Edge Kubernetes Deployment: A Step-by-Step Guide

Architecting for the edge means rethinking core Kubernetes concepts. A centralized control plane must communicate with nodes over unpredictable networks, and those nodes must be able to function autonomously when disconnected. This isn't just a configuration tweak; it's a fundamental design principle that impacts everything from application deployment to security. You must plan for resource scarcity and build a networking model that is both secure and resilient.

This edge Kubernetes deployment guide breaks down these complex architectural decisions into actionable steps. We'll explore how to design your control plane, configure nodes for high availability, and implement a networking strategy that works for distributed environments, providing a solid foundation for your edge operations.

Key takeaways:

• Design for disconnection: Build your edge architecture around node autonomy. Use lightweight Kubernetes distributions and local caching for configurations and images, ensuring your edge locations can operate independently and recover from failures without a constant connection to the control plane.
• Secure the edge with a zero-trust model: Treat edge networks as untrusted. Enforce strict RBAC and network policies to isolate workloads, and adopt an egress-only communication pattern, like Plural's agent-based model, to eliminate inbound attack vectors and secure remote clusters behind firewalls.
• Centralize control with GitOps automation: Manage your distributed edge fleet through a centralized, GitOps-driven workflow. Codify all application and infrastructure configurations in Git to serve as the single source of truth, enabling consistent and auditable management of all edge nodes from a single platform like Plural.

What Is Edge Kubernetes?

Edge Kubernetes extends container orchestration from centralized data centers to the network’s edge—closer to where data is produced and consumed. Think factory floors, retail outlets, remote IoT gateways. By running workloads locally, you can meet low-latency requirements, process data on-site, and maintain uptime even with intermittent network links. This enables real-time decision-making, but also brings new architectural and operational constraints.

Defining Edge Computing

Edge computing processes data near its source instead of sending everything to a central cloud or data center. Computation happens directly on edge devices or nearby servers, reducing latency, conserving bandwidth, and improving responsiveness. This is critical for use cases like:

• Real-time industrial monitoring
• Autonomous vehicle control
• Interactive retail experiences

The key goal: deliver immediate, local insights where milliseconds matter.

Why Kubernetes at the Edge?

Kubernetes offers a consistent, API-driven way to deploy, scale, and manage containerized apps. At the edge, this consistency pays off in environments that are otherwise fragmented and hard to standardize. You can:

• Orchestrate workloads across thousands of nodes using the same declarative configs you use in the cloud
• Package apps once, run them anywhere (Kubernetes portability)
• Ensure resilience, self-healing, and automated updates—essential for large fleets you can’t touch manually

Challenges in Edge Kubernetes

Running Kubernetes at the edge isn’t just “smaller clusters”—it’s a different game:

• Unreliable networks → Difficult control plane communication and update rollouts
• Resource limits → Need lightweight distros (e.g., K3s) and tuned workloads
• Security risks → Nodes may sit in unsecured physical locations
• Operational complexity → Managing a diverse, distributed fleet demands automation and central oversight

These challenges require purpose-built architectures, optimized tooling, and security-by-design practices.

Key Components of an Edge Kubernetes Architecture

1. Designing the Control Plane

The control plane is the brain of your cluster—deciding scheduling, managing state, and handling API requests. At the edge, you can:

• Keep a centralized control plane in the cloud
• Run decentralized control planes closer to edge locations

The big challenge: keeping edge nodes functional over unreliable networks. Your design should ensure offline resilience—nodes must keep workloads running even when the API server is unreachable.

Some platforms, like Plural, solve this with agent-based architectures, where edge agents maintain secure, intermittent connections to the central management plane—no need for constant connectivity.

2. Configuring Edge Nodes for Autonomy

Edge nodes should be able to operate independently for hours or days without talking to the control plane. Best practices include:

• Running only essential components (kubelet, container runtime)
• Enabling local control loops to manage workloads without API calls
• Caching container images and configs locally so pods can restart without downloading assets again

These measures ensure that a pod crash or node reboot doesn’t mean downtime while waiting for reconnection.

3. Networking for Distributed Edge Clusters

Networking is the hardest part of edge Kubernetes—multiple clusters, inconsistent bandwidth, and untrusted networks.
Key considerations:

• How nodes talk to the control plane
• How edge locations talk to each other
• How to secure low-bandwidth, high-latency links

A common pattern is egress-only communication, where agents initiate outbound, encrypted connections to the control plane (avoiding inbound firewall rules or VPN overhead). This is how Plural CD simplifies secure multi-cluster management.

4. Managing Resources on Constrained Hardware

Most edge hardware can’t handle a full Kubernetes install. Lightweight, CNCF-conformant distributions like K3s are built for these environments—they have a small footprint and reduced overhead.

On top of that:

• Use resource requests and limits in pod specs to avoid noisy-neighbor problems
• Schedule workloads based on actual node capacity, not assumptions from cloud-sized clusters
• Monitor resource usage closely to prevent cascading failures

This keeps edge workloads stable, even under tight CPU, memory, or storage constraints.

How to Plan Your Edge Deployment

Edge deployments succeed or fail in the planning phase. Unlike cloud or data center setups, edge environments bring hardware limits, unstable networks, and heightened security risks that can’t be “fixed later.” Planning isn’t a one-time checklist—it’s an ongoing process of defining requirements, anticipating failure modes, and building an operational model that can scale without falling apart under real-world conditions.

Below are the core areas to address before you deploy your first container.

1. Assess Hardware and Network Conditions

Edge hardware is often small-form, low-power, and far less forgiving than data center gear. Inventory what’s available at each site: CPU, memory, storage, and power constraints. Kubernetes can orchestrate workloads in constrained environments, but it can’t magic away a lack of resources.

Your network baseline is equally critical. Measure:

• Bandwidth — to size data sync intervals
• Latency — to inform health check tuning
• Stability — to determine whether nodes need full offline autonomy

These metrics guide decisions like whether to use K3s or MicroK8s, how to configure probes, and how often to sync state back to the control plane.

2. Define Security from Day One

Edge nodes may be deployed in public or semi-secure locations, so assume physical access is possible. Your security model should include:

• Physical hardening (tamper detection, secure boot)
• Network isolation with Kubernetes Network Policies
• Secrets management (Kubernetes Secrets, sealed secrets, or external vaults)

Implement Role-Based Access Control (RBAC) to enforce least privilege. Managing RBAC at scale is tricky, but tools like Plural integrate with your central identity provider so you can apply policies consistently across thousands of clusters.

3. Capacity Planning for Constrained Nodes

Most upstream Kubernetes distributions assume data center-level resources. Edge sites rarely have that.
Steps to avoid overcommitment:

• Use lightweight distros like K3s or MicroK8s
• Profile workloads to measure real CPU/memory usage
• Set realistic resource requests/limits in manifests to prevent noisy-neighbor failures

Proactive capacity planning keeps nodes stable without requiring constant manual tuning.

4. Build a Data Management Strategy

At the edge, you’re dealing with two types of data:

• Application data — real-time streams, analytics inputs
• Operational data — logs, metrics, and status

Intermittent connectivity means you can’t rely on continuous upstream transmission. Solutions include:

• Local buffering (e.g., Prometheus remote_write with local storage)
• Batch uploads during connectivity windows
• Agent-based, pull-model architectures where the node calls out to fetch configs and send updates

Plural’s agent model follows this approach, avoiding the need for persistent inbound connections and working even over egress-only, flaky links.

A Step-by-Step Guide to Implementation

Deploying Kubernetes to the edge involves a structured process that moves from central control to distributed execution. While tools and specific commands may vary based on your chosen distribution, the fundamental steps remain consistent. This guide breaks down the implementation into four key stages, providing a clear path from setting up your central management layer to validating your first edge application. Following this process ensures a robust and functional edge environment ready for production workloads.

Set Up the Control Plane

The control plane acts as the central nervous system for your edge fleet, orchestrating deployments and managing communication. For many, this involves installing a standard Kubernetes distribution on a cloud node using tools like kubeadm and then layering on an edge management system like KubeEdge. This central node is responsible for synchronizing application states and configurations with all connected edge nodes.

Plural simplifies this foundational step by providing a unified control plane that can be deployed onto any Kubernetes cluster you designate for management. This abstracts away the manual setup and provides a scalable, API-driven foundation for managing your entire fleet from day one.

Configure Your Edge Nodes

Once the control plane is active, each edge node must be configured to join the cluster. This typically involves installing a lightweight agent on the edge device and using a security token generated by the control plane to establish a trusted connection. This process registers the node, making it visible to the scheduler and ready to receive workloads. The key is ensuring a secure and reliable communication channel between the edge and the cloud.

Plural’s architecture uses a lightweight deployment agent that polls the control plane for instructions. This pull-based model eliminates the need for direct ingress to the edge node, simplifying network configuration and enhancing security. The agent handles the connection automatically, streamlining the onboarding of new devices at scale.

Implement Network Security

Securing an edge deployment is critical, as it extends your infrastructure into physically diverse and often less secure environments. Kubernetes offers native tools like network policies for controlling traffic flow between pods and Role-Based Access Control (RBAC) for defining user and service permissions. Properly configuring these is essential to protect your applications and data from unauthorized access.

Plural helps enforce a consistent security posture across your fleet. You can define RBAC policies once and use Plural CD to sync them to all edge clusters, ensuring uniform access controls everywhere. The agent’s egress-only communication model further reduces the attack surface, preventing direct external access to your edge nodes and creating a more secure default configuration.

Validate and Test the Deployment

After configuration, you must validate that the entire system works as intended. A common practice is to deploy a sample application, such as Nginx, from the control plane and verify that it successfully runs on a designated edge node. This end-to-end test confirms that the control plane can schedule workloads, the edge node can pull the required container images, and the application is operational.

With Plural, this validation is built into the workflow. You can deploy an application using a GitOps pipeline and then use Plural’s embedded Kubernetes dashboard to inspect the edge node’s resources directly from the UI. This provides immediate feedback and allows you to confirm pod status, view logs, and ensure the deployment was successful without needing separate tools or direct cluster access.

How to Optimize Edge Performance

Once your edge deployment is running, the focus shifts to optimizing performance, reliability, and resource efficiency. Edge environments present unique constraints, from limited hardware to unreliable network connections, that require specific strategies to overcome. Effective optimization ensures your applications deliver low-latency responses and remain available even when facing network disruptions. By strategically managing resources, network traffic, and system observability, you can build a resilient and high-performing edge infrastructure.

Allocate Resources Strategically

Edge nodes operate in resource-constrained environments, making efficient resource allocation critical. Unlike data centers with abundant CPU and memory, edge devices require careful management to prevent performance bottlenecks. Kubernetes helps by allowing you to orchestrate microservices across these nodes, but you must define resource requests and limits for each container. This practice prevents any single application from consuming all available resources and starving other critical processes. Using a lightweight Kubernetes distribution can also reduce the baseline resource footprint. With Plural, you can monitor resource utilization across your entire fleet from a central console, helping you identify over-provisioned or under-resourced nodes and adjust allocations accordingly.

Optimize Network Traffic

Latency is a primary concern in edge computing. The goal is to process data as close to the source as possible to minimize delays. Deploying multiple Kubernetes clusters across edge locations helps localize data processing and reduces reliance on a central cloud. You can further optimize traffic using service meshes to intelligently route requests and Container Network Interface (CNI) plugins designed for performance. Plural’s agent-based architecture is well-suited for these environments, as it uses an efficient, egress-only pull model. This design minimizes network chatter and ensures that deployments can proceed even over connections with high latency or limited bandwidth, making it ideal for managing distributed edge clusters.

Establish Monitoring and Observability

Effective Kubernetes monitoring is essential for maintaining the health and performance of your edge deployments, but collecting metrics and logs from geographically distributed nodes is a significant challenge. Centralizing this data is key to gaining a complete picture of your environment. Plural provides a single pane of glass for your entire Kubernetes fleet, including edge clusters. The platform’s embedded Kubernetes dashboard uses a secure auth proxy to give you direct, SSO-integrated access to troubleshoot workloads on any cluster without complex networking or VPNs. This unified view simplifies observability, allowing you to monitor performance, diagnose issues, and manage your distributed infrastructure from one place.

Configure for High Availability

Edge deployments must be resilient to network failures. A key principle is to prioritize node autonomy, ensuring that edge locations can function independently even if they lose connection to the central control plane. This involves caching container images and configurations locally so that applications can continue running and restart if needed. For critical sites, deploying multi-node clusters provides local redundancy. Plural’s architecture inherently supports this model. The Plural agent installed on each edge cluster operates autonomously, polling the control plane for updates. If connectivity is lost, the agent and its workloads continue to run with the last known configuration, ensuring service continuity until the connection is restored.

Best Practices for Managing Edge Applications

Managing applications at the edge introduces operational challenges that differ from traditional data center or cloud environments. The distributed and often resource-constrained nature of edge deployments requires a deliberate approach to application deployment, resource management, and data processing. Adopting best practices ensures that your edge applications are not only functional but also reliable, efficient, and scalable. This involves designing for unreliable networks, optimizing for limited hardware, and implementing a consistent lifecycle management strategy across a potentially vast fleet of devices.

A successful edge strategy hinges on how effectively you can manage the entire application lifecycle, from initial deployment to ongoing maintenance and updates. By focusing on reliability, resource optimization, and intelligent data handling, you can build a robust edge infrastructure that delivers on its promises of low latency and high availability. Plural provides the tools to implement these practices at scale, offering a unified platform to automate and streamline operations across your entire edge fleet.

Deploy Applications Reliably

In edge environments, network connectivity can be intermittent. To ensure consistent operation, Kubernetes edge deployments should prioritize node autonomy, allowing edge nodes to function independently even when disconnected from the central control plane. By implementing local control loops, nodes can handle disruptions without relying on continuous communication with a central controller. This resilience is critical for applications that require high availability, such as in retail point-of-sale systems or industrial IoT sensors.

A GitOps-based approach is ideal for achieving this reliability. With a pull-based model like the one used by Plural CD, an agent on each edge node periodically pulls its configuration from a central repository. If a node is offline, it simply syncs the latest configuration once it reconnects, ensuring eventual consistency across the fleet without requiring a persistent connection.

Optimize Application Resources

Edge devices are often resource-constrained, with limited CPU, memory, and storage. Kubernetes facilitates the orchestration of microservices in these environments, and lightweight distributions like K3s are specifically designed for these scenarios. When building your applications, focus on creating lightweight container images by using minimal base images like Alpine Linux and implementing multi-stage builds to discard unnecessary build artifacts.

Beyond the application itself, you must carefully manage resource allocation within Kubernetes. Define precise resource requests and limits in your deployment manifests to prevent applications from consuming more resources than necessary, which could destabilize the node. This practice ensures that critical system processes have the resources they need to run, maintaining the stability of the entire edge device.

Select the Right Data Processing Patterns

One of the primary drivers for edge computing is the need to reduce latency by processing data closer to its source. Deploying multiple Kubernetes clusters across various edge locations is an effective pattern for achieving this, as it not only localizes data processing but also enhances resilience. If one edge location experiences an outage, it doesn't impact the others. This distributed model is particularly effective for applications that serve geographically dispersed users, such as content delivery networks or real-time analytics platforms.

Managing a large fleet of distributed clusters, however, introduces significant operational complexity. A centralized management platform is essential for maintaining visibility and control. Plural provides a single-pane-of-glass console that simplifies the management of multiple Kubernetes clusters, regardless of their location, allowing platform teams to enforce consistent configurations and monitor health from one unified interface.

Manage the Full Application Lifecycle

Effectively managing the full application lifecycle, from development to production and decommissioning, is critical for maintaining a healthy edge deployment. This requires a standardized and automated CI/CD workflow that ensures reliability and scalability. By codifying your infrastructure and application configurations using Infrastructure as Code (IaC), you can create a repeatable and auditable process for deploying and updating your edge applications. This approach minimizes manual errors and ensures consistency across all your edge nodes.

Plural's Stacks feature extends GitOps principles to infrastructure management, allowing you to automate the entire lifecycle. You can declaratively define your application's infrastructure dependencies—such as databases or message queues—in a Git repository. Plural then automates the provisioning and management of these resources alongside your application deployments, creating a cohesive system for managing your entire edge stack.

Advanced Edge Operations

Once your initial edge deployment is running, the focus shifts to long-term management, scaling, and resilience. Advanced edge operations involve moving from managing a single cluster to orchestrating a distributed fleet, often under challenging network conditions and with strict resource limitations. This requires a robust strategy for managing configurations, troubleshooting remote issues, and automating as much of the operational lifecycle as possible. The goal is to maintain a secure, consistent, and reliable edge infrastructure as it grows in size and complexity, without overwhelming your engineering teams.

Manage Fleets of Edge Clusters

Managing a handful of edge clusters is one thing; managing hundreds or thousands is another challenge entirely. Each edge location can have unique constraints, but you still need to enforce consistent security policies, deploy applications uniformly, and apply updates reliably across the entire fleet. Kubernetes provides a powerful foundation to orchestrate microservices in these decentralized environments, but doing so at scale requires a centralized management approach. A single pane of glass becomes essential for visibility and control, allowing you to see the health and status of all your edge deployments from one place.

Plural is built for this exact scenario. Using a GitOps-based workflow, you can define your application and infrastructure configurations in a central repository. The Plural CD agent on each edge cluster then pulls and applies these configurations, ensuring consistency across your fleet.

Scale Your Edge Environment

As your needs grow, you'll need to scale your edge environment by adding more clusters in new locations. Strategically deploying clusters closer to your users helps reduce latency and enhance resilience by localizing data processing and providing redundancy. However, scaling introduces complexity. How do you ensure each new cluster is provisioned with the correct configuration, security policies, and networking rules? Manually setting up each one is slow, error-prone, and doesn't scale.

This is where Infrastructure as Code (IaC) becomes critical. With Plural Stacks, you can define your edge cluster infrastructure using Terraform and automate the provisioning process. By creating standardized templates, your teams can self-service new edge deployments through a simple, governed workflow, allowing you to scale your edge footprint efficiently and securely.

Troubleshoot Common Issues

Troubleshooting at the edge is notoriously difficult. Unlike in a data center, you can't just walk over to the machine. Edge nodes often operate with limited or intermittent network connectivity, making it hard to access logs, run diagnostic commands, or even know the current state of a device. When a pod fails on a resource-constrained device or a network issue isolates a cluster, you need remote access tools that are resilient to these conditions.

Plural’s agent-based architecture provides a secure, reliable channel for remote troubleshooting. The embedded Kubernetes dashboard gives you a real-time view into your edge clusters without requiring a VPN or direct inbound network access. All communication happens over a secure, egress-only connection, allowing you to inspect resources and check logs even on clusters behind strict firewalls.

Automate Operations with Plural

Manual intervention at the edge is a recipe for failure. The only way to manage a distributed fleet effectively is through automation. GitOps provides the perfect model, where your Git repository serves as the single source of truth for your entire edge deployment. Every configuration change, application update, or policy adjustment is made through a pull request, creating an auditable and repeatable process.

Plural fully embraces this model to automate edge operations. As our practical guide to running Kubernetes at the edge explains, even with a spotty connection, the agent will wait until it can connect, then pull and apply any pending changes. This automates everything from application deployments to system updates, ensuring your edge fleet remains consistent and up-to-date with minimal human effort.

Securing Your Edge Deployment

Securing edge deployments presents a unique set of challenges. Devices often operate in physically insecure locations with intermittent network connectivity, expanding the attack surface and complicating security management. A comprehensive security strategy is not optional; it's a fundamental requirement for protecting your infrastructure, applications, and data from the control plane to the farthest node. This involves a multi-layered approach that includes strict access controls, robust network policies, secure certificate management, and a clear data protection plan.

With Plural, you can centralize and automate many of these security workflows. The platform's agent-based architecture ensures that even disconnected or air-gapped edge clusters can be managed securely without exposing them to inbound network traffic. By leveraging GitOps principles, you can enforce consistent security configurations across your entire fleet, ensuring that every edge location adheres to your organization's security and compliance standards. This allows you to manage a distributed and complex environment from a single pane of glass, simplifying operations while strengthening your security posture.

Implement Robust Access Control

At the edge, controlling who can access and modify your Kubernetes resources is critical. Role-Based Access Control (RBAC) is a core Kubernetes security feature that allows you to define granular permissions for users and services. By implementing a least-privilege model, you ensure that each component only has the access it needs to perform its function, minimizing the potential blast radius of a compromise.

Plural simplifies this process by integrating with your existing identity provider (OIDC) and using Kubernetes Impersonation. This means all RBAC policies resolve to your console user's email and groups, creating an effective SSO experience. You can define ClusterRoleBindings that grant permissions to specific users or groups and use Plural's GitOps engine to sync these policies across your entire edge fleet. This ensures consistent, auditable, and centralized management of access controls without needing to manually configure each cluster.

Enforce Network Security Policies

Edge environments often rely on public or untrusted networks, making network security a top concern. Kubernetes NetworkPolicies are essential for controlling traffic flow between pods, namespaces, and external endpoints. By default, all pods in a cluster can communicate with each other, so you must explicitly define rules that restrict traffic to only what is necessary. This helps isolate workloads and prevents lateral movement by an attacker who gains a foothold in one part of your system.

Plural's architecture enhances network security by design. The Plural agent, installed on each edge cluster, initiates all communication with the management plane via egress-only networking. This means your edge clusters don't need to be exposed to the internet, drastically reducing their attack surface. You can define and deploy NetworkPolicies using Plural CD, ensuring that consistent, strict security rules are enforced across every device in your fleet, no matter where it's located.

Manage Certificates Securely

Secure communication between components is non-negotiable. TLS certificates are used to encrypt traffic and verify identity for everything from the Kubernetes API server to inter-service communication. Managing the lifecycle of these certificates—issuance, renewal, and revocation—across a distributed fleet of edge devices can be a significant operational burden. Failure to do so can lead to service disruptions or security vulnerabilities when certificates expire or are compromised.

Automating certificate management is the only scalable solution. Tools like cert-manager can be deployed to your clusters to handle this automatically. Using Plural, you can package cert-manager as part of your standard edge deployment stack. This allows you to leverage GitOps to configure and maintain consistent certificate management practices across all edge locations, ensuring that all communication is encrypted and all identities are verified without manual intervention.

Develop a Data Protection Strategy

Data at the edge is vulnerable both at rest and in transit. With limited and unreliable network connectivity, you can't assume a continuous link to a central control plane for monitoring or data backups. Therefore, your strategy must include strong protections for data stored locally on edge devices and for data being transmitted back to a central location. This includes encrypting sensitive data on disk and ensuring all network traffic is encrypted with TLS.

A robust data protection strategy also includes plans for backup and recovery. For stateful applications running at the edge, you need a reliable way to back up their data and restore it in case of device failure. You can use Plural Stacks to declaratively define and deploy backup tooling, like Velero, across your edge fleet. This ensures that you have a consistent, automated process for protecting critical data, even in challenging and disconnected environments.

Related Articles

• Kubernetes Management: The Complete Guide
• Plural | Edge Kubernetes

Frequently Asked Questions

How is managing Kubernetes at the edge different from a typical cloud deployment? The primary differences are driven by three core constraints: unreliable networks, limited hardware resources, and physical security. Unlike a data center, edge devices often have intermittent connectivity, which means your entire operational model must be built for autonomy. You can't assume a stable connection to the control plane. Furthermore, edge hardware is typically resource-constrained, requiring lightweight Kubernetes distributions and carefully optimized applications. Finally, since these devices can be in physically accessible locations, you must adopt a more rigorous security posture that accounts for potential tampering.

How can I reliably deploy application updates to edge nodes with unstable network connections? The most effective approach is to use a pull-based GitOps model. Instead of the central control plane pushing updates to the edge, a lightweight agent on each node periodically polls a central Git repository for its desired state. If the node is offline, it simply tries again later. Once connectivity is restored, it pulls the latest configuration and applies it. This makes your deployment process resilient to network disruptions. Plural CD is built on this exact agent-based, pull-style architecture to ensure consistency across your fleet, regardless of network quality.

Do I need a special version of Kubernetes for resource-constrained edge devices? While standard Kubernetes is highly capable, it can be too resource-intensive for typical edge hardware. For this reason, many teams opt for lightweight, fully conformant distributions like K3s. These distributions are specifically packaged to have a smaller binary size and lower memory footprint, making them ideal for devices with limited CPU and RAM. Choosing the right distribution is a critical first step, but it must be paired with disciplined application resource management, including setting firm requests and limits for every workload.

What's the best way to secure an edge cluster that I can't place behind a corporate firewall? Security at the edge requires a multi-layered strategy. You should always start by using Kubernetes NetworkPolicies to strictly control traffic between your pods and isolate workloads. However, the most significant improvement comes from changing the communication model. Plural’s agent-based architecture uses an egress-only connection, meaning the edge device initiates all communication with the management plane. This eliminates the need for any inbound ports to be open on the edge device's firewall, drastically reducing its attack surface and removing a common vector for attack.

How can I troubleshoot workloads on a remote edge device without direct network access? Directly accessing edge clusters with kubectl is often impractical due to network restrictions and security policies. A centralized dashboard that can securely proxy API requests is the most effective solution. Plural provides an embedded Kubernetes dashboard that uses a secure channel initiated by the agent on the edge device. This allows you to inspect resources, view logs, and troubleshoot workloads on any cluster in your fleet directly from the Plural UI, all without requiring a VPN or complex network configurations.