SQAWebinar637: Automate and Optimize Your Test Lab with Software-Defined Networking #pluribusnetworks #SQAWebinars15Nov2018

SQAWebinar637: Automate and Optimize Your Test Lab with Software-Defined Networking  #pluribusnetworks #SQAWebinars15Nov2018

URL TO REGISTER:  CLICK HERE

When: Tuesday, November 15 2018,  1 PM EST

What You Gain:

  • Create, automate, and provision production-like test environments in minutes, not days
  • Cable once and automate to instantly share expensive local and remote lab resources
  • Leverage programmability and cost efficiencies to automate and streamline test lab operations
  • Support next-generation interfaces with upgradeability to 10, 25, 40, and 100 gigabit connections
  • Gain real-time visibility into lab performance and efficiency with embedded network visibility, analytics, and resource utilization
  • Q&A

Who Should Attend?

  • Test Engineers- Yes
  • Test Architects- Yes
  • Mobile/Automation Engineers- Yes
  • QA Managers- Yes
  • QA Directors- Yes
  • VP QA- Yes
  • CTO- Yes
  • Anyone who has curiosity to know about SQA/Testing Automation

Sponsor(s):  

Speaker(s):

Steven Shalita

Hashtag: #SQAWebinars15Nov2018 

Details:

Your organization is under pressure to deliver new products faster, and test lab environments are the center of innovation. However, lab infrastructure often relies on manual processes and slow updates that do not meet the expectations of speed and reliability. Costly gear might be underutilized, and cabling requests for any changes create a bottleneck, impeding the entire release velocity and the ability for your lab to scale and grow. Lab infrastructure needs to become more automated, dynamic, and efficient.

Join this web seminar to learn how to transform your lab into an agile, elastic, self-service environment that will improve resource utilization, decrease test cycles, and reduce operational costs. We will explore best practices for leveraging software-defined networking (SDN) technology to scale and optimize your lab environment with production-like precision while reducing complexity and improving operational efficiency.

 

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