Choose the infrastructure that fits your product
Your application may need a different cloud bill, a particular workload location or an installation on your customer’s servers. As it grows, the platform still needs capacity, releases, security checks and new environments.
Ankra brings server provisioning, Kubernetes operations and application delivery into one product on supported infrastructure. It also provides a common autoscaling integration for those public-cloud server routes, built-in CI scanning and a view of vulnerabilities in running workloads.
Qovery is a capable alternative with substantial overlap. The practical difference is which foundation each product creates and which operating work stays with your team. Both have AI tools, APIs, Terraform workflows and support for Helm. Qovery’s Agent Tasks, in open beta, run AI agents inside your infrastructure, and its Copilot can apply well-defined fixes to failed clusters. Evaluate them on the infrastructure and release process you intend to use.
Build the foundation on servers you control
Qovery’s native provisioning creates provider-managed Kubernetes, meaning EKS on AWS, GKE on Google Cloud, AKS on Azure and Kapsule on Scaleway. It includes networking and cluster maintenance on that path.
Ankra also creates the Kubernetes control plane and workers on ordinary servers. On AWS EC2, you can choose kubeadm or k3s, with the AWS cloud controller and EBS storage integration. Ankra offers server provisioning on Hetzner, OVHcloud, UpCloud and DigitalOcean, and private provisioning on Proxmox VE. Include ingress, TLS and DNS in the supported creation workflow.
In November 2024 Qovery announced it was decommissioning its EC2 (K3s) cluster offer, citing limited adoption and no node autoscaling. It still supports existing k3s and vanilla Kubernetes through BYOK. Its EU sovereign-cloud guide describes Hetzner and OVHcloud through that route. BYOK leaves cluster lifecycle and infrastructure upkeep with your team; Qovery can install optional networking components during setup.
Choose Ankra for this difference when you want the product to create and operate that server foundation. Azure and Google Cloud are supported through provider-managed Kubernetes and import routes; Ankra’s current server-provisioning list does not establish kubeadm or k3s creation on Azure VMs or Google Compute Engine.
Use a common workflow for node scaling
There are two separate jobs. One is scaling application replicas, and the other is adding the servers those replicas need.
Qovery provides application HPA and KEDA options. HPA uses Kubernetes resource metrics. Its KEDA event-driven autoscaling is available on AWS and GCP clusters, enabled as a cluster add-on and limited to KEDA’s built-in scalers. Node scaling uses Karpenter on EKS, GKE Autopilot, and provider autoscaling on AKS and Kapsule. Those mechanisms can remove substantial operating work on its native clouds.
Ankra’s node autoscaling connects the upstream Kubernetes Cluster Autoscaler to Ankra’s provisioning pipeline. The same integration adds and removes workers on AWS EC2, Hetzner, OVHcloud, UpCloud and DigitalOcean. You enable it per node group and set minimum and maximum counts; Ankra installs the autoscaler on first enable. Scale-down drains nodes and respects PodDisruptionBudgets.
That is a common scaling workflow across those supported clouds. Provider APIs still differ underneath it. It scales the existing group’s server configuration; it does not promise Karpenter-style automatic selection of a new instance type for every pod. The documented minimum is one worker per group, and existing clusters need a compatible agent.
Compare cost decisions and the changes they require
Both products provide cost controls. Qovery offers spot instances, environment schedules and node optimisation. Its KRR integration recommends application CPU and memory requests or limits from historical usage. With Qovery Observe enabled, those recommendations use historical usage, and they are available through CLI and API, including for agent workflows. Recommendation and application of a change are separate steps.
Ankra’s Cloud Cost combines fleet estimates, utilisation evidence, savings recommendations and what-if sizing. Compare the same cluster shape across provider catalogues, or price private capacity using a rate card. Like-for-like matching keeps shared and dedicated CPU classes distinct where possible, and unpriced resources remain visible.
Ankra AI can propose supported capacity changes for confirmation. Resize capabilities and disruption depend on the provider; a cheaper estimated shape does not guarantee an in-place downgrade. Budgets and the cost autopilot work through the CLI, API and Ankra AI; their portal screen is in closed beta. Estimates also need a separate review of egress, discounts, availability, storage and migration effort before they become a buying decision.
Bring checks into the release workflow
Qovery has built-in image builds and ordered deployment stages, plus lifecycle jobs and external CI integrations. It can use a pre-built image instead of building from Git. Its open-source engine also supports Kubernetes BuildKit builders and a rootless option. Building in Kubernetes is a shared capability.
Ankra Pipelines adds a declared path for tests, rootless image builds, Semgrep source checks, Checkov configuration checks and Trivy image scans. A policy gate evaluates the findings before the approved digest is published for application delivery. Pipeline authority comes from an administrator-approved default-branch definition, so a pull request cannot widen its own permissions.
The concrete Ankra proposition is tests, scanner findings and a gate on the image being released in the same platform. Compare that with the checks you configure in Qovery’s jobs or existing CI. Some Ankra stage kinds, including in-pipeline approval and verification, do not execute yet. Application previews are a separate working route. Builds may use Ankra’s platform fallback when the selected cluster cannot run the builder; disable that fallback if source must stay inside your infrastructure.
See risk in the workloads you run
Qovery documents SSO, RBAC, secret management and audit controls, and lists SOC 2 Type II among its certifications. Its pricing includes the SOC 2 report on Business and Enterprise plans. Its security offering also covers encryption, isolation and a self-hosted control plane. Features and retention depend on the plan.
Ankra’s Security Center provides a different workflow to evaluate. It covers findings from running workloads, optional software bills of materials, benchmark checks and vulnerability prioritisation using CISA’s Known Exploited Vulnerabilities catalogue and FIRST’s EPSS probabilities. It shows affected workloads and scanner coverage across the fleet. Each application’s Security section puts its pipeline’s Semgrep and Checkov findings beside its image CVEs. The baseline uses Trivy Operator and Kubernetes Pod Security Admission; policy mode defaults to Audit, while SBOM generation is opt-in.
This is a specific Ankra capability to demonstrate. Qovery’s published access and compliance controls do not establish an equivalent built-in fleet CVE, SBOM and exploitation-prioritisation view. Confirm the available workflow during evaluation, including any scanners or integrations added to either product. A benchmark dashboard does not establish vendor certification or guarantee application security.
When to choose Ankra, and when to evaluate Qovery
Choose Ankra when you want the product to build and operate Kubernetes on supported cloud servers or Proxmox VE, carry reusable stacks across environments, and bring CI checks and workload security into the operating workflow. Git-backed stacks and versioned profiles let you reuse a working foundation with different environment inputs.
Evaluate Qovery closely when EKS, GKE, AKS or Kapsule is your preferred foundation, or your team already operates Kubernetes and wants its application platform through BYOK. For private provisioning, also evaluate its EKS Anywhere integration, available on request. Private infrastructure, reusable templates and AI are available in both products.
Compare the work that remains
Use the same workload, infrastructure requirements and starting point.
- Create the foundation. Record server, cluster, networking and storage work done outside the product.
- Run the next release. Include tests, scan failures, image publication, a preview and rollback. Verify which failures actually block release.
- Change capacity. Trigger node scale-up and scale-down, inspect a sizing recommendation and record how it becomes a safe change.
- Investigate a vulnerability. Find every affected workload, establish scan coverage and carry a fix through release.
- Compare total cost. Include platform fees, infrastructure, CI and observability allowances, setup effort and recurring operating work.
Ankra’s pricing follows managed worker-vCPU usage, with the first 30 vCPUs free and infrastructure billed separately. Match Qovery’s plan and add-on scope to the same workload. Neither a feature list nor a list-price comparison establishes the savings your team will achieve.
Ankra’s strongest case is a supported route from the servers you choose to repeatable application operations, with provisioning, scaling, delivery checks and workload security connected.
Reviewed 9 October 2026 against linked documentation and Qovery’s open-source engine. Provider paths, plan scope and features can change.