What is managed Kubernetes?
Managed Kubernetes is a cloud-hosted form of Kubernetes in which hyperscalers (like Azure, AWS, and GCP) run the cluster’s control plane for you. Instead of provisioning servers, generating certificates, and installing etcd yourself, you request a cluster through the provider and begin deploying containers.
While managed Kubernetes refers to a broad range of service models, Kubernetes as a service (KaaS) is a popular approach that allows teams to utilize Kubernetes features without managing the underlying control plane components. The provider patches and upgrades the control plane and often supplies integrations for load balancing, identity, and secret management.
This model drastically reduces operational burdens and cost: Customers typically pay for worker nodes (or pod resources in serverless models like GKE Autopilot or EKS Fargate) and, depending on the provider, a control-plane management fee—for example, EKS charges $0.10 per hour per cluster. There's no need to provision or manage control plane VMs. When a managed Kubernetes cluster is ordered through a cloud console or API, the provider automatically provisions the control plane and delivers a ready-to-use platform.
Actionable Kubernetes Security Best Practices
From locking down kubelets and the API server to enforcing mTLS and service account isolation, this cheat sheet helps you tackle threats across every layer of your Kubernetes stack.
How managed Kubernetes works
Kubernetes splits the cluster into two planes:
The control plane hosts the API server, etcd, scheduler, and controllers. It exposes the cluster API, stores desired and actual state, schedules pods, and orchestrates tasks.
The data plane consists of worker nodes running application workloads.
Across GKE, EKS, and AKS, the managed Kubernetes model is consistent: The provider operates the control plane, and customers own and secure everything that runs on top of it. In other words, customers don’t manage the underlying infrastructure directly but are responsible for configuring workloads and security in the data plane.
Some offerings also manage node provisioning: GKE Autopilot handles all node lifecycle operations, while AWS EKS Fargate provides serverless compute where you don't manage nodes at all. In standard managed modes (like EKS Managed Node Groups or AKS VMSS), the provider automates the orchestration of updates, but the user must often trigger the upgrade or define the maintenance window.
Managed vs. self-managed Kubernetes: Key differences
Self-managed and managed Kubernetes have important differences when it comes to operational effort, cost, scaling, and patching:
Self-managed offers full control but requires teams to handle upgrades, scaling workflows, and infrastructure maintenance. Since self-managed clusters require teams to operate and maintain all components themselves, long-term operational costs can be steep.
Managed Kubernetes simplifies deployment, automates control plane patching, and provides built-in high availability, enabling faster scaling with less operational overhead. Managed services typically offer predictable control plane costs, where customers pay for worker nodes and usage.
The bottom line? With a Kubernetes managed service provider, you trade control for speed and standardization. But there is one downside to keep in mind. Managed Kubernetes introduces a grey zone: Because providers operate the control plane and customers remain responsible for workloads, networking, IAM, and runtime security, risks surrounding security, compliance, and long-term maintenance are often overlooked by teams.
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Security considerations for managed Kubernetes environments
Using a hosted control plane reduces some attack surfaces but introduces others. Key risks include:
Misconfigured RBAC: Granting overly broad ClusterRole privileges or binding service accounts to cluster-admin are common mistakes.
Exposed dashboards and APIs: Misconfigured Service/Ingress rules or cloud security settings can unintentionally expose dashboards or kubelet endpoints to the public internet.
Weak network segmentation: Flat networks allow compromised pods to move laterally. Implementing network policy rules lets you restrict traffic between namespaces and services.
Unmanaged node images: Keep worker node OS images current by enabling node auto-upgrade and auto-repair features offered by GKE, EKS managed node groups, and AKS. Alternatively, adopt fully managed compute models like GKE Autopilot or EKS Fargate to eliminate node patching responsibilities entirely.
Over-permissioned service accounts: Prefer cloud-native workload identity mechanisms—EKS IAM Roles for Service Accounts (IRSA), GKE Workload Identity, or AKS Workload Identity—to grant pods least-privilege access to cloud APIs. These eliminate long-lived node credentials and reduce blast radius by binding IAM roles directly to Kubernetes service accounts.
To go deeper, download our Kubernetes security best practices cheat sheet for actionable guidance on RBAC, network policies, admission controls, and workload hardening.
Kubernetes Clusters: A Security Review
A Kubernetes cluster consists of a group of node machines designed to run applications within containers.
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Benefits and challenges of managed Kubernetes
Managed Kubernetes simplifies cluster operations, but the convenience comes both pros and cons.
Benefits:
Faster time to value: Clusters can be created and scaled in minutes.
Reduced operational overhead: The provider handles control-plane maintenance, multi-zone redundancy, and patching.
Built-in reliability and security integrations: Managed services offer service-level agreements and integrate with cloud-native IAM, logging/auditing, KMS-backed secrets management, and admission-time policy enforcement.
Challenges:
Limited control: You can’t customize control plane internals or rapidly adopt new Kubernetes features.
Inconsistent defaults: Each cloud provider sets different defaults for networking, storage, security, and versioning, making multi-cloud architectures complex.
Vendor dependency: Migrating clusters between providers may require retooling and data migration.
When to choose managed Kubernetes
Managed Kubernetes is a strong fit when you want enterprise-grade reliability without deep in-house Kubernetes expertise. Organizations adopting microservices can benefit from rapid cluster provisioning, auto-scaling, and integrated monitoring. It also suits teams operating across multiple projects or regions because managed services handle control plane availability and upgrades uniformly.
That said, self-managing may be necessary in air-gapped environments, for workloads subject to strict regulatory requirements, or when specialized networking and storage are required.
How Wiz addresses the shared responsibility model in managed Kubernetes
In managed Kubernetes environments, security responsibilities don’t disappear, but it can be tough to tell who they belong to. Wiz takes the guesswork out of the shared responsibility model by surfacing and securing the layers customers own. Here’s how:
Full visibility and protection: Wiz provides round-the-clock coverage for workloads. Wiz's agentless architecture connects via cloud and Kubernetes APIs to deliver immediate visibility across clusters and accounts without requiring DaemonSet deployment. For runtime protection, you can optionally deploy lightweight eBPF-based sensors through Wiz Defend to detect container escapes, lateral movement, and other runtime anomalies in high-risk environments.
Kubernetes Security Posture Management (KSPM): Identify and remediate risks such as overly permissive RBAC bindings, publicly exposed services, weak pod security standards, and missing network policies. Enforce guardrails across all clusters to prevent configuration drift.
Essential context: The Wiz Security Graph correlates Kubernetes workloads with cloud resources, identities, vulnerabilities, and permissions. This graph-based analysis exposes real attack paths, helping teams prioritize the issues that pose the highest risk to critical workloads.
Shift-left security: Wiz Code integrates into CI/CD pipelines to scan Kubernetes manifests, Helm Charts, and container images before deployment, preventing insecure artifacts from reaching production.
Near-zero CVE container images: WizOS levels up your managed Kubernetes security by providing hardened, minimal container images that shrink your attack surface from the start. By utilizing WizOS hardened images, teams ensure code-to-cloud security—reducing the vulnerability backlog before a single line of code is even deployed to the cluster.
By unifying Kubernetes Security Posture Management, workload protection, identity risk analysis, and container security in a single platform, Wiz helps teams reduce tool sprawl and focus on the risks that matter most within the shared responsibility model.
Ready to see for yourself? See how Wiz maps your cluster risks in minutes and schedule a demo today!
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