MANAGING AWS COST OPTIMISATION IN THE GEN AI ERA
Reserved instances, savings plans and spots instances can reduce costs 30 – 70 % for consistent workloads, while unused resource cleanup identifies orphaned snapshots, unattached EBS volumes, forgotten AMIs and idle load balancers. Storage class optimisation moves rarely accessed S3 data to cheaper tiers, and region cost arbitrage takes advantage of regional price differences for non-latencysensitive workloads.
“ We’ ve seen clients cut 37 % off their cloud bills in just three months by following this sequence,” Éric shares.“ In one case, 60 % of the savings came from the quick wins alone, implemented in the first week.”
Level 2: Low-hanging fruit( weeks) Once quick wins are implemented and teams see tangible results, they’ re ready for optimisations requiring brief maintenance windows or minor code changes. Rightsizing instances address over-provisioning, where utilisation analysis often reveals 40-w60 % idle capacity.
“ We’ ve seen immediate savings of 20 % simply by switching from x86 to ARM-based Graviton2 processors,” Éric reports. Lambda memory optimisation requires testing but can produce dramatic results.“ Right-sizing Lambda memory has produced reductions of up to 85 %: one client saved $ 38,000 annually this way,” he says.
Level 3: Architectural changes( months) With momentum established, teams can tackle optimisations requiring substantial engineering effort. Serverless migration
KEY TAKEAWAY
Time-to-market improves dramatically. New features reach production 43 % faster through rapid provisioning and deployment. Staff can redirect 29 % more of their focus toward innovation rather than maintaining infrastructure. Security incidents decrease by 45 % through AWS’ s shared responsibility model and continuous updates
“We’ ve consistently found savings of 30 % or more through deeper analysis”
ÉRIC PINET, CEO, UNICORNE fintechmagazine. com 113