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Control Plane vs Qovery

ComparisonQovery
Last updated
First published
4 min read
Control Plane
vs
Qovery
Runs across clouds
Yes
Can run in your account
Yes
Platform's job
Underlying cluster ops
Qovery-managed, in your account (yours with BYOK)
Yes
VM workloads
No
PCI DSS L1, SOC 2, HIPAA
Compliance built in
SOC 2 Type II; HIPAA BAA (Business+)

Choose Control Plane for a platform that spans clouds and on-prem as one virtual cloud, with identity, networking, VMs, scale-to-zero, and enterprise compliance built in. Choose Qovery to add developer-friendly deployment automation and preview environments to a cloud account you already operate. Short version: Qovery automates your cloud; Control Plane virtualizes it.

Qovery and Control Plane both run workloads in your own cloud accounts, which makes them easy to confuse and quite different in practice. Qovery is a deployment layer: it automates environments, previews, and deploys on infrastructure that stays in an account you own. Control Plane is a cloud virtualization platform: it turns AWS, GCP, Azure, Kubernetes, and on-prem servers into one virtual cloud, and the infrastructure underneath stops being your problem.

The core difference: a layer on your cloud vs a cloud of your own

Qovery's pitch is developer experience on your own account: connect a repo, get environments and ephemeral previews, keep the cloud bill and the data where they already live. It is a strong answer for a team on one primary cloud that wants Heroku-style flow without leaving its account. Qovery provisions and upgrades the cluster for you; the account, its network posture, and the rest of the operational surface are still yours.

Control Plane goes a layer deeper. Workloads deploy to a Global Virtual Cloud that can span several providers and your own hardware at once, with one network model, mTLS between services, credential-free access to native cloud services through Universal Cloud Identity, full Linux and Windows VMs beside containers, and scale-to-zero with Capacity AI right-sizing. Compliance (PCI DSS Level 1, SOC 2 Type II, HIPAA, GDPR) comes with the platform rather than the to-do list.

Which one should you pick?

Choose Control Plane if...

  • You need one platform across several clouds and on-prem, not automation on one account.
  • You run VMs as well as containers, or regulated workloads with hard compliance requirements.
  • You want networking, identity, and observability handled, not configured.
  • Cost control matters: scale-to-zero and automatic right-sizing, billed on consumption.

Choose Qovery if...

  • You live on one primary cloud and want better deploy flow inside it.
  • Ephemeral preview environments per pull request are the headline feature you need.
  • You want to keep operating your own account and simply automate the repetitive parts.
  • Your compliance posture is already handled at the account level.

Control Plane vs Qovery, 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: Environment-to-cluster binding immutable
Number of publicly published regions or locationsYes: Around 30 managed regions across AWS, GCP, and Azure, plus any location you bringN/A: Inherits the underlying cloud's regions
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 onesYes: Any Kubernetes distribution, 4 CPU/8GB floor
Automatic failover of a running workload to another locationYes: DNS geo-routing drops unhealthy locations automaticallyNo: Manual; DR runbook published
Fine-grained traffic steering across locations (priority, latency bias)Yes: routingTier priority groups, latency offset and tolerance per locationNo: Not documented
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 repositoryYes: GitHub, GitLab, Bitbucket
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: Buildpacks and Dockerfile
Named framework guides (Next.js, Django, Rails, Laravel…)Partial: Buildpack language conventions for Node, Python, Go, Java, Ruby, PHP, Rust — not per-framework guidesNo: Generic multi-language claims only
One-click template or app catalogYes: Template catalog, 87 entries (databases, queues, analytics, and more); deployable from the UI, CLI, Terraform, or PulumiPartial: Template API endpoint and an examples repo; no browsable catalog
Documented free tierYes: The account is free to create and set up, with no cloud account required; you pay only once workloads use computePartial: Trial
Local development story (emulator, local run, tunnel)Partial: Deploys a docker-compose project directly; port-forward and shell for working against remote instancesYes: Local cluster for development, plus a local demo install
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 translationPartial: Migrate-to-Kubernetes guide plus BYOK
Scaling & efficiency5
Metric-driven horizontal autoscalingYes: concurrency, rps, cpu, latency percentile, memory, KEDA, multi-metricPartial: cpu and memory plus KEDA with 8 scalers (beta, AWS/GCP)
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: Node-level recommendations only
Scale to zero with automatic wakeYes: Request-rate or concurrency triggers on serverless workloads; event-driven via KEDA for long-running and stateful onesPartial: KEDA min=0 (beta, AWS/GCP) plus scheduled stop/start
Published cold-start or wake latency figuresNo: No figures publishedNo: Not documented
Spot or preemptible instance supportPartial: Spot allocation in Managed Kubernetes node poolsYes: Spot instances via node auto-provisioning, cited as a cost-optimisation feature
Networking & edge7
First-party CDN or edge cachingNo: Docs cover configuring an external CDN; no first-party CDNNo: 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: Egress is a Squid-proxy tutorial
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: Manual VPC peering
Encrypted service-to-service networking as a platform defaultYes: Sidecar-based service mesh providing mTLS between workloads by defaultPartial: mTLS available; Envoy is ingress only
Application-layer request authentication at the edgeYes: JWT validation at the edge: multiple issuers, remote JWKS, claim-to-header mapping, per-path rulesPartial: Basic auth and mTLS
Static IP addresses for inbound or outbound trafficYes: Reserved static public IP per location, attachable to a load balancerYes: Static IP on by default
Storage & data services6
Managed relational or key-value databases as a first-party productYes: Postgres, Redis, MySQL, and more from the template catalogYes: Managed databases
Persistent volumes attachable to a scaled-out workloadYes: One volume per replica, preserved when the workload scales downPartial: Docs state volumes cannot be shared between replicas
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: Managed DB backups
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 primitiveYes: Cron jobs and lifecycle jobs as service types
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 workloadPartial: Manual IRSA; the only cross-cloud path uses a static key file
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 allYes: Built-in plus External Secrets Operator across four providers
Role-based access control granularityYes: Permissions expressed as verbs per resource type, granted to users, service accounts, groups, or workload identitiesYes: 5 built-in plus custom roles across three scopes
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 trailPartial: 3-30 days by plan, no export
Third-party compliance certificationsYes: SOC 2 Type II, PCI DSS Level 1, HIPAA, GDPRPartial: Best-practices framing plus HIPAA eligibility and a BAA
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 caseNo: Not a documented use case
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: Prometheus and Thanos, but not self-service
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, SyslogPartial: Sales-gated
Default log retentionYes: 30 days by default, adjustable per orgYes: 12 weeks default, configurable
Built-in alerting with notification channelsYes: Pre-provisioned alert rules with configurable contact points; notifications are off until a contact point is addedPartial: Inside sales-gated Observe
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 CLIYes: qovery shell and port-forward
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 cutoverNo: RollingUpdate or Recreate only
Ephemeral preview environment per pull requestYes: Per-PR preview environmentsYes: Blueprint clone with auto-stop rules
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: Qovery/qovery, 464,641 downloads, actively released
Complete public API referenceYes: Full API and CLI referenceYes: ~550 endpoints
MCP server for AI-agent operation of the platformYes: First-party, with documented setup for Claude, Codex, Cursor, Gemini CLI, VS Code and AntigravityYes: Hosted, OAuth or token, read-only by default with an explicit write opt-in
Machine-readable documentation (llms.txt, per-page markdown)Yes: llms.txt published and referenced from every pageYes: llms.txt
Ephemeral sandboxes for running untrusted or AI-generated codeYes: Sandboxes documentedNo: Not documented
Core product available as open sourceNo: Not open sourcePartial: The deployment engine is GPL-3.0; the control plane is not
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 imagesNo: Nothing
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 workloadsPartial: Per-application GPU allocation on a dedicated GPU nodepool; AWS EKS with Karpenter only
Commercial terms6
Published compute and memory unit pricesNo: No price list in the documentation snapshotNo: Not published
Published uptime SLA with a numberYes: 99.999% uptime SLAYes: 99.9% on Business
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 publishedYes: Your cluster, your registry, standard Helm, plus a Terraform exporter
Public community channelPartial: Support via Slack and Discord referenced in docs; no public community forum documentedYes: Public Discord plus a Discourse forum
Named reference customers publishedPartial: Customer stories exist off-docs; none named in the documentation snapshotYes: Talkspace, Alan, Powens, Prezi, Getsafe
Vendor continuity risk signalsPartial: Independent; funding and headcount not documented in the snapshotPartial: Changelog abandoned; TF provider ships constantly

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: a fintech spanning AWS and Azure with a PCI audit on the calendar. The workloads need specific accounts and regions, credential-free access to services in both clouds, and a paper trail an auditor will accept. That is platform work Qovery leaves with you and Control Plane ships as the product.

Qovery fits: a product team on AWS that wants previews and cleaner deploys. One cloud, containers, an ops setup that basically works, just too much friction per deploy. A layer that automates environments in the account you already run is the shortest path, and Qovery does it well.

Frequently asked questions

Is Control Plane a Qovery alternative?

They overlap on running workloads in your own cloud account, but at different depths. Qovery automates deployments on infrastructure you operate; Control Plane virtualizes the infrastructure itself: clusters, networking, identity, and compliance become the platform's job, across clouds and on-prem at once.

Does Control Plane support preview environments?

Workloads and virtual clouds are created through the API, CLI, or Terraform, so CI can stand up and tear down per-branch environments, and scale-to-zero means idle previews cost nothing while they wait. Qovery's git-integrated preview flow is more turnkey; if that is the headline requirement, it is a fair reason to pick Qovery.

Do I have to manage Kubernetes with Control Plane?

No. You never operate a cluster, patch a node, or write manifests, including when workloads run in your own accounts or on your own servers. Qovery-managed clusters also spare you upgrades; the structural difference is that Control Plane does it across clouds and on-prem as one layer, with networking, identity, and compliance included.

When is Qovery the better choice?

A single primary cloud, container-only workloads, compliance already handled, and the pain concentrated in deploy flow rather than infrastructure. In that shape, an automation layer is the right size of solution.

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