Best of FinOps — January 2026

1. 1
   Article

   CNCF·18w

   OpenCost: Reflecting on 2025 and looking ahead to 2026

   OpenCost, a CNCF incubating project for Kubernetes cost management, released 11 versions in 2025 with major features including Prometheus-optional operation, an AI-powered MCP server for natural language cost queries, and improved cloud provider support. The project expanded through mentorship programs that delivered integration testing, the MCP server, and KubeModel for Data Model 2.0. Looking ahead to 2026, priorities include completing KubeModel, adding AI usage costing features, and enhancing supply chain security.

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2. 2
   Video

   DesignCourse·18w

   Replacing a $500 Annual SaaS in 4 Hours with Claude 4.5

   A developer replaced a $492/year live chat SaaS subscription by building a custom solution in 4 hours using Claude Opus 4.5 through Cursor IDE. The new implementation cost $88 to develop, integrates directly with the existing admin panel, includes AI-powered responses via Gemini Flash with customizable knowledge base, and provides better user identification for logged-in members. The project demonstrates how AI coding assistants enable rapid development of custom alternatives to expensive SaaS tools, with plans to replace additional services like email marketing platforms.

   27

   6
3. 3
   Article

   Halodoc·16w

   Reducing Amazon EKS Compute Costs by 35%: Migrating Production Workloads from Graviton3 to Graviton4

   Halodoc migrated their Amazon EKS workloads from Graviton3 to Graviton4 processors, achieving 35% cost savings through a data-driven approach. The migration involved two-phase validation: hardware benchmarking with Sysbench showed 28% CPU throughput improvement and 64% memory bandwidth gains, while application-level testing with JMeter demonstrated lower latency and resource utilization. By combining the processor upgrade with strategic resource right-sizing (15% CPU and 10% memory reduction), they reduced node count by 40% and maintained performance while cutting costs. The zero-downtime migration used controlled node pool rebalancing, followed by a one-week stabilization period before applying resource optimizations.

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