a docker-compose project directly; port-forward and shell for working against remote instancesNo: Not documented
Migration in1
Import from an existing platform (Heroku, compose, Kubernetes manifests)Yes: Consumes docker-compose files directly, and converts Kubernetes manifests with a preview of the translationNo: Comparison pages only, no importer
Scaling & efficiency5
Metric-driven horizontal autoscalingYes: concurrency, rps, cpu, latency percentile, memory, KEDA, multi-metricYes: 5 metrics with thresholds
Automatic vertical resizing of a running workloadYes: Analyses historical usage and resizes container CPU and memory in place, without a restart; update frequency is throttleableNo: Not documented
Scale to zero with automatic wakeYes: Request-rate or concurrency triggers on serverless workloads; event-driven via KEDA for long-running and stateful onesYes: Two idle tiers with published wake times: 200 ms from light sleep, 1-5 s from deep sleep
Published cold-start or wake latency figuresNo: No figures publishedYes: 200 ms light sleep, 1-5 s deep sleep
Spot or preemptible instance supportPartial: Spot allocation in Managed Kubernetes node poolsNo: Not documented
Networking & edge7
First-party CDN or edge cachingNo: Docs cover configuring an external CDN; no first-party CDNPartial: Edge network does routing and TLS; caching not documented
First-party managed WAFNo: External CDN/WAF compatible; none first-partyNo: Not documented
Egress control: restrict which destinations a workload may reachYes: Outbound CIDR allow and block, hostname allowlist, port restrictionNo: No firewall at all
Private connectivity into a customer VPC or on-prem networkYes: An agent inside the private network tunnels TCP and UDP from workloads to internal endpoints; newer protocol adds HA across agent instances and bi-directional trafficNo: No private networking
Encrypted service-to-service networking as a platform defaultYes: Sidecar-based service mesh providing mTLS between workloads by defaultNo: No private networking
Application-layer request authentication at the edgeYes: JWT validation at the edge: multiple issuers, remote JWKS, claim-to-header mapping, per-path rulesNo: Not documented
Static IP addresses for inbound or outbound trafficYes: Reserved static public IP per location, attachable to a load balancerPartial: Not documented in detail
Storage & data services6
Managed relational or key-value databases as a first-party productYes: Postgres, Redis, MySQL, and more from the template catalogPartial: Managed Postgres
Persistent volumes attachable to a scaled-out workloadYes: One volume per replica, preserved when the workload scales downPartial: Volumes
Automatic volume growth before capacity is exhaustedYes: Expands on a free-space threshold, and also projects a growth rate from recent usage to expand ahead of needNo: Not documented
Backup and restore with scheduled retentionPartial: Snapshot and restore are available as commands; no scheduled backup or retention policy documentedPartial: Manual, in preview
Static site hosting as a first-class productNo: Not documentedNo: Not documented
First-class background jobs, queues and cronPartial: Cron workload type and one-off runs; no managed queue primitivePartial: Workers; managed cron not documented
Identity & secrets6
How a workload authenticates to external cloud servicesYes: A single identity grants a workload least-privilege access to resources in AWS, GCP and Azure simultaneously, with no credentials stored in the workloadNo: Not documented
Secrets management with access control on retrievalYes: Typed secret kinds with a runtime permission gate — a workload without an explicitly granted identity cannot read a secret at allPartial: Basic secrets
Role-based access control granularityYes: Permissions expressed as verbs per resource type, granted to users, service accounts, groups, or workload identitiesNo: Not documented
Audit trail of platform changesYes: Tamper-proof audit trail covering platform actions, and extensible so an application can write its own entries into the same trailNo: None
Third-party compliance certificationsYes: SOC 2 Type II, PCI DSS Level 1, HIPAA, GDPRPartial: ISO 27001 and SOC 2 listed on the Enterprise plan only; no HIPAA or PCI
Multi-tenancy for the customer's own end customersPartial: Top-level tenancy boundaries give hard isolation, but per-end-customer tenancy is not positioned as a use casePartial: Sandboxes for isolated per-invocation execution
Operations & observability8
Metrics with a queryable interfaceYes: Scrapes Prometheus-format metrics from containers on a 30s interval with regex filtering; queryable through a per-org GrafanaPartial: Basic, 7 days
Distributed tracingYes: Distributed tracing with custom tags and a configurable sampling rate, set at environment levelNo: Not documented
Managed log export to third-party destinationsYes: Datadog, CloudWatch, Coralogix, Logz.io, S3, Stackdriver, SyslogNo: No export
Default log retentionYes: 30 days by default, adjustable per orgNo: Not documented
Built-in alerting with notification channelsYes: Pre-provisioned alert rules with configurable contact points; notifications are off until a contact point is addedNo: Billing alerts only
Shell, file copy and port-forward into a running workloadYes: Interactive shell into a replica, file copy in and out, and local port-forwarding — all from the CLIPartial: Exec only
Progressive delivery: weighted traffic between versionsYes: Route-level traffic splitting by integer weight across workload versions; weighting everything to the new version performs a blue/green cutoverPartial: One implicit strategy
Ephemeral preview environment per pull requestYes: Per-PR preview environmentsPartial: Not first-class
Automation & extensibility6
First-party infrastructure-as-code provider (Terraform or equivalent)Yes: First-party Terraform and Pulumi providers, plus a Kubernetes operator exposing platform resources as CRDs for ArgoCDYes: Terraform and Pulumi
Complete public API referenceYes: Full API and CLI referenceYes: REST API
MCP server for AI-agent operation of the platformYes: First-party, with documented setup for Claude, Codex, Cursor, Gemini CLI, VS Code and AntigravityNo: Not documented
Machine-readable documentation (llms.txt, per-page markdown)Yes: llms.txt published and referenced from every pageNo: llms.txt returns 404
Ephemeral sandboxes for running untrusted or AI-generated codeYes: Sandboxes documentedYes: microVM sandboxes with JS and Python SDKs
Core product available as open sourceNo: Not open sourceNo: CLI and SDKs only
Specialized compute2
Run full virtual machines, not just containersYes: VMs run with their own guest OS and kernel while sharing the same mesh, identity, firewall and observability as containers; supports Windows guests and lifting existing VM disk imagesPartial: Firecracker, cited in blogs only
Run GPU workloads alongside standard servicesYes: NVIDIA T4 and A10G requested per container in the standard workload spec, drivers managed by the platform, billed at standard unit rates; GPU capacity from any provider, including neoclouds, joins through attached or provisioned Kubernetes clusters; automatic right-sizing does not apply to GPU workloadsYes: GPU instance types from L4 to H200 and B200 with published hourly prices, on the same service primitive and mesh as CPU instances; GPU scale-to-zero with wake
Commercial terms6
Published compute and memory unit pricesNo: No price list in the documentation snapshotPartial: Instance-bundled plus published GPU hourly rates
Published uptime SLA with a numberYes: 99.999% uptime SLAYes: 99.9% at $29/mo, 99.99% Enterprise
Documented path to migrate off the platformPartial: Environment export produces a portable spec, and workloads are OCI images that can run on the customer's own clusters; no migration-out guide publishedNo: Not documented
Public community channelPartial: Support via Slack and Discord referenced in docs; no public community forum documentedYes: Public forum
Named reference customers publishedPartial: Customer stories exist off-docs; none named in the documentation snapshotYes: Kong, eToro, Strapi Cloud, Toddl, FoxSell
Vendor continuity risk signalsPartial: Independent; funding and headcount not documented in the snapshotNo: Acquired by Mistral Feb 2026; changelog silent since; entry tier withdrawn

Scored from public documentation as of September 2026. “No” means not documented, not necessarily absent; breadth is not a quality ranking, and specialists doing one thing well score narrow by design.

Which fits your scenario

Control Plane fits: an AI product graduating from API calls to its own GPUs. Inference moves from a vendor endpoint to a pool at a neocloud, the web tier stays on AWS, and a healthcare customer wants HIPAA terms with data in named regions. Control Plane runs all of it as one cloud, with the GPU pool and the AWS regions under the same deploy, identity, and audit trail.

Koyeb fits: a small team shipping a global API with zero infrastructure appetite. Push the container, get the endpoint, let it scale to zero at night. If nobody is asking where it runs, the simplest host wins.

Frequently asked questions

Is Control Plane a Koyeb alternative?

For teams that have started caring where workloads run, yes. Both give you serverless-style containers with scale-to-zero; Control Plane adds control over placement (your accounts, your regions, your hardware) plus VMs, Universal Cloud Identity, and enterprise compliance.

Does Control Plane have scale-to-zero like Koyeb?

Yes. Idle workloads scale to zero, and Capacity AI right-sizes running ones in place as usage changes, on managed compute and in your own accounts alike.

Can Control Plane run GPU workloads?

Yes. GPU capacity from neoclouds like Lambda or CoreWeave, hyperscaler GPU instances, or your own hardware joins the virtual cloud as regions, and workloads deploy to them like anywhere else.

When is Koyeb the better choice?

When speed-to-URL beats control-of-placement: self-contained apps, inference endpoints, and side services where the vendor's infrastructure is good enough. Control Plane earns its keep when accounts, regions, identity, and audits enter the conversation.

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