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Jobvite + AppDynamics: a case study in saved time

Jobvite Saves Hours Per Incident After Migrating Critical Apps and Workloads With AppDynamics

 

 AppDynamics, a part of Cisco, and the world’s #1 Application Performance Monitoring (APM) solution and full-stack, business centric observability platform, is partnering with Jobvite to save the company several hours per incident by simplifying its debugging processes and accelerating the mean time to repair (MTTR) for software bugs or errors.

 

Jobvite, an applicant tracking system (ATS) and recruiting software serving customers in many different industries, selected AppDynamics APM to migrate mission critical applications such as Recruiting and Canvas to the Amazon Web Services (AWS) cloud. Because of the competitive HR market and how essential it is to ensure a flawless digital customer experience, Jobvite needed a way to scale its digital platforms to meet an increase in usage of millions of job seekers and recruiters using Jobvite every year and thousands of customers who rely on the applications daily. To do this, Jobvite partnered with AppDynamics to enable a seamless migration to AWS without any disruption to their end users.

 

After successfully transitioning to their cloud-native microservice architecture, Jobvite turned to AppDynamics to manage and monitor its multiple AWS-based applications, including the company’s popular customer facing applications. More recently, Jobvite added observability to gain access to Deep Code Insights powered by Rookout.

 

By partnering with AppDynamics, Jobvite can pinpoint functionality issues in production, eliminating the time previously wasted sifting through log files, saving hours per incident. AppDynamics has allowed Jobvite to detect any issues early in development and resolve them before they impact customers. By providing deep performance insights at every stage of the software development lifecycle—from code insights through to production—Jobvite has accelerated innovation by bringing high-quality products to market faster. AppDynamics has allowed Jobvite to shift left and get the most important products to market faster, while still delivering the high-quality standards that the market expects.

 

Since partnering with AppDynamics, Jobvite has been able to make vast improvements, including:

 

  • Migrating all workloads to AWS within six months and with zero disruption to the end user.
  • Simplifying production debugging and rapid root-cause analysis to optimize application performance.
  • Democratizing secure access to the product runtime behavior in any environment, empowering teams to take ownership from development to delivery and accelerating MTTR for software bugs or errors.
  • Improving management of unplanned work, allowing IT teams to maintain a strategic focus and allocate resources to support business objectives.

 

“With a small but agile team, we have been able to migrate all of our workloads to AWS within just six months. There’s no way we would have been able to achieve this accelerated journey to the cloud without the performance visibility provided by AppDynamics,” says Ron Teeter, chief architect, Jobvite.

 

“The global pandemic has forced enterprises to accelerate their move to the cloud in order to remain competitive. Many technologists are concerned with missing application dependencies, but with AppDynamics and AWS, customers have the clarity they need to guide decision-making, while also planning and assessing their current cloud operational maturity, leading to a successful migration,” said Nick Bogaty, chief revenue and customer officer, AppDynamics.

 

To learn more about how to move quickly and securely to AWS with AppDynamics full-stack performance monitoring, visit here.

 

AppDynamics will have a virtual booth at AWS re:Invent, through December 18, 2020, and registered attendees can click here.

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Jennifer Evans
Jennifer Evanshttp://www.b2bnn.com
principal, @patternpulseai. author, THE CEO GUIDE TO INDUSTRY AI. former chair @technationCA, founder @b2bnewsnetwork #basicincome activist. Machine learning since 2009.