With the investment into today’s modern and agile networks, many IT organizations are searching for intelligent tools that can help simplify the complexity that comes with the advanced capabilities of today’s networks and keep up with the business demands. Topping off the complex challenges, many organizations are facing challenges on how to bridge the growing IT skill gap and automate various aspects of their network management.
In a recent Gartner article regarding the State of Network Automation, according to the article:
◉ 41% of network activities are less than 10% automated.
◉ 31% of network activities are 11% to 25% automated.
Essentially 72% of network activities are less than 25% automated. Separately, Gartner has also identified 4 IT personas (AIOps, NetOps, SecOps, and DevOps), stating that NetOps2.0 is the evolution of network operations towards automation.
Attributes of NetOps 2.0 include an Automation-first approach, embedded analytics, SecOps integrations, and Turn-key DevOps tools. IT organizations that embrace this approach can achieve increased IT agility, Proactive network operations, and an increased level of collaboration between common silos in IT organizations. An additional outcome is minimized friction between the NetOps, SecOps, and DevOps personas.
When it comes to automation products, the Inventor’s paradox states, “It is easier to solve a more general problem that covers the specifics of the sought-after solution”. Organizations who transitioning to AIOps, NetOps2.0, and automation platforms, are faced with common challenges and limitations such as:
◉ Automation products are often not bi-directional with network equipment
◉ Third-party products lack Cisco’s deep understanding of the network and platforms
◉ Lack of tight integration between the hardware and software platforms
◉ Lack of cross-domain visibility between the campus, data center, and the cloud
◉ Reliance on legacy SNMP protocol which provides limited visibility and control
◉ Limited AI capabilities due to lack of data quality and domain specialization
Out-of-the-box automation with Cisco DNA Center
While there are various barriers to network automation, there are some pragmatic methods by iterating on non-change and/or non-production automation activities, leading to some “quick automation wins.” Below are some “quick automation wins” examples available out of the box with Cisco DNA Center automation.
◉ Network Device Configuration Backup and archival of all network devices.
◉ Integration with ServiceNow, which automats auto-population of trouble tickets.
◉ Automated creation of network availability baselines and compliance reporting.
◉ Automated creation of user experience baselines and reporting.
◉ Maintenance mode to enable/disable monitoring during change windows.
◉ Automated network performance testing with MRE (Machine Reasoning Engine) and features such as Truetrace and path trace to automate and expedite troubleshooting.
◉ Automated packet capture for network anomalies.
◉ Redundant Link Monitoring.
◉ RMA Automation workflows.
◉ Automated creation of application health and reporting.
◉ Software Upgrade Cycle
Granular Automation Control
In looking at Cisco DNA Center’s automation suite, Cisco DNA Center not only provides automation features but also provides the granular control to enable workflows and actions from manual to AI-assisted to selectively autonomous change management. Let’s look at the three modalities of automation possible with Cisco DNA Center:
Manual (clickOps) is where many organizations are today; all administrative actions are performed by or initiated by an operator. Numerous automated workflows need manual initiation, but they still automate numerous repetitive steps such as SWIM for software updates. Additionally, some of these can be automated through templates and EEM (Embedded Event Manager) triggers.
Figure 1. Cisco DNA Center (SWIM) Software Image Management Cycle
AI-Assisted is where leveraging the depth of knowledge, streaming telemetry, and Cisco’s vast knowledge and experience in running networks; Cisco DNA Center can identify issues and use the MRE to suggest troubleshooting steps and possible remediation. MRE is a network automation engine that uses AI (artificial intelligence) and ML (machine learning) to automate complex network operation workflows. This feature encapsulates human knowledge and expertise into a fully automated inference engine to help you perform complex root cause analysis, detects issues and vulnerabilities, and either manually or automatically perform corrective actions.
Figure 2. Cisco DNA Center Compliance automation with configuration drift
Autonomous Change Management (ACM) provides for Cisco DNA Center to be enabled to perform and enforce automated actions on the network under predefined conditions and events. As today’s networks grow at incredible rates with new demands, manually managing all aspects of the network is no longer feasible for humans. Nor do most organizations have staff watching alerts every second of the day. The integration of AI/ML into the automation engine enables Cisco DNA Center to regularly tune the network based on predictions and models, which can greatly optimize the user experience and network performance. Compare human intervention as the ax vs. AI-driven automation doing it with a scalpel. This can be the difference between a system taking proactive measures vs. correcting an issue after it occurred.
Doing a left shift and taking automation to the next level, depending on the intents and architecture of the network, there are several highly automated deployment models, such as the Software-Defined Access (SDA), User Defined Networking (UDN), and AI-RRM, which are highly ACM deployments within the Cisco DNA Center solutions suite.
Focusing on automation outcomes and benefits
Focusing on outcomes, as organizations embark on network automation, there are various success metrics and business outcomes that can be tracked, such as:
| Tangible Metrics | Intangibles |
|
Faster moves adds and changes |
Team Agility |
Source: cisco.com
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