The era we live in witnesses the changes, creations, closures, and operation of the applications and workloads at an exorbitant pace- much faster than the potential of NetOps teams. Zillions of devices interconnected through various applications make the human-driven networks next to impossible. The networking divisions of organizations are in the transition phase- from virtualization to automation. Though IT division is now more dynamic than ever, still many organizations are working with the conventional (manual) approach.
Mostly, the networking teams manage the devices one at a time- the tactic being tedious, inefficient, and more prone to errors. With the increase in the number of switches, firewalls, routers, and ADCs, the networking teams are not able to accurately hold up the operations. The complexities are fueled by the roll-out of 5G and skyrocketing IoT devices. All this demands the physical network to be a virtual one with software-defined capabilities.
To counter all these glitches, a relatively modern branch of automation has evolved; enunciated as Closed-Loop Automation.
Simply stated, Closed-Loop Automation enables the NetOps team to actively manage a large, growing network without ramping up the workforce and with minimal errors. Leveraging data analytics, Closed-Loop Automation monitors and evaluates the faults within the network and rectifies the issues accordingly.
In Closed-Loop Automation, the term ‘loop’ interprets the feedback communication cycle between identifying, adjusting, and optimizing the overall performance of the networking infrastructure to empower it with self-optimization capabilities.
To get a network function as envisaged, the administrators have to go through few specific phases viz. Planning, Designing, Deploying, Configuring, Verifying, Monitoring, and Maintaining. In the last two phases of ‘Monitoring’ and ‘Maintaining’, the cognizance of all potential issues and auto-remediation plays a critical role, which is possible due to closed-loop automation. This can easily sustain the network’s health and its compliance with standards.
It is a solution of managing the entire networking infrastructure as a single system, which greatly enhances efficiency and accuracy- the two main things being greatly missed in the NetOps systems today.
CLA is undoubtedly the next major development in networking automation as continually validating the network automatically rectifies the fudge factors and revalidate the network after remediation steps are executed.
This way the human intervention is greatly reduced, saving them time and efforts for core business and more productive tasks. Network configuration across devices gets more consistent and the meantime for incident resolution is reduced. All these leading-edges enhance the efficiency and accuracy of managing the devices at a time.
Also known as Self-healing Network, the Auto-healing network, and Closed-Loop Assurance, the technology incorporates Networking, Scripting, Artificial Intelligence, and DevOps tools like Kubernetes, Dockers, monitoring, and other CI/CD tools.
To achieve the fruitful level of Closed-Loop Automation, the platform must possess capabilities to efficiently execute the following steps:
It is very important to collect and parse data related to configurations and network devices to extrapolate the dots and take indemnifying actions automatically.
The collected data then needs to be stored across internal databases to generate insights by tracking metrics and events over a period of time.
Leveraging descriptive analytics and machine learning, the platform must perform classification and clustering of issues, thus deviations from baseline behaviors are monitored.
In this step, the platform auto-executes the corrective steps required in case of deviation from the baseline behavior. The possible actions are first assessed and then implemented accordingly. For Example – If the issue is having lesser severity then the alarm is raised and in case of highly critical issues, the system interface is auto-shut and the operation teams are notified immediately. The logic behind auto-remediation can be implemented using scripting languages like Python.
The following are some main use cases of the Closed-Loop Automation
With the CLA in action, the networking teams can easily check the traffic causing malfunction of the network. Gain app-centric visibility into network infrastructure, observe historic and current data related to applications, network devices, and configurations to identify vulnerabilities, trigger alerts, and execute auto-remediation actions immediately in case of inconsistencies and issues. By integrating the incident management platforms into the automation workflows, the escalation and approval steps can get automated.
The redundant network operations can be automated end-to-end for faster delivery, ensuring the application’s high availability and peak performance. The automation of configurations to network devices is the most important aspect during application deployment.
The network health can be constantly monitored and during network congestions, latency, interface queue depth issues, additional bandwidth can be provisioned or load sharing can be performed easily with closed-loop automation.
The leading edges imparted to the networking teams:
As human intervention is greatly reduced with closed-loop automation, the service delivery is greatly enhanced.
Human errors have been established as the most prominent cause of network outages and application availability issues.
As the troubleshooting is simplified and the potential human errors are eliminated, the risks of network outages are greatly reduced.
As efficient automation facilitates the application with the most optimized and compliant network for their specific requirements, the downtime is reduced to a great extent.
With Closed-Loop automation, the focus shifts from fault identification to performance optimization, empowering businesses to get greater value, reputation, and productivity with time.
Implementing Closed-Loop Automation might be challenging for organizations as it demands greater trust between operators, software layers, and the networking hardware. A mindset change is also required to trust a sophisticated system remediating the network issues on its own.
Moreover, the dynamic routing protocols have a provision of automated remediation, which counters other impediments.
Also, it is not mandatory to completely transform network operations with Closed-Loop Automation. One can start with simple but routine tasks where there is expertise and complete data for automating the system. Gradually such transformations can be made into other components and can be integrated into the main system.