Promptly scales patient-care AI with DoiT's Accelerator
- $600K
- Annual cloud cost savings
- 3x
- Months of engineering time saved
How LivePerson manages hundreds of microservices with Kubernetes
LivePerson simplified application deployment and achieved major cost savings by implementing Kubernetes and Google Kubernetes Engine for their messaging platform
- Hundreds of thousands of dollars
- Annual savings
- Hundreds of thousands of dollars
- Annual savings from autoscaling
“DoiT International delivered a roadmap for Kubernetes. So we knew what to expect, and when, and, almost every week for the past year, we have had workshops with their team to discuss features and implementation.”
The Challenge
LivePerson's platform is built on hundreds of microservices that serve large-scale enterprise contact center messaging for major banks and telecommunications companies. The vast number of traffic and data points touching their platform made application deployment and delivery increasingly complex. Their growing number of services made changes more painful, and while Docker offered application simplification, it made operations complex and wasn't scalable for their massive ping volumes.
The Solution
LivePerson implemented Kubernetes and Google Kubernetes Engine to manage their microservices at scale. They chose Google Kubernetes Engine because its implementation of Kubernetes is mature and hassle-free, with no vendor lock-in. The solution enables independent teams to run their own applications and clusters without DevOps assistance. DoiT International provided a roadmap for Kubernetes implementation and conducted weekly workshops to discuss features and implementation approaches.
Results
- Saved hundreds of thousands of dollars annually through autoscaling capabilities
- Enabled independent teams to manage workloads without DevOps assistance
- Simplified cluster management while maintaining scalability for enterprise operations
- Achieved transparent application deployment in hybrid cloud environments
Meet LivePerson
LivePerson develops products for online messaging, marketing, and analytics, including LiveEngage, a messaging platform that enables real-time customer service. By pioneering web-based user-engagement systems, LivePerson has become the world's most successful messaging and bots platform for brands. LiveEngage enables real-time conversations between large enterprises and their customers on websites, mobile, and social networks. Founded in New York in 1995, today LivePerson has offices in 10 countries and monitors around 3 billion internet visitors every month.
A Natural Fit with Kubernetes
For companies providing SaaS solutions, success often brings increased complexity that makes product management more difficult. LivePerson realized their number of services was growing rapidly, making changes increasingly painful. To solve this challenge, they implemented Kubernetes and Google Kubernetes Engine. With no vendor lock-in, they had freedom to choose the best cloud provider available. They chose Google Kubernetes Engine because its implementation of Kubernetes is mature and hassle-free. Several independent teams run their own applications and clusters, and the combination enables them to manage workloads without assistance from DevOps or other operational teams.
Implementation with DoiT International
To implement Kubernetes and Google Kubernetes Engine, LivePerson partnered with DoiT International. It was clear they needed a partner to discover the new area of application delivery. They contacted Vadim Solovey, Chief Technology Officer of DoiT International, and began their journey discovering the potential and discussing approaches. DoiT delivered a comprehensive roadmap for Kubernetes implementation, providing clarity on expectations and timelines. Almost every week for a year, they conducted workshops with the DoiT team to discuss features and implementation strategies.
Major Savings with Autoscaling
By simplifying and improving cluster management with Kubernetes and Google Kubernetes Engine, LivePerson created efficiencies with direct financial impact. Their performance testing build is a batch process that happens periodically. With autoscaling, they don't have to keep clusters at full capacity all the time, saving hundreds of thousands of dollars annually. The team is now looking to use more aspects of Google Cloud Platform to improve services by leveraging data, including better data mining, deep learning, and other tools for their data scientists.
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Dr. Anish Kapur, Founder & CEO, Promptly
DoiT's Customer Success and Forward Deployed Engineering teams work very closely with us. The regular sessions with our CSM keep us focused on the right priorities, and the FDEs provide the deep technical guidance we need to validate decisions and optimize our environment. That combination has been genuinely valuable for us.
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