Where is Your CSP on the Closed Loop Automation Journey?
Automation in telecom is not new. But it has evolved.
Initially, it was about being more efficient at solving well-defined problems – the known knowns. Solutions like Root Cause Analysis that reduced tens of thousands of NOC alarms to a single “parent alarm”, which highlighted the underlying problem.
From there automation progressed to addressing known problems that are characterized by more dynamic scenarios – the known unknowns. With known unknowns you can’t know ahead of time the full spectrum of scenarios and parameters that you might confront – but you know the broad characteristics and can code for them ahead of time. An example of this is self-optimizing mobile networks. You don’t know where or when coverage holes will occur, but you can detect them and up-tilt surrounding antennas to mitigate the problem.
Today, we are moving into the era of the unknown unknows where software can identify problems that we can’t necessarily code for in advance. It’s like detecting and mitigating new cyber threats that were never encountered before. Machine Learning and Artificial Intelligence are the ‘secret sauce’, that, for example, could enable software to progressively learn traffic patterns, detect anomalous deviations from the norm and initiate relevant mitigation.
What is Closed-Loop Automation?
And as automation has matured, CSPs are increasingly willing to close the loop and let the software automatically resolve the detected problem without needing human intervention. In the words of Frost & Sullivan, this comes into play “when the carrier’s network is equipped to analyze subtle and diverse traffic characteristics, reach high-fidelity conclusions, and act on those conclusions in real time. The positive outcomes can be immense”. This is full-blown Closed Loop Automation (CLA). An illustrative example comes from the world of dynamic, QoE based congestion management.
But how ready are CSPs to embrace CLA?
- What are the key use cases they use, plan to use and would like to use?
- What industry trends will drive CLA adoption?
- Where are CSPs committing budgets, what are key barriers and whom do they think can best provide solutions?
To find out, we asked them – via a survey of 100 CSPs around the world. On February 13th we hosted a live webinar with Next Curve sharing industry attitudes toward CLA and presenting Allot and Next Curve’s insights.
Among the interesting findings were:
- While CSPs are becoming increasingly customer focused, adopting service assurance automation solutions – they still perceive CLA as more about network KPIs than customer KQIs.
- Popular current implementations of closed loop network automation address bandwidth optimization and prominent budgeted scenarios include DDoS detection and mitigation.
- Two-thirds of CSPs prefer to get CLA solutions from outside their organizations and the biggest barrier to adoption is lack of required skillset.