ClearSlide
Optimizing a next-generation sales engagement platform for managing opportunities, teams, and individual reps based on actual customer engagement data.
Back End Development
Quality Assurance
Java, Spring, Concurrency, AWS, docker, Kubernetes, FFmpeg, Selenium, Grafana, Prometheus, MySQL, Datadog
Java Tech/Team Lead
3 Java Developers
Automation QA Engineer
DevOps
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About the Client.
An innovative US based IT company developing solutions for sales engagement and management that integrate content, communications, and actionable insights to improve business results.
Challenge.
Client’s sales engagement platform was aimed at providing customers with a microservice for video calls and conferencing with the possibility of speech and video recording. To ensure stable functioning of this microservice, the client reserved substantial number of cloud servers. Their reserved capacity was the same, regardless of the time of day or users’ activity load. This resulted in permanent unreasonable expenses for the client’s business.
The client needed to optimize the usage of server space, keeping the platform capacity at the same time to withstand users’ activity load and reduce the server costs.
Solution.
Solution
We introduced sales engagement platform to the client, which was a flexible solution for real-time management of the server space needed for stable platform functionality. This was done through development and integration of a service discovery and a custom load balancer.
Functionality
The service discovery collected and stored data about the average server capacity needed for stable functioning of the microservice. To enable its functioning, we developed the system and custom metrics and integrated them with Grafana through Prometheus.
Server
The custom load balancer analyzed the servers load and incoming requests for the server space. It assigned performance of the microservice to the server with sufficient capacity as well as scaled-up and down the servers when needed.
Business
Value.
Our solution allowed our client to involve server capacities when needed, and not to reserve excessive server capacities which led to reduced costs.
Our team conducted business analysis to clarify all the business requirements and develop clear technical requirements.
We developed the service discovery and load balancer and integrated the metrics with the third-party solutions.
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