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State of FinOps ’24: Top Priorities Shift to Reducing Waste and Managing Commitments

FinOps Foundation

Key Insight: With economic pressure increasing across the world in 2023, many organizations are leaning on their FinOps teams to help prioritize cloud optimizations. Sustainability teams have limited intersection with FinOps teams today, but that number is expected to increase substantially in the future.

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FOCUS Sandbox and sample data available now

FinOps Foundation

Key Insight: To support the adoption of FOCUS , the FinOps Foundation has augmented the Use Case Library with the introduction of the FOCUS Sandbox. The FinOps Open Cost and Usage Specification (FOCUS ) is an open-source technical specification for cloud cost and usage billing data. What is FOCUS? Why a FOCUS Sandbox?

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FOCUS 1.0 is Now Available. Practitioners and Clouds Continue Adoption.

FinOps Foundation

FOCUS is being adopted by end user FinOps Practitioners, leading cloud Infrastructure-as-a-Service (IaaS) providers, and FinOps tool vendors, who all benefit from removing complexity associated with cloud billing data normalization. Get trained on the Specification through the FinOps Certified FOCUS Analyst certification.

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Key MLOps processes (part 4): Serving and monitoring machine learning models

FinOps in Practice

The team can: Write all the code to set up a RESTful service, Implement all the necessary wrapper code around it, Collect everything in a Docker image, Eventually, spin up a container from this image somewhere, Scale it in some way, Organize metrics collection, Configure alerts, Set up rules for rolling out new model versions, and much more.

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How to debug and profile ML model training

FinOps in Practice

For instance, OptScale , a FinOps and MLOps open source platform, gives full transparency and a deep analysis of internal and external metrics to identify training issues. on GitHub → [link] The post How to debug and profile ML model training first appeared on FinOps in Practice.

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What are the main challenges of the MLOps process?

FinOps in Practice

For the convenience of the reader and at the same time for the sake of attention, we will divide it into the following four (plus one, never-ending) stages: Data Collection and Preparation; Model Training and Evaluation; Model Deployment; Monitoring and Management; Continuous Improvement. first appeared on FinOps in Practice.

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Rightsizing recommendations: get GCP costs down with Google Cloud optimization services

FinOps in Practice

Having access to rightsizing recommendations to consider can really help businesses leaders and FinOps teams to solve and improve their companies’ current processes and usage. It is based on system metrics which collect Cloud Monitoring service data over the previous 8 days. Rightsizing is often a huge challenge which companies face.

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