Overview

Finvantage, a FiTech firm processing millions of daily transactions, wanted an automated and instant response system to reduce downtime and boost service reliability. With our DevOps practices, we enabled real-time issue resolution, proactive monitoring and faster recovery across their microservices-based infrastructure, ensuring seamless operations at scale.

Technical Stack

  • Kubernetes
  • Prometheus
  • Grafana
  • Jenkins
  • AWS Lambda

    • Industry

    Finance

  • region

    • Region

    United States

  • project-size

    • Project Size

    Non- Disclosable

Highlights

Reduced MTTR by 70%

Achieved 99.99% system uptime

Increased incident resolution speed by 85%

40% lower operational costs

Challenges & Solutions

It impacted service reliability and caused extended downtimes that frustrated customers.

  • Solution: We implemented an automated monitoring system using Prometheus and Grafana to enable instant issue detection and automated recovery. This reduced MTTR by 70%, ensuring faster detection, response, and improved system reliability.

Manual Incident Management Slows down Resolution and delayed response times and reduced overall service efficiency.

  • Solution: By leveraging AWS Lambda and Jenkins CI/CD, we implemented an automated incident response framework with real-time alerts. This reduced issues and were handled automatically, which boosted resolution speed by 85%.

The complexity of the microservices setup created vulnerabilities in uptime and service continuity.

  • Solution: Our experts utilize Kubernetes to orchestrate and manage microservices across multiple nodes to enable redundancy, auto-scaling, and seamless failover. The solution resulted in 99.99% uptime and uninterrupted service.

High Operational Costs Due to Inefficient Resource Allocation. Inefficient resource allocation increased operational costs, resulted in underutilization, and negatively impacted performance.

  • Solution: We optimized compute resources by implementing resource allocation policies based on actual demand patterns. The solution enabled dynamic resource allocation, reducing costs by 40% and optimizing performance during peak loads.

Core Features

  • Automated incident response with AWS Lambda
  • Continuous integration and delivery with Jenkins
  • Real-time monitoring with Prometheus and Grafana
  • Redundant Kubernetes clusters for high availability
  • Dynamic auto-scaling to optimize resources
  • Proactive issue detection and alerting
  • 24/7 support and incident management
  • Cost-effective resource allocation
  • no.-of-resources

    • No. of Developers

    06

  • time-frame

    • Time Frame

    March 2023 - November 2024

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