Case Studies

25M+ Users, Zero Downtime: QualityKiosk Delivers Hypercare Elasticsearch Monitoring

Industry & Segment

Tech & Digital Natives

Objective

To ensure uninterrupted, high‑performance operations of the client’s Elasticsearch‑based platform by enabling real-time issue detection, reducing downtime risks during peak loads, and optimizing cluster resources through proactive expert monitoring.

Partner

Elasticsearch

Engagement Overview

The client already had an existing Elasticsearch deployment to manage metadata and search functionality for 25 million users. During high-demand periods, they required expert technical support to proactively monitor clusters, prevent potential disruptions, and optimize resource utilization. QualityKiosk was engaged to provide hands-on Elasticsearch expertise for real-time monitoring and continuous support, ensuring optimal system performance under peak load conditions. Our role included identifying potential issues before they affected users, and coordinating with internal teams to maintain stability.

Business Objectives & Challenges

Missed Real-Time Detection

Latency and failures in Elasticsearch queries could lead to delayed responses and degraded user experience.

High-Risk Operational Windows

The constant risk of downtime during peak demand periods required continuous monitoring.

Inefficient Resource Utilization

Cluster sizing needed efficiency to avoid either over-provisioning (higher costs) or under-provisioning (performance degradation).

Limited Automation Coverage

Existing monitoring systems sent alerts but could not prevent emerging issues, necessitating expert oversight.

Proactive monitoring coverage

Lack of proactive monitoring made it difficult to spot early warning signs, leading to issues being caught only after they became critical.

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QualityKiosk’s Solution and Approach

To address these challenges, QualityKiosk implemented a multi-layered expert monitoring and optimization strategy:

Optimal Resource Utilization

With constant monitoring, the team was able to help them right-size their Elasticsearch cluster from 90+ nodes to approximately 40 nodes, while maintaining peak performance.
Helped deliver a balance of cost-effective infrastructure and robust system reliability.

Eyes-on-Glass Expert Support

Deployed certified Elasticsearch experts on-call for real-time monitoring during peak load periods.
Implemented a red-amber-green metric system to track cluster health, proactively identifying potential issues before they escalated.
Coordinated with internal teams to provide immediate remediation for any amber-level alerts.

Proactive Monitoring with Custom Dashboards

Monitored using custom-built Elasticsearch dashboards providing a holistic view of cluster health, JVM metrics, indexing throughput, and search query performance.
Enabled real-time detection of anomalies and early-warning signs before they escalated into critical issues.

Strategic Execution During Peak Demand

Coverage focused on pre-peak, peak, and post-peak periods.
Provided hands-on monitoring to complement automated alerts, offering nuanced insights only expert human oversight can deliver.

Validation Strategy

Automated Coverage Analysis

A proprietary Validation & Coverage Analysis Module assessed the AI‑generated test cases by calculating overall requirement‑to‑test coverage, identification of missing or under‑represented scenarios, and percentage‑based coverage metrics. This ensured that gaps were detected early, driving consistency and completeness across all generated test artifacts.

SME Review & Enhancement

Subject Matter Experts performed a targeted review, not full manual authoring, to validate accuracy and business relevance. Their role included reviewing AI‑recommended scenarios, adding any high‑risk or edge‑case scenarios flagged through the coverage module and ensuring regulatory and domain‑specific completeness. SME intervention was optional and value‑driven, accelerating the validation cycle.

Structural and Standards Compliance Check

The platform ensured that each generated test case adhered to standardized structures, including test summary, description, expected results and test type. This reduced variability caused by human authors and ensured uniformity across teams.

Performance Testing Strategy

Once validated, test artifacts were exported into the client’s Test Management System for workflow alignment, traceability verification and compatibility with Agile/DevOps pipelines

Results

92%

improvement in integration stability with near-zero data mismatches across modules

99.5%

driver app data reliability, ensuring consistent real-time operational visibility

Live sync

time reduced to under 3 seconds, with dashboard updates delivered in 1.05 seconds

Bug leakage

lowered to 0.7%, reflecting improved release quality and regression control

99.1%

ticket generation accuracy, enabling reliable incident and service management

87%

reduction in route logic defects across complex transport hierarchies

98.7%

accuracy achieved in the exchange engine for operational transactions

100%

validation coverage for vehicle and driver master data

70%

faster incident response, empowering depot managers with reliable real-time insights

Business Impact

Operational Improvements

Monitored the performance impact while the team optimized Elasticsearch cluster usage by almost 58%, ensuring efficient resource utilization without compromising performance.
Ensured zero disruption during high demand periods with up to 25M+ concurrent users.
Proactively prevented potential Elasticsearch performance issues before escalation.
Hands-on Elasticsearch experts provided a trusted layer beyond automated monitoring.

Strategic Business Outcomes

Stronger Brand Reputation: Enhanced platform stability minimized user complaints, leading to higher user satisfaction and reinforcing the clientʼs brand credibility.
Reduction in Infrastructure Costs: Optimized cluster sizing lowered operational expenses, improving overall ROI and freeing up resources for strategic business initiatives.

QualityKioskʼs real-time expert monitoring and guidance allowed the client to deliver uninterrupted service under extreme load conditions. By combining proactive issue
identification, continuous support, and resource optimization, we ensured system stability while enabling the client to operate more efficiently and with greater confidence.

This engagement demonstrated how strategic technical oversight can enhance operational resilience and platform performance during periods of high demand, even in pre-existing infrastructure environments.