Revitalizing Performance for a Growing Enterprise Workflow Platform
Resolving critical database bottlenecks and optimizing Azure infrastructure to reduce query times by 82% while enhancing reliability
Overview
A mid-sized enterprise software company headquartered in Pune developing workflow automation solutions used by over 180 mid to large enterprises across India, UAE, and Southeast Asia. Their platform manages critical business processes including procurement, employee onboarding, compliance workflows, and approval chains for over 250,000 end users.
Following rapid customer growth and expansion of their feature set, the platform began experiencing significant performance degradation, particularly in database-intensive operations. Customer complaints about slow response times and unreliable backup processes threatened renewal rates and expansion opportunities in competitive enterprise markets.
Business Challenges
Database Performance Issues
Query response times exceeding 15-20 seconds for complex workflow reports
Managed PostgreSQL instances struggling during peak business hours
Connection pooling issues causing intermittent timeouts
Gradual performance degradation as database size exceeded 800GB
Query performance varying unpredictably between similar customer instances
Azure Infrastructure Inefficiencies
Over-provisioned resources with utilization below 35% during off-hours
Inappropriate tier selection for various Azure services
Ineffective auto-scaling configurations causing performance spikes
Monthly Azure costs exceeding ₹16 lakhs with poor cost-to-performance ratio
Limited use of Azure PaaS capabilities increasing operational overhead
Monitoring Limitations
Reactive troubleshooting after customer complaints
Limited visibility into database query performance
No correlation between user experience and system metrics
Siloed monitoring across application, database, and infrastructure layers
Insufficient alerting leading to delayed response to emerging issues
Backup and DR Concerns
Inconsistent backup success rates with occasional failures
Backup processes impacting production performance
Recovery testing conducted infrequently with uncertain results
DR process largely manual with recovery time exceeding 6 hours
Limited point-in-time recovery capabilities for specific workflow data
Our Solution
We implemented a comprehensive performance optimization strategy focusing on database efficiency, Azure right-sizing, enhanced monitoring, and robust disaster recovery.
Assessment & Strategy
We conducted a thorough analysis of existing database and infrastructure configurations, identifying root causes and developing a strategic remediation plan.
Database Performance Analysis
Conducted comprehensive query performance profiling and bottleneck identification
Analyzed indexing strategy and query execution plans for optimization opportunities
Evaluated connection management practices and configuration settings
Benchmarked performance against PostgreSQL best practices
Azure Architecture Review
Performed detailed assessment of current Azure resource configuration
Analyzed resource utilization patterns across different time periods
Evaluated service tier selections against workload requirements
Identified cost optimization opportunities with minimal performance impact
Observability Gap Analysis
Mapped current monitoring coverage against critical service paths
Evaluated existing alerting effectiveness and response procedures
Assessed log aggregation and correlation capabilities
Identified visibility gaps in end-to-end transaction flows
Business Impact & Results
Query Performance
•Average query time reduced from 15-20 seconds to 2.7 seconds
•Complex report generation time decreased from 45 seconds to 8 seconds
•Eliminated timeout errors during peak usage periods
•Maintained consistent performance across all customer instances
Azure Optimization
•Reduced monthly Azure costs from ₹16 lakhs to ₹9.4 lakhs
•Improved resource utilization from 35% to 78%
•Eliminated performance spikes through proper auto-scaling configuration
•Reduced management overhead by 65% through appropriate PaaS adoption
Monitoring Effectiveness
•Proactively resolved 92% of issues before customer impact
•Reduced mean time to detection from 95 minutes to 21 minutes
•Improved root cause analysis time by 68% through correlated monitoring
•Created full performance visibility across system components
Business Continuity
•Reduced disaster recovery time from 6+ hours to 53 minutes
•Improved backup success rate from 94% to 99.98%
•Eliminated production impact during backup operations
•Successfully demonstrated point-in-time recovery for critical workflow data
"VegaStack improved platform reliability, resolved database issues, and optimized Azure for cost savings. Their monitoring offered unmatched system visibility, and knowledge transfer empowers our team to maintain long-term improvements."
Key Takeaways
Database-First Approach
Focusing on database optimizations delivered the most immediate and significant performance improvements.
Right-Sizing Methodology
Systematic right-sizing based on actual workload patterns yielded substantial cost savings without performance compromise.
Correlated Monitoring Value
Implementing end-to-end monitoring with correlation between user experience and system metrics transformed troubleshooting effectiveness.
Proactive Recovery Testing
Regular automated DR testing revealed and resolved subtle recovery issues before they affected real recovery scenarios.
Conclusion
This engagement transformed the client's workflow platform from a performance liability into a reliable foundation for their enterprise customers. By implementing a comprehensive approach to database optimization, Azure infrastructure refinement, and enhanced monitoring, we helped them achieve the performance and reliability standards expected in enterprise software.
The optimized platform now provides a foundation for their continued expansion in the competitive workflow automation market. With dramatically improved query performance, they can confidently onboard larger enterprise customers while maintaining the responsive experience business users expect. The established performance governance practices ensure they can sustain these improvements while continuously enhancing their platform capabilities for increasingly complex enterprise workflows.
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