TechValidate Research on Kentik


Kentik Case Study

Pennsylvania’s Chesconet Boosts Network Performance and Security with Kentik Detect

Introduction

This case study of Chester County Community Network (Chesconet) is based on a June 2017 survey of Kentik customers by TechValidate, a 3rd-party research service.

Larry Konig, Network Operations Manager of Chesconet:

“We were in the market for a replacement for our existing NetFlow-tracking software package for a while. Most of the replacement solutions we considered turned out to be very, very expensive and required using the vendor’s dedicated hardware.

Kentik’s solution generates reports for us way faster than our old system ever did and it retains data longer. Now we can generate monthly reports for our customers rather than daily or weekly reports.

The best surprise with Kentik is the platform’s DDoS detection and mitigation capabilities. Kentik’s capabilities are having us re-think how we’re going to mitigate DDoS activity in the future."

Challenges

Chesconet found that generating network analysis and planning reports required too much of its team’s time.

Use Case

Chesconet selected Kentik for:

  • Long-term retention of full network data details
  • Power and flexibility of anomaly detection
  • Real-time, ad-hoc big data analytics
  • Quality and openness of API
  • SaaS ease of deployment

When compared to competition, Chesconet rates Kentik best-in-class for:

  • Analytics & reporting
  • Anomaly & DDoS detection
  • API & automation-friendliness
  • Scalability & performance
  • Ease of deployment

Results

With Kentik, Chesconet achieves:

  • Increased network security and improved DDoS defense — with 25-50% more attacks defended
  • Self-service of network visibility — with 50-100% better use experience
  • Faster problem resolution
  • CAPEX savings
  • OPEX savings




About This Data

This data was sourced directly from verified users of Kentik by TechValidate.

TechValidate verifies the identity and organizational affiliation of all participants that contribute to published research data. When research participants so desire, we also guarantee their anonymity so that they may share information honestly and freely.


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