UNICORNE | WHITEPAPER
Load balancers, auto-scaling, crossregion transfers and detailed logging create interdependencies where optimising one component inadvertently increases costs elsewhere.
“ With thousands of updates each year, even seasoned teams can’ t keep up,” says Éric Pinet, CEO of Unicorne, a company that specialises in AWS transformations. Before founding Unicorne in 2018, Éric spent eight years managing development teams of up to 125 people.“ Add to this the complexity of interdependencies and costs become impossible to predict without the right tools.”
Today, the company’ s SaaS offering, Stable, constantly monitors enterprise
AWS infrastructure from Lambda functions to ElastiCache clusters, providing real-time, smart alerts and savings recommendations.
A four-level framework for optimisation Éric’ s team developed a framework over years of managing infrastructure across multiple organisations. The approach prevents teams from jumping to complex architectural changes whilst overlooking easy wins that deliver immediate impact.
Level 1: Quick wins( days) These require no downtime, architectural changes or code deployments.
THREE MISCONCEPTIONS THAT PREVENT OPTIMISATION
1.
2. 3.
THE DOWNSIZING TRAP:“ Downsizing can slow workloads so much that they end up costing more,” Éric warns. An undersized database creates bottlenecks, causing applications to retry requests and spawn processes. The solution isn’ t about making resources smaller but about matching capacity to actual demand, plus a reasonable buffer.
THE PROJECT MENTALITY: Another misconception is that optimisation is a one-time project.“ Like security, it must be continuous,” Éric says.
THE NATIVE TOOLS ILLUSION:“ There’ s the belief that AWS’ s free tools are enough,” Éric adds.“ They can be helpful, but they are generalist and often late. We’ ve consistently found savings of 30 % or more through deeper analysis.”
112 November 2025