Arcfra is excited to announce the release of Arcfra Kubernetes Engine (AKE) version 1.4, a production-ready container management platform designed to make Kubernetes simpler, more secure, and more efficient. This latest upgrade brings powerful enhancements in observability, operations & maintenance (O&M), and multi-tenant resource management — making it easier than ever for enterprises to operate Kubernetes at scale.

Why This Release Matters

As Kubernetes adoption grows across enterprises, so do its operational challenges. Teams often struggle with:

• Complex permission management and poor resource isolation
• Disorganized resource files and fragmented deployment workflows
• Dispersed security configurations that are hard to manage centrally
• Weak observability that hinders issue diagnosis and prolongs troubleshooting
• Time-consuming toggling between command-line tools and graphical UIs

AKE 1.4 directly addresses these issues by prioritizing enhanced user experience and streamlined operations, helping teams cut O&M costs and deploy faster with confidence.

What’s New in AKE 1.4

Experience Elevated

1. Smarter Team Collaboration with Multi-Tenancy

Integrated with Arcfra Operation Center, AKE 1.4 introduces project-level permission control, allowing teams to securely share a single cluster while maintaining clear boundaries. Role-based access ensures only the right users have access to the right resources.

2. Unified Security Policies Across VMs and Containers

With a flat network plugin AIC and Arcfra Network Service distributed firewall, enterprises can now define and enforce consistent, unified security policies across both virtual machines and containers — dramatically improving security and access control.

Read more about unified security across VMs and containers.

3. Visualized Application Deployment

AKE 1.4 streamlines the deployment experience with support for selecting local YAML directories via file chooser. Kubernetes resource objects are auto-recognized, enabling one-click creation and real-time status monitoring — perfect for deploying from core components to business applications.

Click to watch the demo video, see how configuration management and troubleshooting can be simplified via the console and O&M operations — significantly boosting operational efficiency.

Operations Made Easier

4. Improved Observability and High Availability

AKE now offers deep visibility into cluster status, system performance bottlenecks, and workload health. Real-time dashboards track usability, availability, resource usage, latency, and system. Alerts via email, SNMP traps, or webhooks ensure rapid incident response. Monitoring has expanded to etcd, Harbor, and Contour, helping users pinpoint root causes faster.

Network traffic visualization (visual network topology view) offers unified monitoring for VM and container traffic, enhancing security analysis and allowing admins to preview policy impacts before enforcing changes.

Click to watch the demo video, learn about the observability enhancements.

5. Direct Console Access for Faster Troubleshooting

AKE brings console-level access for clusters, nodes, and pods — right within the UI. Admins can:

• Use the cluster console to run kubectl commands for managing Kubernetes resources, such as viewing custom CRDs or handling system components stuck in a Terminating state
• Configure core system components like kubelet and static Pods, and view kernel logs and component statuses via the node console
• Access the pod console for application-level debugging, including checking environment variables, JVM configurations, and performing network connectivity tests

Enhanced with syntax highlighting, autocomplete, and pagination, this makes daily operations much faster and less error-prone.

Built for AI Workloads

6. Flexible Infrastructure for AI Training & Inference

AKE supports Kubernetes cluster deployment on:

• Bare metal: ideal for high-performance AI training
• VMs: suited for scalable, multi-tenant AI inference

Advanced scheduling, tenant isolation, and visual tools make AKE an optimal foundation for enterprise-grade AI pipelines.

Proven in Production

Arcfra Kubernetes Engine is already powering mission-critical systems across industries:

• ConnectWave, a leader in South Korea’s e-commerce market, uses AKE to run its PLAi AI platform, gaining the performance and flexibility required for efficient model training and deployment.
• Foxconn, the world’s largest electronics manufacturing services provider, implemented AKE to unify management of container workloads across DevTest and Shop Floor Control systems, increasing operational efficiency and service quality.

Read more about ConnectWave case study.

Learn More

• Download Arcfra Kubernetes Engine Product Brief
• Explore Arcfra Kubernetes Engine in Docs