What Is Virtual Kubelet? An In-Depth Explainer

In a standard Kubernetes cluster, the kubelet is the node-level agent responsible for executing instructions from the control plane and managing the pod lifecycle. Virtual Kubelet generalizes this concept by decoupling the kubelet from a physical or virtual machine.

Virtual Kubelet is an open-source implementation that registers itself with the Kubernetes API as a node, but does not run containers locally. Instead, it acts as an abstraction and translation layer, forwarding pod specifications to an external compute provider and reporting status back to the control plane. From the scheduler’s perspective, this virtual node behaves like any other node in the cluster.

This model allows Kubernetes to schedule workloads onto non-traditional backends such as serverless container platforms like Azure Container Instances. The result is an elastic extension of your cluster that can burst into on-demand infrastructure without changing application manifests, APIs, or operational workflows. For platform teams using Plural, Virtual Kubelet fits naturally into hybrid and multi-environment setups, enabling consistent Kubernetes primitives across both managed nodes and external execution environments.

Key takeaways:

• Connect to serverless platforms for on-demand scaling: Virtual Kubelet allows you to treat external services like AWS Fargate as if they were nodes in your cluster. This lets you handle bursty workloads and scale your applications without provisioning, managing, or paying for idle cluster capacity.
• Maintain consistent tooling and workflows: Since Virtual Kubelet presents serverless environments as standard nodes, your team can continue using familiar tools like kubectl and existing GitOps pipelines. This approach reduces operational overhead by offloading server management to the provider without disrupting established development practices.
• Plan for provider-specific configurations: Virtual Kubelet delegates networking and storage to the underlying provider, bypassing standard CNI and CSI plugins. This means you must manage security groups, network policies, and persistent storage using the provider's native tools, requiring careful planning to ensure security and application portability.

What Is Virtual Kubelet?

Virtual Kubelet is an open-source implementation of the Kubernetes kubelet that allows a cluster to schedule pods onto external, typically serverless, container runtimes. In a conventional Kubernetes setup, the kubelet runs on every node and is responsible for reconciling PodSpecs with containers running on that machine. Virtual Kubelet preserves this contract with the control plane but removes the assumption that a node maps to a physical or virtual host.

Instead of managing local containers, Virtual Kubelet registers itself with the Kubernetes API server as a node and delegates pod lifecycle operations to a third-party execution environment. From Kubernetes’ perspective, this virtual node behaves like any other schedulable node, often advertising large or effectively unbounded capacity. This abstraction lets teams extend a cluster with on-demand compute without provisioning or operating the underlying infrastructure.

This model is well suited for bursty workloads, batch jobs, and short-lived tasks, or for isolating specific classes of applications onto a different cost or execution profile, all while continuing to use standard Kubernetes manifests, APIs, and tooling. Platforms like Plural can incorporate Virtual Kubelet as part of a broader hybrid or multi-environment strategy without introducing a separate operational model.

How Virtual Kubelet Bridges Kubernetes with External Providers

Virtual Kubelet acts as a translation layer between the Kubernetes control plane and external compute providers. It watches for pods scheduled onto its virtual node and converts Kubernetes API objects into provider-specific API calls. To users and automation, this process is invisible: workloads are still deployed with kubectl and defined in YAML, just as they would be for any other node.

This integration is implemented through a pluggable provider architecture. Each provider encapsulates the logic required to interact with a specific backend, such as AWS Fargate, Azure Container Instances, Alibaba Cloud ECI, or HashiCorp Nomad. When deploying Virtual Kubelet, you configure it with a provider, making the system extensible and adaptable to different serverless or external runtimes without changes to core Kubernetes behavior.

Virtual Kubelet’s Role in the Kubernetes Architecture

Within the Kubernetes architecture, Virtual Kubelet presents itself as a node that represents the aggregate capacity of the connected provider. When the scheduler assigns a pod to this node, Virtual Kubelet intercepts the assignment and uses the provider API to create and manage the corresponding workload outside the cluster.

Throughout the pod lifecycle, Virtual Kubelet reports status back to the Kubernetes API server, including phase transitions, health information, and logs. This ensures that externally executed workloads are observable and manageable using the same Kubernetes-native tools as in-cluster pods. Conceptually, Virtual Kubelet extends the Kubernetes API boundary, allowing the control plane to manage compute resources that exist entirely outside the cluster’s physical node pool.

How Virtual Kubelet Works

Virtual Kubelet integrates with the Kubernetes control plane by presenting itself as a standard kubelet-backed node. It registers with the API server like any other node, but instead of managing containers on a local host, it delegates all pod lifecycle operations to an external execution environment, typically a serverless container platform. This creates a clean abstraction layer that allows Kubernetes to schedule and manage workloads that run entirely outside the cluster.

Simulating Nodes and Managing the Pod Lifecycle

At startup, Virtual Kubelet registers a virtual node with the Kubernetes API server. This node appears in kubectl get nodes alongside physical and virtual machines, but it is not backed by actual CPU or memory on a host. When the Kubernetes scheduler assigns a pod to this virtual node, Virtual Kubelet becomes responsible for that pod’s lifecycle.

Rather than starting containers locally, it intercepts the pod specification and translates lifecycle events—create, update, and delete—into operations understood by the external provider. From the control plane’s perspective, the pod is running on a normal node, which means existing controllers, admission policies, and operational tooling continue to work without modification.

Connecting the Kubernetes API to Providers

Virtual Kubelet itself does not execute containers. Its extensibility comes from a provider-based architecture that acts as a bridge between the Kubernetes API and external compute services. Each provider encapsulates the logic required to map Kubernetes primitives, primarily pods, to a specific backend platform.

When a pod is scheduled to the virtual node, Virtual Kubelet forwards the pod specification to the configured provider, such as one targeting AWS Fargate or Azure Container Instances. The provider then provisions and manages the workload using the native APIs of that platform. This design allows Kubernetes to orchestrate workloads across heterogeneous environments through a single, consistent control plane.

Handling Resource Allocation and Scheduling

To influence scheduling behavior, Virtual Kubelet typically advertises its virtual node as having very large or effectively unbounded resource capacity. This prevents the scheduler from rejecting pods due to local resource constraints and makes the virtual node a viable target for burst or overflow workloads.

Actual resource allocation and enforcement are delegated to the external provider at runtime. This makes Virtual Kubelet well suited for unpredictable or spiky workloads where pre-provisioning cluster nodes would be inefficient. The trade-off is increased complexity in observability and capacity tracking across hybrid environments. Platforms like Plural address this by providing unified visibility and management across both in-cluster nodes and externally executed workloads, keeping operational complexity manageable as clusters extend beyond their physical boundaries.

Key Benefits of Virtual Kubelet

Integrating Virtual Kubelet into a Kubernetes environment provides clear advantages for platform and infrastructure teams. By abstracting node management and delegating execution to external compute providers, it addresses recurring challenges around cost efficiency, scalability, and operational complexity. This approach extends cluster capacity without increasing the size or management surface of the underlying node pool.

Simplify Resource Management and Cut Costs

Virtual Kubelet simplifies resource management by allowing workloads to run on external services that do not require you to provision or maintain servers. Instead of sizing a node pool for peak demand and paying for idle capacity, you can schedule suitable workloads onto a virtual node backed by a pay-per-use execution model.

Because the virtual node advertises itself as schedulable capacity while delegating execution externally, you avoid overprovisioning cluster resources. Costs align more closely with actual usage, making this model particularly effective for batch jobs, intermittent workloads, and environments with uneven traffic patterns.

Scale Seamlessly with Serverless Integration

Virtual Kubelet enables near-instant, on-demand scaling by exposing serverless container platforms as standard Kubernetes nodes. When in-cluster capacity is exhausted, the scheduler can place additional pods onto the virtual node without waiting for new virtual machines to be provisioned.

This “burst to serverless” behavior happens transparently at the scheduling layer, preserving existing deployment pipelines and manifests. It allows teams to absorb sudden traffic spikes or workload surges without complex auto-scaling configurations or long node startup times, while still operating entirely through Kubernetes-native workflows.

Reduce Operational Overhead

Offloading pod execution to managed, serverless environments significantly reduces operational overhead. For workloads running on a virtual node, the cloud provider is responsible for the operating system, container runtime, patching, and underlying hardware.

This shifts the responsibility away from platform teams, eliminating routine tasks such as node maintenance, security hardening, and capacity planning for those workloads. As a result, teams can focus on higher-value concerns like application architecture, platform reliability, and developer experience. In environments managed with Plural, this model aligns well with centralized governance while minimizing the day-to-day operational burden.

Supported Platforms and Providers

Virtual Kubelet’s extensibility is driven by its provider model. A provider is a pluggable component that translates Kubernetes API interactions into the native operations of an external platform, such as a serverless container service or another orchestrator. This design allows a standard Kubernetes control plane to project capacity onto heterogeneous backends by exposing them as virtual nodes.

The ecosystem includes both community-maintained and experimental providers, and the architecture is intentionally open-ended. Teams can integrate new backends without modifying the core Virtual Kubelet logic, making it possible to attach Kubernetes scheduling semantics to a wide range of execution environments.

AWS Fargate and Azure Container Instances

The most widely used providers connect Kubernetes to serverless container platforms, notably AWS Fargate and Azure Container Instances. These integrations allow pods to be scheduled directly onto managed, on-demand infrastructure without provisioning or maintaining virtual machines.

When a pod is assigned to a virtual node backed by one of these services, the provider converts the pod specification into the required API calls to launch and manage the container remotely. This approach is well suited for stateless services, batch jobs, and burst workloads, where elastic scaling and consumption-based pricing provide clear advantages. From the developer’s perspective, deployments remain fully Kubernetes-native, using the same manifests and tooling as in-cluster workloads.

Alibaba Cloud ECI and HashiCorp Nomad

The provider ecosystem extends beyond the major hyperscalers. Support for Alibaba Cloud Elastic Container Instance enables similar serverless execution models for teams operating in that cloud environment.

Virtual Kubelet is also not limited to serverless runtimes. The provider for HashiCorp Nomad demonstrates how Virtual Kubelet can bridge entirely different orchestration systems. In this model, Kubernetes schedules pods onto a virtual node, and the provider translates those requests into Nomad jobs. This allows organizations to centralize workload scheduling behind a Kubernetes API even when the underlying execution platforms differ.

Building Custom Provider Integrations

When no existing provider fits a given backend, teams can build their own. Virtual Kubelet is structured to clearly separate Kubernetes-facing responsibilities from provider-specific logic. Custom providers implement a well-defined pod lifecycle interface that covers creation, deletion, updates, and status reporting.

This modularity makes it possible to integrate proprietary platforms, specialized compute environments, or internal scheduling systems directly into Kubernetes. The result is a unified control plane where standard cluster nodes and custom infrastructure resources are managed through the same Kubernetes abstractions, an approach that aligns well with platform-layer tooling and governance models such as those provided by Plural.

Core Features for DevOps Teams

For DevOps and platform teams, adopting any new Kubernetes component depends on how well it integrates with existing operational workflows. Virtual Kubelet is designed to extend familiar Kubernetes primitives to provider-backed environments, including serverless runtimes, without introducing a parallel management model. It operates as a translation layer that preserves standard lifecycle management, observability, and health semantics, regardless of where workloads actually execute.

Manage the Full Pod Lifecycle

Virtual Kubelet enables full lifecycle control using standard Kubernetes tooling. Pods scheduled to a virtual node can be created, updated, scaled, and deleted using the same kubectl commands, Kubernetes API calls, and GitOps controllers used for in-cluster workloads.

Because Virtual Kubelet integrates directly with the Kubernetes API server, existing CI/CD pipelines and deployment strategies do not need to change. This allows teams to extend automation, rollout policies, and declarative configuration practices to serverless or external environments while maintaining a consistent operational surface across physical and virtual nodes.

Access Logs, Metrics, and Debugging Tools

Virtual Kubelet preserves access to application logs and runtime signals by streaming data from the underlying provider back into Kubernetes-native interfaces. Logs from externally executed pods are available through standard commands such as kubectl logs, keeping debugging workflows centralized.

Pod status and metrics are also surfaced through the Kubernetes API, allowing existing monitoring and observability systems to continue functioning without custom integrations. In environments managed with Plural, these logs and metrics can be viewed through a unified Kubernetes dashboard, providing consistent observability across in-cluster and external workloads without additional access management overhead.

Report Status and Perform Health Checks

Reliability depends on accurate and timely health reporting. Virtual Kubelet continuously relays pod state from the external provider back to the Kubernetes control plane, ensuring that pod phase, readiness, and failure conditions are accurately represented.

It supports standard Kubernetes liveness and readiness probes, allowing service routing, restarts, and self-healing behaviors to work as expected. If a workload running on a serverless backend becomes unhealthy, Kubernetes detects the condition through Virtual Kubelet and responds using its normal reconciliation logic. This preserves the resilience guarantees teams expect from Kubernetes, even when execution is delegated beyond the cluster’s physical infrastructure.

Common Challenges and Considerations

While Virtual Kubelet provides a powerful mechanism for extending Kubernetes beyond traditional nodes, it introduces architectural trade-offs that must be understood before production adoption. It is not a drop-in replacement for a standard kubelet and shifts responsibility for key subsystems such as networking, storage, and parts of security to external providers. Platform teams should evaluate these constraints early to avoid unexpected operational complexity or security gaps when running hybrid or serverless workloads.

Overcoming Networking and CNI Limitations

Virtual Kubelet does not implement the Container Network Interface (CNI). As a result, pods scheduled onto virtual nodes do not participate in the cluster’s native pod-to-pod networking model, and Kubernetes network policies cannot be enforced using familiar CNI plugins.

Instead, networking is fully delegated to the underlying provider. Traffic control, isolation, and routing are handled using provider-native constructs, such as VPC security groups or cloud-specific firewall rules. This requires teams to reason about networking at the provider layer rather than the Kubernetes layer, and to ensure that equivalent segmentation and security controls are in place outside the cluster.

Working with Storage and Service Restrictions

Virtual Kubelet also does not implement the Container Storage Interface (CSI), which limits the use of Kubernetes-native persistent storage abstractions. PersistentVolumes and PersistentVolumeClaims may not be supported or may behave differently depending on the provider.

Stateful workloads must typically rely on provider-specific storage mechanisms, such as managed file shares or object storage, mounted through custom configuration. This reduces workload portability and increases the need for provider-aware application design. Service discovery can also diverge from Kubernetes defaults, often depending on the provider’s DNS and load-balancing systems rather than cluster-internal services, further reinforcing the need to avoid tight coupling to Kubernetes-native storage and networking primitives.

Managing Compatibility and Security

Introducing Virtual Kubelet expands the trust boundary of the cluster. The virtual node represents an external execution environment, so securing communication between the Kubernetes API server and the provider is critical. This includes carefully scoped authentication credentials and well-defined RBAC policies that limit what the virtual node can access.

Not all Kubernetes objects are supported on virtual nodes. For example, DaemonSets cannot run because there is no underlying host, and some security contexts, volume types, or privileged operations may be incompatible. Thorough compatibility testing is required before migrating critical workloads. Platforms like Plural help enforce consistent RBAC and policy controls across both physical and virtual nodes, reducing the risk of configuration drift or over-privileged access.

Addressing Integration Complexity

Running Virtual Kubelet across multiple providers introduces integration complexity due to differences in APIs, feature sets, and operational semantics. Without a unifying approach, teams risk inconsistent configurations and fragmented operational practices.

A centralized control plane and declarative workflows are essential to manage this complexity at scale. Using GitOps-driven deployment and configuration management with Plural allows teams to standardize how applications and infrastructure are defined and promoted across environments. This ensures that workloads running on traditional nodes and virtual nodes adhere to the same version-controlled, auditable processes, even when backed by different provider technologies.

Installing and Configuring Virtual Kubelet

Deploying Virtual Kubelet requires some upfront preparation and careful provider-specific configuration. While the operational model is Kubernetes-native, the fact that workloads execute outside the cluster means authentication, permissions, and integration details matter more than with standard nodes. This section outlines what teams need in place before installation and how to approach configuration securely and repeatably.

Prerequisites and Installation Methods

Before installing Virtual Kubelet, you must have access to a functioning Kubernetes cluster and a correctly configured kubectl context pointing to it. This is required for deploying manifests, inspecting nodes, and validating that the virtual node registers correctly with the API server.

In most setups, Virtual Kubelet itself runs as a pod inside the cluster. Installation is typically done by applying provider-specific manifests or Helm charts that define the Virtual Kubelet deployment, ServiceAccount, and supporting configuration. While not strictly required, tools like Skaffold can simplify local development and iteration when testing provider integrations or custom configurations.

You will also need a container image build and registry workflow. Any pods scheduled onto a virtual node must reference images that are accessible both to the Kubernetes control plane and to the external provider backing the virtual node.

Provider-specific Configuration

Virtual Kubelet configuration is tightly coupled to the provider it targets. The core component acts as a translation layer, but each provider requires its own credentials, network settings, and runtime parameters.

For example, configuring the Azure Container Instances provider requires Azure credentials, typically in the form of a service principal with permissions to create and manage container instances. The AWS Fargate provider relies on IAM roles, subnet selection, and VPC configuration to launch tasks securely. These details are usually passed to the Virtual Kubelet pod via environment variables or mounted configuration files.

Because these settings directly control how Kubernetes workloads are executed outside the cluster, provider documentation should be treated as required reading. Misconfigured credentials or networking can lead to failed pod scheduling or unintended exposure of workloads.

Setting up RBAC and Security

Role-Based Access Control is a critical part of any Virtual Kubelet deployment. The Virtual Kubelet pod needs permission to interact with the Kubernetes API server, including creating and deleting pods, reading pod specifications, and updating pod status fields. These permissions are typically granted through a dedicated ServiceAccount, along with a tightly scoped ClusterRole and ClusterRoleBinding.

Over-permissioning this component expands the cluster’s attack surface, while under-permissioning it leads to subtle and hard-to-diagnose failures. Managing these policies consistently across multiple clusters can become operationally expensive.

Platforms like Plural help mitigate this complexity by centralizing RBAC management. By mapping user and service identities through Kubernetes impersonation and synchronizing policies via GitOps, teams can enforce least-privilege access for Virtual Kubelet and related components across their entire fleet, without managing RBAC definitions cluster by cluster.

Virtual Kubelet Best Practices

Adopting Virtual Kubelet requires a strategic approach to ensure your architecture remains secure, performant, and resilient. While it simplifies node management, it introduces a new layer of abstraction with its own set of operational considerations. Following established best practices helps mitigate risks and allows your team to fully capitalize on the benefits of a serverless container infrastructure. Key areas of focus include tightening security controls, optimizing resource allocation for performance, and developing a clear strategy for troubleshooting integration issues.

Implement Robust Security and Monitoring

Extending your Kubernetes control plane to external providers can introduce security gaps, such as insecure default configurations and a lack of complete resource visibility. To counter this, you must enforce strict security policies and establish comprehensive monitoring. Start by configuring fine-grained Role-Based Access Control (RBAC) for the Virtual Kubelet itself, ensuring it has only the permissions necessary to manage the pod lifecycle. Implement network policies to control traffic flow between virtual pods and other cluster resources.

Centralized observability is critical for maintaining security and operational health. A unified platform like Plural provides a single-pane-of-glass console that offers deep visibility into both standard and virtual nodes. This allows you to monitor logs, metrics, and resource states across your entire fleet from one place, simplifying the process of detecting anomalies and enforcing security configurations consistently.

Optimize for Performance

Performance optimization with Virtual Kubelet involves understanding the characteristics of the underlying provider and aligning your workloads accordingly. Since you are not managing the nodes, you rely on the provider's ability to provision resources on demand. This means you should pay close attention to pod startup times, which can vary significantly between providers like AWS Fargate and Azure Container Instances.

To maximize efficiency, use Horizontal Pod Autoscalers (HPAs) to scale your applications based on actual demand, taking full advantage of the serverless model. You can also leverage flexible deployment strategies to provision specialized resources, such as GPUs for machine learning workloads, without managing the complex underlying infrastructure. Properly defining resource requests and limits in your pod specifications is also crucial to ensure the provider allocates appropriate capacity for stable performance.

Troubleshoot Common Implementation Issues

Integrating Virtual Kubelet can present unique challenges, particularly with networking, storage, and version compatibility. One common issue is regression during Kubernetes upgrades, where changes in the API can affect Virtual Kubelet's behavior. Before any upgrade, thoroughly review the provider’s documentation for compatibility notes and test the new version in a non-production environment.

Integration challenges often persist across different cloud environments, especially with CNI plugins and storage providers that may not be fully compatible with the virtual node model. When issues arise, start by verifying network connectivity between the Kubernetes control plane and the provider's API. Check for misconfigured credentials or permissions that might block resource creation. Using a tool with advanced diagnostics, like Plural's AI Insight Engine, can help accelerate root cause analysis by correlating logs and configuration data to pinpoint the source of failure.

Key Use Cases for Virtual Kubelet

Virtual Kubelet’s core function is to abstract the underlying compute, which opens up several powerful operational patterns. By decoupling the Kubernetes control plane from the physical or virtual machines that traditionally make up a cluster, you can extend your workloads into new environments without adding operational complexity. This flexibility is particularly useful for serverless computing, burst scaling, and managing distributed infrastructure across hybrid and edge environments.

Running Serverless Container Workloads

One of the primary applications for Virtual Kubelet is to integrate Kubernetes with serverless container platforms like AWS Fargate and Azure Container Instances (ACI). It acts as a connector, allowing the Kubernetes scheduler to treat these serverless environments as nodes with virtually infinite capacity. When you deploy a pod to a virtual node, the provider provisions the necessary compute resources on demand. This model eliminates the need to manage a pool of worker nodes, patch operating systems, or worry about scaling node groups. Your team can focus entirely on the application, paying only for the exact resources a pod consumes while it's running.

Handling Burst Capacity and Multi-cloud Needs

Virtual Kubelet provides an effective solution for handling sudden, unpredictable traffic spikes. Instead of overprovisioning your cluster with expensive, often-idle nodes, you can configure it to "burst" workloads onto an external provider. When your cluster's resources are fully utilized, the Kubernetes scheduler can automatically place new pods on a virtual node backed by a serverless platform. This gives you on-demand access to massive scale without the delay of provisioning new VMs. This same principle applies to multi-cloud strategies, where Virtual Kubelet can bridge a single Kubernetes control plane to different cloud providers, enabling workload distribution based on cost, features, or resiliency requirements.

Deploying to Edge and Hybrid Environments

For organizations with distributed infrastructure, Virtual Kubelet simplifies the management of workloads running in hybrid or edge computing environments. You can register an on-premises data center, an IoT gateway, or a remote office as a virtual node in your central Kubernetes cluster. This allows you to use standard Kubernetes APIs and GitOps workflows to deploy and manage applications consistently across your entire infrastructure fleet. This unified approach is critical for fleet management, where platforms like Plural provide a single pane of glass to oversee deployments across core data centers and remote edge locations from one control plane.

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Frequently Asked Questions

Is Virtual Kubelet a direct replacement for the standard kubelet on my worker nodes? Think of Virtual Kubelet as an extension, not a replacement. It doesn't manage containers on a physical or virtual machine within your cluster. Instead, it registers a "virtual" node that delegates pod execution to an external service, like AWS Fargate. You'll still run the standard kubelet on your regular worker nodes for your baseline workloads, while using Virtual Kubelet to add on-demand, serverless capacity for specific use cases like handling sudden traffic bursts.

How does pod-to-pod communication work if Virtual Kubelet doesn't use a CNI plugin? This is a key architectural difference. Since Virtual Kubelet doesn't implement the Container Network Interface (CNI), networking is handled entirely by the underlying provider. For example, a pod running on a virtual node backed by AWS Fargate will use AWS VPC networking rules. This means you'll manage connectivity and security using tools like VPC security groups instead of Kubernetes NetworkPolicies. Communication between pods on virtual nodes and pods on regular nodes typically requires careful configuration of your cloud network.

Can I run stateful applications like databases on a virtual node? Running stateful applications on virtual nodes is challenging and generally not recommended for production databases. Virtual Kubelet doesn't support the Container Storage Interface (CSI), so you can't use standard Kubernetes PersistentVolumes. While you can mount storage using provider-specific methods, like attaching an Azure File Share, this approach ties your application to that provider and lacks the robust, portable storage management you get with Kubernetes. Virtual nodes are best suited for stateless or short-lived, job-based workloads.

When should I use Virtual Kubelet instead of a traditional cluster autoscaler? The choice depends on your workload patterns and speed requirements. A cluster autoscaler is great for predictable growth, as it adds new nodes to your cluster when resources run low, a process that can take a few minutes. Virtual Kubelet excels at handling unpredictable, sudden spikes in demand. It provides near-instant capacity by scheduling pods on a serverless platform without waiting for new VMs to boot. It's ideal for "bursting" traffic that exceeds your cluster's provisioned capacity or for running short-lived tasks without dedicating a full node to them.

How can I maintain consistent security policies across both regular and virtual nodes? Maintaining consistent security requires a centralized approach to configuration and access control. Since virtual nodes operate outside your cluster's CNI, you can't rely on a single tool for network policies. However, you can and should enforce consistent Role-Based Access Control (RBAC) for all workloads. A unified management platform is essential here. For instance, Plural allows you to define RBAC policies in a Git repository and apply them across your entire fleet, ensuring that both your team's access and the permissions granted to components like Virtual Kubelet are managed consistently from a single control plane.