The following components form the foundation of the Netpicker Automation Platform’s container-based architecture:

• Container Orchestration: Manages the deployment, scaling, and lifecycle of containers. It enables the platform to run modular automation services across diverse environments, ensuring efficient use of resources and high flexibility.
• Microservices Structure: Breaks platform functions—such as device configuration, inventory management, and policy enforcement—into discrete, stateless services. This modularity allows for independent updates, better fault isolation, and seamless scaling.
• Persistent Data Storage: Utilizes persistent volumes for storing important information such as logs, automation results, or credentials. Kubernetes secrets and configuration maps are employed to handle sensitive data securely.
• Networking & Service Mesh: Implements strict network segmentation and optionally integrates a service mesh to provide enhanced service discovery, encrypted inter-service communication, and observability for troubleshooting and monitoring.

Netpicker Automation Platform supports several deployment models, giving organizations the flexibility to match their infrastructure needs. Below are the main approaches:

• On-Premise: Ideal for organizations running local infrastructure. Netpicker operates within a managed Kubernetes cluster, typically using storage such as NFS or iSCSI, and network plugins like Calico or Flannel. High availability is achieved with multi-node clusters.
• Public Cloud: Designed for cloud environments with managed Kubernetes solutions such as AWS EKS, Google GKE, or Azure AKS. These environments leverage built-in cloud block storage, automated networking, and support multi–availability zone redundancy.
• Hybrid: Combines on-premises and cloud resources. Netpicker runs across federated Kubernetes clusters connected via secure overlay networking like VPN or IPSec, supporting workload distribution and centralized management.

Each deployment approach ensures consistent automation workflow, robust orchestration, and a scalable architecture that aligns with a variety of operational requirements and compliance considerations.

The Netpicker Automation Platform delivers robust protection across each stage of deployment and operation. The security approach encompasses image integrity, network isolation, secrets management, and comprehensive auditing. Explore the focus areas below:

• Hardened Container Images: All images are composed with minimal base operating systems and continuously scanned for vulnerabilities. Automated policies enforce use of trusted sources and up-to-date distributions.
• Role-Based Access Control (RBAC): Detailed RBAC policies ensure users and services operate with the least amount of privilege necessary. Namespace isolation further limits scope of access within Kubernetes clusters.
• Restrictive Network Policies: Network segmentation is mandated by default-deny policies. Only explicitly permitted services, protocols, or ports can communicate, reducing lateral movement risk within the cluster.
• Secrets Management: Sensitive data such as API tokens or credentials is managed outside container images. Secrets are provisioned at runtime and stored in encrypted storage with strict access controls.
• Vulnerability Scanning & Compliance: Regular scanning for system and application vulnerabilities, along with compliance validation, helps proactively identify and remediate security gaps before they impact the environment.
• Audit Logging: Continuous audit trails record every relevant API call and configuration change for investigation, compliance, and ongoing improvement.

By embedding these practices, Netpicker Automation Platform ensures automation remains secure, traceable, and resilient, adapting to stringent regulatory and operational standards.

The automation lifecycle within the Netpicker Automation Platform is a streamlined process that manages network devices and services from initial discovery through continuous monitoring. The steps below explain how automation is achieved end-to-end:

1. Container Deployment: Automated pipelines build, test, and roll out containerized automation services, ensuring updates and new features can be deployed rapidly and with minimal risk.
2. Discovery & Provisioning: Upon initialization, dedicated containers automatically discover network devices and populate inventory data, maintaining an up-to-date view of the environment.
3. Orchestration & Execution: Job schedulers coordinate task-specific containers to execute scripts, playbooks, or workflows targeting configuration, compliance, or bulk changes. Each task runs in isolation to avoid impact on other processes.
4. Testing & Validation: Before deployment, compliance and stability checks validate configuration changes against policy and design rules to maintain a robust network state.
5. Deployment of Intended Changes: Validated configurations are rolled out automatically, with options for staged or instant deployment, minimizing service interruptions.
6. Monitoring & Scaling: Live monitoring agents track task and resource health, enabling automated scaling or self-healing for service containers as demand shifts.
7. Audit & Reporting: Every automation event, configuration change, and policy validation is logged, offering comprehensive visibility for troubleshooting and compliance review.

These lifecycle phases allow teams to reliably automate device management and network operations while ensuring compliance, traceability, and resilience.

To ensure seamless customization, integration, and long-term maintainability, follow these best practices when extending the Netpicker Automation Platform:

• Use Official or Certified Base Images: Start all custom containers with official or trusted base images to maintain security and compatibility throughout the platform.
• Maintain Clear API Contracts: Ensure any integrations or extensions publish well-documented API specifications. This promotes interoperability and avoids future conflicts.
• Apply Namespace Separation: Organize development, staging, and production workloads in separate namespaces within your Kubernetes environment to minimize risk and ease management.
• Automate Testing and Validation: Integrate automated testing pipelines to validate custom modules or extensions before deployment, helping to catch issues early and maintain platform reliability.
• Document Custom Workflows: Maintain up-to-date documentation for any new automation scripts, playbooks, or integrations so that future users and teams can easily understand and support changes.
• Monitor Resource Consumption: Use built-in monitoring tools to track the performance and health of all extensions, ensuring they do not negatively affect the core platform.
• Follow Security Best Practices: Secure container images, manage secrets appropriately, and review RBAC and network policies when deploying new modules or integrating external services.

By following these practices, you can tailor Netpicker Automation Platform to fit evolving requirements while ensuring stability, compliance, and ease of future enhancements.

This conceptual diagram illustrates the primary components and their interactions within the Netpicker Automation Platform’s container-based architecture. Use it as a visual reference to understand how the platform orchestrates automation workflows, manages data, and delivers services:

+-------------------------+
|   Netpicker UI/API      |
+-----------+-------------+
            |
+-----------v-------------+
|   API Gateway / Ingress |
+-----+-------------------+
      |          |        |
+-----v--+  +----v---+  +---v-----+
|  Core  |  | Device |  | Task    |
| Mgmt   |  | Inv.   |  | Runner  |
+--------+  +--------+  +---------+
      |   (Inter-Service API/Queue)
      +---------------------------+
             |
      +------v-------+
      |  Data Store  |
      +--------------+

(Each block above represents services deployed as separate containers within a Kubernetes cluster)

This architecture leverages modular microservices, API-centric integration, and container orchestration to ensure scalability, performance, and maintainability.