With networks continuing to rapidly evolve at a pace greater than many IT departments can monitor manually, automated network operations via Python as a programming language have become a viable option for enterprise organizations to validate configurations, monitor performance and strengthen security on a larger scale.
According to the 2024 Stack Overflow Developer Survey, Python continues to be among the top three languages used within the field of Network Engineering in conjunction with automation workloads. As it has an easy to read syntax, is supported by many mature libraries, and has a large community of developers, it allows both seasoned developers and Networking professionals to easily leverage its capabilities for automating their work within this field.
This article will discuss how IT departments have been using Python-based Network Automation to improve reliability, minimize operational risks, and strengthen security across modern networks. Specifically, we will examine Use Cases of Validations, Monitoring, and Security, as these Use Cases will drive the largest amount of measurable value for large Enterprise Organizations.
How Python-based Network Automation Can Support The Validation Process
The Validation of a Network Configuration is the process by which an IT organization ensures that the operational configuration of the devices on their network matches the authorized configuration of those devices based on organizational Policies and/or Compliance Frameworks in network automation. When validated manually, validation takes an excessive amount of time, and moreover, requires multiple parties to verify the configurations against each other (such as documentation, spreadsheets, and the actual outputs from devices), which is inherently susceptible to Human Error.
With Python Automation, an organization can verify that the Virtual State of a Network Device matches the Expected State of that Device through the use of Python Automation tools to compare the Actual Configuration State of the Network Device against the policies that govern the device.
1. Network Configuration Drift Detection
By leveraging Python Automation Libraries such as Netmiko, Scrapli or Paramiko, Network Engineers have the ability to access network devices, download their running configuration, and validate it against the organization’s template (i.e., approved operational configuration). Based upon running these validations frequently (i.e., daily or hourly), Network Engineers will receive timely alerts when a Network Device has drifted away from the approved operational configuration in network automation as per Netpicker.
This proactive approach to Network Configuration Validations aids in reducing the likelihood of an organization suffering outages due to Routing Table inconsistencies, ACLs set incorrectly, or the utilization of outdated Firmware in network automation as per Netpicker.
2. Policy and Compliance Validation
Using Python Automation Libraries, Network Engineers can validate multiple aspects of the Configuration of Network Devices including:
- Password Strength Policies
- SSH Configuration Rules
- SNMP Configuration Settings
- Logging Destination Configuration
- Firewall Rule Structure
- Routing Protocol Standards
Network Engineers can also integrate Python Automation into organizing for Compliance Against Frameworks such as PCI DSS, HIPAA, or ISO 27001. Therefore, rather than having to perform a single audit of an organization’s Network Configuration one time per year, a Network Engineer could utilize Python Automation to perform regular (i.e., continuous) Audits against multiple Compliance Frameworks, thus eliminating the potential for ‘Gaps’ in the Compliance audit process in network automation as per Netpicker.
3. Template Based Deployment Validation
Infrastructure teams employ Python for validating that its configuration settings are in accordance with template files, such as Golden Configuration Files. By performing this function prior to the device’s commissioning, this automation prevents misconfigurations associated with unqualified devices.
Real Time Monitoring with Python
Python also affords Real-Time Monitoring of Infrastructure Devices and as previously stated, Python extends traditional monitoring methods to allow Infrastructure Teams more customized and immediate visibility of network behaviors by virtue of its ability to fetch data directly from Metric APIs, Telemetry and Command-Line Interfaces.
The following subsections detail the types of metrics Python can record real-time via events triggered by the context of a device’s operation:
1) Performance Data
Python scripts can capture the following performance metrics of a device:
- Interface Bandwidth Utilization
- CPU & Memory Utilization
- Packet Loss & Latency
- Quality of Service (QoS) Counters
- Wireless Signal Quality
- BGP Neighbor Status
- Power Supply & Environmental Variables
All of these performance metrics allow Network Engineers to anticipate potential issues before becoming a reality. The ability to schedule Metric Collection events at predefined intervals optimized for Infrastructure needs creates a simplified, yet powerful, approach to constructing Telemetry Pilots.
2) Event-Based Alerting
Python scripts can integrate with many other monitoring tools by Utilizing Event-Driven API integrations provided by Various Messaging Applications (e.g., Slack, MS Teams) and Email Clients.
Upon a Metric Crossing Threshold, the Python script will immediately alert the team responsible for monitoring an Infrastructure, as evidenced by an alert for a Firewall CPU spike or a WAN drop, resulting in a response from the team members within seconds.
3) Network Telemetry Integration
Modern Infrastructure Devices provide Network Telemetry via gNMI and REST APIs, and with Python Libraries such as gNMI Client and Requests providing direct access to this information, Python can facilitate the timely construction of near-real-time dashboards by viewing Network Telemetry data as Events Triggered.
Investing in automation, in general, through the use of Python, is also motivated by an increased focus on securing infrastructure. The risk associated with being connected to the Internet presents a relentless threat of attack on all networks, thus necessitating automated Vulnerability Detection and Remediation as per Netpicker.
1) Automated Vulnerability Scanning
By utilising Python scripts, an Infrastructure can automatically scan for:
- outdated firmware;
- unsupported protocol;
- weak encryption;
- misconfigured access lists;
- open management ports; and
- unapproved services.
Python scripts can capture the Device Banner, match the Software Versions matches against the Vulnerability Feed, and checks against the Cybersecurity Best Practices; therefore, reducing the time to identify Gaps that may be exploited by attackers.
2) Automatic Risk Inventory
Python can generate real-time inventories of devices on an Infrastructure through automation by discovering:
- IP Addresses;
- Operating System Versions;
- Hardware Details;
- Installed Modules;
- Enabled Services;
- Neighbor Routing Devices;
- API Endpoints.
Knowing what devices are present in a Network is vital; without visibility, devices cannot be secured. Automated Discovery provides that visibility.
3) Firewall & ACL Verification
Firewall Rule Verification can be accomplished with the assistance of Python by testing through Test Queries or analysis of ACL Statements to identify Redundant Rules, Shadowed Rules, and/or Overly Permissive Entries, creating unnecessary Risk.
Security Teams can also utilise Python to simulate Network Paths and verify that Traffic follows the Intended Policy.
4. Automated Response and Remediation
The application of Python-driven workflows by several companies allows them to both identify and remedy security issues within minutes of detection. For example:
By combining the above automated response mechanisms, organizations are able to response to security incidents and minimize the effects of damage and losses during that timeframe.
Key Python Libraries That Enable Network Automation
Several libraries are currently available to the Python community to allow for the automation of specific and commonly performed network operations, including:
Netmiko, NAPALM, Scrapli, Paramiko, Requests, Pandas, gNMI Client, pyATS.
These libraries provide network engineers and security professional the tools to automate common tasks with reduced code and time consumption on the automation deployment process.
Why Python Based Network Automation Is Now Essential
The use of Python to automate network operations is becoming a necessity for many network operations teams due to the high level of complexity in today’s networks, as a result of continuous network changes and the threat of continued intrusion and the inability to meet the compliance issues.
In addition to improving the reaction time to incidents, Python is also used to reduce the number of errors made by humans when troubleshooting, and enhance security, improve visibility, and accelerate the process of identifying and mitigating issues prior to deploying a network operation to ensure the maintain compliance across a multivendor environment.
All of these characteristics make Python the tool of choice for network engineering and security professionals. Any enterprise that invests in the early adoption of Python will gain a significant competitive advantage over its competitors. Enterprises will reduce their downtime, achieve operational efficiencies, and build redundant and resilient networks, without fully relying on proprietary solutions. For more on details about network automation, contact us at Netpicker!