How Easyway improved MTTR by 60% and Saved Dozens of Developer Hours a Month using Lightrun Logs and Snapshots

About Easyway 

Easyway is a cloud-based platform that provides a suite of artificial intelligence-powered tools to automate customer service and support tasks. The platform uses natural language processing (NLP) and machine learning (ML) to interpret customer inquiries and generate accurate and timely responses. Easyway’s tools include a chatbot builder, live chat support, and an AI-powered knowledge base that can be integrated with popular customer support channels like Facebook Messenger, WhatsApp, and more. With Easyway, businesses can save time and resources by automating their customer service workflows while still providing high-quality support to their customers.

The Challenge

Easyway’s developers build their guest relationship management platform on top of multiple Node.js microservices running on Amazon’s EKS Kubernetes clusters. These services were previously single-instance pods but the company recently moved to using replicas as part of a major scaling process happening in the organization. Easyway engineering team was aiming to properly support the increasing traffic and address issues when they arise.

Specifically, the developers were dealing with problematic request-response debugging cycles in the service that manages their integrations and in the MKS Kafka cluster that the integrations used as a data streaming layer. The developers added logs to debug the requests going out, the responses coming in and to the Kafka consumers to gain further insight into what was happening. 

However, debugging was still difficult as they would have to release multiple deployments with additional logging, which was too time-consuming and resource-intensive. The developers needed a more efficient solution to debug the services

The Solution

Lightrun helped the Easyway developers by providing a comprehensive view of their micro-services running on Amazon EKS and their data streaming layer on top of MKS, enabling them to quickly identify and address increased traffic issues in case they occur.

By using Lightrun, developers were able to add logs without hotfixing, redeploying or even restarting to multiple components in the system, including:

1. Their own code processing the incoming API responses
2. The Kafka consumers in charge of handling the data receive from the API requests

By utilizing the Lightrun Visual Studio Code plugin to add Logs and Snapshots to running applications, the Easyway development team were able to quickly investigate and troubleshoot their pods during a massive scale-up, without relying on iterative and manual deployment steps.

The Results

Using Lightrun platform, Easyway developers were able to improve MTTR by 60% 

Easyway developers were used to troubleshooting sessions lasting many hours due to their existing tool stack prior to bringing on Lightrun. After adding Lightrun to the development ecosystem, the engineering team was able to better troubleshoot Amazon EKS deployments from their native IDEs, shorten their MTTRs, and optimize their workflows.

Today, using Lightrun, developers reduced troubleshooting time from hours to mere minutes using Lightrun’s read-only, real-time Logs and Snapshots, and have accredited Lightrun as being a major success driver in their current scale-up process.