Trellis Connect / Trellis Technologies
Trellisconnect was experiencing rapidly rising cloud costs without a clear link to product growth or customer value. Epsilon ran a focused, four-week sustainable cost reduction engagement, addressing root causes across architecture, Kubernetes efficiency, and operational habits. The result was immediate, durable savings with no performance regressions and stronger long-term cost controls.
Sustainable Cost Reduction
Cloud Cost Optimization
Kubernetes Optimization
FinOps Engineering
Infrastructure Optimization
As Trellis scaled, cloud spend increased faster than traffic and revenue. Costs were driven by over-provisioned compute, inefficient Kubernetes utilization, orphaned resources, and autoscaling configured for fear rather than data. Leadership needed immediate, meaningful savings without risking reliability or slowing delivery.
Epsilon executed a four-week, engineering-led cost reduction program focused on architecture, runtime behavior, and operational habits. Rather than relying on surface-level FinOps tactics, the engagement addressed the systems and defaults that caused waste in the first place.
Right-sized over-allocated CPU and memory across workloads
Adjusted node sizes and instance families to match usage patterns
Deleted unattached volumes, snapshots, load balancers, and IPs
Improved CPU and memory bin packing to increase pod density
Reduced node count while maintaining performance headroom
Tuned autoscaling to eliminate thrashing and overreaction
Established sane defaults for resource requests and limits
Introduced automation to prevent wasteful configurations
Mapped cost ownership to services and teams
4 Weeks; Focused cost reduction sprint with analysis, execution, and guardrails
Built service-level cost model Identified primary sources of waste
Reduced over-provisioned compute Removed orphaned and idle resources
Improved bin packing and autoscaling Reduced node counts safely
Established ownership and standards Ensured savings would persist long-term
Sustained savings driven by structural changes, not temporary discounts
within 4 weeks
Across Kubernetes clusters and underlying infrastructure
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