[Day #85 PyATS Series] End-to-End Service Validation Across Data Center Fabrics Using pyATS for Cisco [Python for Network Engineer]
Table of Contents
Introduction on the Key Points
In modern data center environments, ensuring that services traverse the network fabric correctly from source to destination is a critical operation. Complex configurations such as VLANs, VRFs, routing policies, and ACLs must work together harmoniously. However, validating service functionality manually is both time-consuming and prone to human error.
This Article demonstrates a production-ready approach using pyATS to automate end-to-end service validation across data center fabrics, focusing on realistic step-by-step procedures, CLI and GUI validations, and automated reporting. This is a critical skill as part of your professional development as a Python for Network Engineer, enabling robust network automation practices in enterprise environments.
Key takeaways from this guide:
- Automate service path verification.
- Validate device-to-device connectivity across VLANs/VRFs.
- Integrate GUI dashboard snapshots for visual proof.
- Generate structured validation reports for audit and compliance.
Topology Overview:

Objective:
- Validate that Service A from Server A to Server B is properly forwarded across the fabric.
- Validate that inter-VRF isolation policies are enforced.
- Ensure routing convergence and correct ACL application.
Topology & Communications
Communication Flow:
- pyATS connects to Spine and Leaf switches via SSH.
- Runs device-specific commands to capture:
- Interface status
- Routing table entries
- VLAN/VRF configurations
- Performs service ping tests between Server A and Server B.
- Extracts and stores GUI dashboard snapshots for traffic path visual confirmation.
- Logs results into structured JSON or HTML reports for detailed insight.
Workflow Script
from genie.testbed import load from pyats.aetest import Testcase, test, main import json class DataCenterServiceValidation(Testcase): @test def connect_and_capture_fabric_state(self, testbed): self.fabric_data = {} for device_name, device in testbed.devices.items(): device.connect(log_stdout=False) print(f"[INFO] Connected to {device_name}") interfaces = device.execute('show interfaces status') routing_table = device.execute('show ip route') vlan_info = device.execute('show vlan brief') self.fabric_data[device_name] = { "interfaces": interfaces, "routes": routing_table, "vlans": vlan_info } print(f"[INFO] Captured fabric state from {device_name}") @test def validate_service_connectivity(self): # Simple ping test from Server A to Server B via CLI ping_output = testbed.devices['server_a'].execute('ping 10.1.2.10') success = 'Success rate is 100 percent' in ping_output assert success, "Ping test from Server A to Server B failed" print("[PASS] Service connectivity validated (Server A -> Server B)") @test def verify_routing_convergence(self): expected_route = '10.1.2.0/24' for device_name, data in self.fabric_data.items(): assert expected_route in data['routes'], f"{device_name} missing route to {expected_route}" print("[PASS] Routing convergence validated across fabric") @test def check_vlan_consistency(self): expected_vlan = '10' for device_name, data in self.fabric_data.items(): assert expected_vlan in data['vlans'], f"VLAN {expected_vlan} missing on {device_name}" print("[PASS] VLAN consistency validated across fabric") @test def save_compliance_report(self): report_file = '/tmp/fabric_service_validation_report.json' with open(report_file, 'w') as f: json.dump(self.fabric_data, f, indent=4) print(f"[INFO] Compliance report saved to {report_file}") @test def capture_dashboard_snapshot(self): # Placeholder for GUI snapshot snapshot_path = '/tmp/fabric_dashboard_snapshot.png' print(f"[INFO] Dashboard snapshot saved to {snapshot_path}") if __name__ == '__main__': main()
Explanation by Line
- connect_and_capture_fabric_state():
- Connects to all devices.
- Captures interface status, routing table, and VLAN configuration via CLI.
- Stores structured output for validation.
- validate_service_connectivity():
- Performs a ping test from Server A to Server B.
- Asserts successful 100% ping delivery.
- verify_routing_convergence():
- Checks if route to Server B is present on all fabric devices.
- check_vlan_consistency():
- Confirms expected VLAN exists on each device.
- save_compliance_report():
- Saves collected state into a structured JSON file for audit purposes.
- capture_dashboard_snapshot():
- Placeholder for automated GUI snapshot of monitoring dashboard.
testbed.yml Example
testbed: name: dc_fabric_validation credentials: default: username: admin password: Cisco123 devices: spine1: os: iosxe type: router connections: cli: protocol: ssh ip: 10.1.10.1 spine2: os: iosxe type: router connections: cli: protocol: ssh ip: 10.1.10.2 leaf1: os: iosxe type: switch connections: cli: protocol: ssh ip: 10.1.20.1 server_a: os: linux type: server connections: cli: protocol: ssh ip: 10.1.1.10 server_b: os: linux type: server connections: cli: protocol: ssh ip: 10.1.2.10
Post-validation CLI (Real Expected Output)
Interface Status Example
show interfaces status Port Name Status VLAN Gi1/0/1 Uplink connected 10 Gi1/0/2 ServerA connected 20
Routing Table Example
show ip route O 10.1.2.0/24 [110/2] via 10.1.10.2, 00:15:23, Ethernet1
VLAN Brief Example
show vlan brief VLAN Name Status 10 Production active 20 Management active
FAQs
Q1. What is end-to-end service validation in a data center fabric?
A1. End-to-end service validation ensures that critical network services, such as VLAN connectivity, routing, multicast, and security policies, are correctly deployed and functioning across all fabric segments—from leaf to spine and across multiple pods if applicable.
Q2. Why use pyATS for data center fabric validation?
A2. pyATS provides a vendor-agnostic automation framework capable of testing multiple devices simultaneously. It supports structured test scripts, detailed reporting, and integration with testbeds, making it ideal for validating large-scale fabric deployments reliably.
Q3. How do you define the validation scope for end-to-end services?
A3. The validation scope typically includes key services such as:
- Interface status and link redundancy
- VLAN and VXLAN connectivity
- Routing protocols (OSPF, BGP, etc.)
- Multicast distribution
- ACLs and firewall policies
Test scripts can be parameterized for each service across the fabric.
Q4. Can pyATS handle multi-vendor data center fabrics?
A4. Yes. pyATS supports multiple vendors like Cisco, Arista, and Juniper. By using vendor-specific connectors in a single testbed, you can validate services consistently across heterogeneous environments.
Q5. How are test results captured and analyzed?
A5. pyATS captures CLI outputs and generates structured reports in formats like JSON, HTML, or CSV. Non-compliant or failing services are highlighted with detailed device and interface-level information, making troubleshooting easier.
Q6. Can validation be automated after configuration changes?
A6. Absolutely. pyATS jobs can be integrated into CI/CD pipelines or triggered post-Ansible playbooks, ensuring that any configuration changes are automatically verified before production rollout.
Q7. How do you validate fabric redundancy and failover scenarios?
A7. Test scripts can simulate failures by administratively shutting down interfaces or devices and verifying that traffic continues through alternate paths, ensuring end-to-end service continuity and failover resilience.
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You’ve now built a robust, end-to-end service validation framework using pyATS that automates key checks across your data center fabric. This is a critical capability in the automation toolkit of every network engineer focused on reliability, scalability, and automation excellence.
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