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Expert insights on cloud optimization, AI, and security -- Page 6
A FinOps framework for 50-500 person companies
Mid-market FinOps is the discipline of managing cloud spend at companies large enough that the bill is material (typically $30k--$1M per month) but too small to justify a dedicated FinOps team.
EKS cost optimization for mid-market: the controls that matter
EKS cost at mid-market scale is dominated by four levers: node-group sizing, pod-resource right-sizing, idle workload elimination, and spot/savings-plan mix.
Snowflake cost optimization: a mid-market practitioner's playbook
Snowflake cost at mid-market scale is dominated by warehouse compute (typically 70-85% of the bill), with storage and serverless features making up the rest.
CloudKeeper vs Vantage vs Apptio Cloudability vs in-house FinOps for mid-market
None of the three platforms is a clear winner for all mid-market companies. CloudKeeper is the strongest fit when you want managed savings on AWS and minimal internal time investment.
Case study: a 31% AWS bill reduction for a Series B SaaS company
A Series B SaaS company (anonymized; ~140 employees, AWS spend ~$112k/month at engagement start) brought us in for a 6-week FinOps engagement.
A 90-day FinOps onboarding plan for companies without a FinOps practitioner
A FinOps practice without a dedicated practitioner is a part-time responsibility for an existing engineer (typically platform engineering), structured around four practices that fit in 25-30% of one person's week.
Reserved Instances vs Savings Plans vs Spot for AI/ML workloads
For AI/ML workloads on AWS, the right commitment mix depends on workload type. Training: heavy Spot, no commitments. Steady inference: Compute Savings Plans or EC2 Instance Savings Plans.