Ensuring 24/7 Reliability: How This Finance Company Achieved 37% Reduction in Downtime Through SRE Implementation

Project Overview

A high profile Finance Company engaged IQZ Systems to transform their API ecosystem and consumer-facing web applications with a focus on mission-critical 24/7 support.

With over 3 million active consumers relying on their digital services, the company needed to address reliability gaps, particularly during off-peak hours (9 PM - 6 AM CST) when issues previously went undetected.

The key requirement was to create a proactive, observable, and autonomous system that would ensure consistent service reliability while improving customer experience.

Challenges Faced

• Delayed Incident Detection — Issues often went unnoticed during off-peak hours.

• Limited Traceability — Difficulty tracking transactions across distributed microservices.

• Customer Experience Issues — Frontend problems with AEM (Adobe Experience Manager) components.

• SLA Risk — High potential for violations affecting millions of active consumers.

• Reactive Approach — Legacy infrastructure lacked proactive monitoring and automation.

Solution — SRE-Driven Azure-Native Platform

After evaluating various approaches, an SRE (Site Reliability Engineering) methodology built on Azure-native technologies was selected because it could:

• Enable proactive detection of issues before they impact users.

• Provide unified observability across all application layers.

• Automate common resolution workflows to minimize human intervention.

• Establish clear reliability metrics tied to business outcomes.

The implementation focused on creating an autonomous, resilient platform with comprehensive monitoring capabilities.

Technology Implementation

To enable robust reliability engineering, the company deployed a comprehensive technology stack:

• Unified Observability — Azure Monitor, Application Insights, and Log Analytics Workspace for cross-platform dashboards.

• Proactive Alerting — Azure Alerts with custom tagging for real-time categorization of errors.

• Automated Resolution — SRE playbooks and runbooks for standardized incident response.

• Content Delivery Monitoring — AEM-specific health checks and dispatcher caching validation.

• Synthetic Testing — Scheduled API and UI tests from global regions to verify uptime and performance.

• Enterprise Logging — Scalable log storage using Azure Blob Containers for compliance and quick root cause analysis.

This structured approach allowed for all-round visibility across all critical systems while enabling automated responses to common issues.

Quality Control Process

System reliability was a major focus throughout the implementation. A robust monitoring and quality control process was established which:

• Defined clear Service Level Objectives (SLOs) for each API with 99.95% uptime targets.

• Implemented error budget tracking to quantify reliability impact.

• Created smart thresholds to reduce alert fatigue and focus on meaningful signals.

• Measured and continuously improved Mean Time to Acknowledge (MTTA) and Mean Time to Resolve (MTTR).

This metrics-driven approach significantly improved system stability and user experience.

Final Results

• Successfully reduced downtime by 37% through proactive monitoring and automated diagnostics.

• Decreased AEM latency by 22% through performance-tuning of backend APIs and image delivery workflows.

• Achieved zero-touch incident resolution for 41% of cases using runbook automation and healing scripts.

• Revamped OKTA integration to eliminate orphaned auth records, improving login success rate.

• Reduced alert volume by 60% via smart thresholds, minimizing alert fatigue.

• Built scalable, queryable log storage facilitating long-term retention and compliance.

Lessons Learned

• Observability is Foundation — Comprehensive monitoring provides the basis for all reliability improvements.

• Automate Strategically — Focus on high-impact, repeatable scenarios for maximum ROI.

• Define Clear Metrics — SLOs and error budgets create objective reliability targets.

• Cultural Shift Matters — SRE principles require organizational buy-in beyond technical implementation.

• Balance Alerting — Smart thresholds prevent alert fatigue while ensuring critical issues are addressed.

The implementation has positioned this leading financial enterprise to support their digital services with confidence, enabling the platform to maintain reliability at scale while delivering an improved customer experience through their API ecosystem and consumer interfaces.