Trellis Connect
Insurance quote workflows require speed and security. Epsilon optimized Trellis’s container startup path, tuned Kubernetes scheduling and autoscaling, and implemented security guardrails to support sensitive data and burst traffic—enabling real-time quote experiences.
Kubernetes performance optimization
Security hardening
Container startup optimization
Autoscaling strategy
A core quote service had ~10-minute startup time, making just-in-time compute impossible and harming user experience, while security requirements remained high.
Epsilon optimized startup behavior, tuned Kubernetes runtime controls, and implemented security and observability guardrails.
Adjusted resource requests/limits to reduce scheduling delays
Introduced autoscaling tuned to burst traffic
Implemented safe rollout strategies and rollback patterns
Least-privilege IAM patterns and secret handling
Network segmentation and policy baseline
Audit-friendly logging and access patterns
6 Weeks; Performance optimization + scaling + security hardening
Readiness alignment Init sequence optimization
Autoscaling tuning Rollout strategy hardening
Guardrails and access controls Operational documentation
post-optimization • Illustrative
post-scaling • Illustrative
post-hardening • Illustrative
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