Trellis Connect / Trellis Technologies
Insurtech / Cloud Platforms / Real-Time Systems
Executive brief
Slashed 26% off Annual Cloud Costs in 4 Weeks
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.
Annualized cloud cost savings
$3.2M+
Monthly cloud spend reduction
~47%
within 4 weeks
Compute footprint reduction
~38%
$3.2M+ in annualized cloud cost savings
~47% reduction in monthly cloud spend
~38% reduction in total compute footprint
~60% reduction in idle and underutilized resources
Engagement shape
Duration
4 wks
Phases
4
Deliverables
5
Annualized cloud cost savings
$3.2M+
How it ran
Focused cost reduction sprint with analysis, execution, and guardrails
Epsilon helped Trellis Connect eliminate $193k in annual cloud waste in just four weeks by fixing the engineering systems that caused costs to creep.
Starting position
What Trellis Connect / Trellis Technologies was working against.
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.
Constraints we worked inside
4 in playEvery one of these ruled an easier option out. They are the reason the approach looks the way it does.
Production systems could not experience downtime
Cost reduction needed to show results within weeks, not quarters
No performance or reliability regressions were acceptable
Savings needed to persist long-term, not rebound after optimization
What had to be true to finish
4 goalsAgreed up front, so the engagement could be called finished on evidence instead of opinion.
Reduce cloud spend aggressively and safely
Identify and eliminate structural sources of waste
Improve Kubernetes efficiency and scaling behavior
Establish guardrails to prevent cost creep from returning
Industry context
Insurtech
Cloud Platforms
Real-Time Systems
Trellis Connect operates a real-time insurtech platform where cloud infrastructure directly impacts customer experience, reliability, and unit economics. The system handles bursty traffic, sensitive data, and high availability requirements, making cost efficiency and reliability inseparable concerns.
Approach
How the work was sequenced.
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.
Delivery track
Segment width reflects the number of workstreams inside each phase — where the engagement actually spent its effort.
Cost & Runtime Analysis
5 workstreams
Service-level and workload-level cost attribution
Kubernetes utilization analysis (requested vs actual CPU and memory)
Identification of idle, orphaned, and zombie resources
Traffic and workload profiling across peak and off-peak periods
Mapping cloud spend back to real business workflows
Right-Sizing & Resource Cleanup
4 workstreams
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
Decommissioned abandoned environments and legacy infrastructure
Kubernetes Efficiency & Bin Packing
4 workstreams
Improved CPU and memory bin packing to increase pod density
Reduced node count while maintaining performance headroom
Tuned autoscaling to eliminate thrashing and overreaction
Separated bursty and steady-state workloads to prevent over-scaling
Guardrails & Cost Durability
4 workstreams
Established sane defaults for resource requests and limits
Introduced automation to prevent wasteful configurations
Mapped cost ownership to services and teams
Defined lifecycle expectations for environments and resources
What the team kept
Artefacts handed over at the end of the engagement — owned and operable by Trellis Connect / Trellis Technologies without us.
Service-level cost attribution model
Right-sizing recommendations and applied configuration changes
Kubernetes scaling and bin-packing improvements
Orphaned resource cleanup and decommissioning plan
Cost guardrails and engineering ownership patterns
Results
What actually moved.
Within four weeks, Trellis Connect achieved dramatic, measurable cost savings while improving reliability and operational clarity. Savings were realized immediately and continued month over month due to structural improvements and guardrails.
Outcome ledger
Every figure we measured on this engagement, including the ones that are ranges rather than headlines.
Annualized cloud cost savings
Sustained savings driven by structural changes, not temporary discounts
$3.2M+
Monthly cloud spend reduction
~47%
within 4 weeksCompute footprint reduction
Across Kubernetes clusters and underlying infrastructure
~38%
Idle / underutilized resources eliminated
~60%
Customer-visible downtime
0
What changed day to day
The part of the result that never shows up in a dashboard, but is the reason the numbers held.
Improved reliability due to cleaner scaling behavior
More predictable capacity planning
Greater confidence that efficiency would not slow delivery
Clear ownership of cost-driving engineering decisions
Your turn
Run this play with your team.
Epsilon helped Trellis Connect eliminate $193k in annual cloud waste in just four weeks by fixing the engineering systems that caused costs to creep. If that shape looks familiar, the first conversation is a working session, not a pitch.
Sustainable Cost Reduction
Cloud Cost Optimization
Kubernetes Optimization
FinOps Engineering
Infrastructure Optimization
What Trellis Connect / Trellis Technologies got
Annualized cloud cost savings
$3.2M+
Monthly cloud spend reduction
~47%
within 4 weeks
Compute footprint reduction
~38%