Introduction au FinOps avec Google Cloud

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💻 + 🚀 + ☁ = 💸 Introduction au FinOps avec Google Cloud

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Julien Landuré Cloud Practice Leader GDG & DevFest Nantes Organizer GDE Cloud jlandure.dev @jlandure

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Back to the future

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5 stratégies de déploiement Rehost Replatform Refactor Rebuild Replace

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IaaS SaaS PaaS Servers VM instances Clusters Cluster management Serverless, autoscaling Google Cloud Platform products and services Compute Engine Kubernetes Engine Cloud Run Cloud Functions App Engine Compute Spectrum

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Proprietary + Confidential IaaS Pay for what they allocate PaaS Pay for what they use Payment models

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Ce qui existe en standard… “Pay-as-you-go” model

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VM World Virtual machine Kernel Dependencies Application Code Hardware + hypervisor Dedicated server Kernel Dependencies Application Code Hardware Container Kernel + Container Runtime Dependencies Application Code Hardware Deployment ~mins (sec) Portable Very Eﬃcient Deployment ~months Not portable Low utilization Deployment ~days (mins) Hypervisor speciﬁc Low isolation, Tied to OS

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Container World (Kubernetes) Virtual machine Kernel Dependencies Application Code Hardware + hypervisor Dedicated server Kernel Dependencies Application Code Hardware Container Kernel + Container Runtime Dependencies Application Code Hardware Deployment ~mins (sec) Portable Very Eﬃcient Deployment ~months Not portable Low utilization Deployment ~days (mins) Hypervisor speciﬁc Low isolation, Tied to OS Master Nodes

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Proprietary + Confidential Google Compute products are billed per-second

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Per VM max: ● 416 vCPUs, 12 TB of RAM, GPUs, TPUs ● Independently configurable, including disk! Start quickly, ~20 seconds to user code running Pre-built images, or create your own ● Debian, CentOS, CoreOS, Ubuntu, RHEL, SUSE ● Windows Server Datacenter: 2008, 2012 R2, 2016 , 2019 What is Compute Engine?

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Disk Persistent Disk ● Network based ● Configure size (to 64 TB) ● Disk or SSD ● Independent of VM ○ Global Snapshots ○ Multi-VM RO mount ● Larger disks == more throughput Local SSD ● Lowest latency ● 375 GB per disk (up to 8) ● Tied to VM lifecycle

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GCE Machine Types

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Custom Machine feature ● Flexible configurations ● Create a machine type with 1 vCPU and up to 96 vCPUs ● Extended Memory enables higher Mem:vCPU ratios ● Sizing recommendation // CREATE INSTANCE WITH 6 vCPUs and 5 GB MEMORY gcloud compute instances create my-vm --custom-cpu 6 --custom-memory 5 Config your own custom machine, with average 19% savings

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Preemptible / Spot VMs Short lived, low cost virtual machines. ● Can run up to 24 hours ● Might be preempted at any time with 30 seconds notification ● Much lower price (up to 80% cheaper) than regular instances ● Offers the same machine types and options as regular VM instances ● Best for running non-urgent fault-tolerant jobs or short-lived tasks, like genomics, media transcoding, etc.

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Managed instance groups (MIGs) ● Instance group can be resized ● Manager ensures all instances are RUNNING ● Typically used with autoscaler ● Can be single zone or regional ● Supports autohealing A collection of identical VM instances that you control as a single entity, using an instance template.

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Usage Level (% of month) % at which incremental is charged 0% - 25% 100% of base rate 25% - 50% 80% of base rate 50% - 75% 60% of base rate 75% - 100% 40% of base rate Up to 30% net discount for instances that run the entire month. Sustained use discounts

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Ce qui existe en standard… “Pay-as-you-use” model

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Serverless Deploy and scale applications fast and securely in a fully managed environment No Infra Management Auto-scaling

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Pay per use CPU / Memory / Requests 100ms Pay per use

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Cloud Run – Billable container instance time

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Ce qui existe en standard… Pour mesurer et comprendre

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Google Cloud Pricing Calculator Search for product you are interested in Estimate Instances cloud.google.com/products/calculator

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Billing tools help to budget and monitor usage Budgets Alerts Reports Quotas

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Ce qui existe en standard… Free tiers

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Free tier https://cloud.google.com/free

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Point d’étape

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FinOps https:/ /www.ﬁnops.org

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📈 Trends

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FinOps Principles by FinOps Foundation - FinOps Foundation under the ccby4.0 license

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🌐 Identiﬁed FinOps practitioners

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📝 Deﬁnition L'approche FinOps, contraction des termes de finance et d’opérations, vise au monitoring et à l’optimisation des coûts en matière de cloud computing. Il est question, dans le même esprit que la stratégie DevOps, d’encourager la coopération et l’assimilation des moyens IT par les métiers. De ce fait, les pratiques FinOps ajoutent une dimension financière dans la gestion des coûts du Cloud.

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DevOps ❌ a standard ❌ a certification ❌ a goal ✅ a culture ✅ a philosophy ✅ a journey

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1. Teams need to collaborate 2. Everyone takes ownership for their cloud usage 3. A centralized team drives FinOps 4. Reports should be accessible and timely 5. Decisions are driven by business value of cloud 6. Take advantage of the variable cost model of the cloud. 📌 Key principles in FinOps

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Cloud FinOps is an evolving cloud ﬁnancial management discipline and cultural practice that: to collaborate on data-driven spending decisions enables organizations to get maximum business value by helping engineering, ﬁnance and business teams FinOps.org FinOps Principles by FinOps Foundation - FinOps Foundation under the ccby4.0 license

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FinOps Principles by FinOps Foundation - FinOps Foundation under the ccby4.0 license

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💬 Ecosystem

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💰 25 Premier Members & 51 general members

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💪 Upskilling

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👤 FinOps Personas

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42 FinOps Principles by FinOps Foundation - FinOps Foundation under the ccby4.0 license 🎓 Training & Certiﬁcation

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43 💚 Community

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📆 Events

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💡 Capabilities Accelerate / State of DevOps Report

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⚙ Domain & Capabilities

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🚧 Tooling

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💡 Examples of measurement

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🤝 Adopt

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⚡ What is the diﬀerence between forecasted spend and actual spend?

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🎁 Percentage of commitment-based discounts that are estimated to go unused each month

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Comment l’appliquer au monde Google Cloud ?

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Des leviers disponibles Solutions de stockage Utiliser les différentes classes de stockage, designer le stockage Ressources préemptibles Utiliser la surcapacité de l'infrastructure Google Ressources orphelines / inutilisées Supprimer les ressources inutilisées (instances, disk, snapshots, IPs, etc.) Planiﬁcation Allumer / éteindre les ressources en fonction de leur plage d'utilisation Redimensionnement Choisir les bons types d’instances de l’utilisation réelle du système Engagement de ressources Engagement en matière de consommation de services & campagne globale de réduction Architecture Revoir l'architecture pour utiliser les services les plus efﬁcaces Optimisation BigQuery Analysis Optimisation des coûts des requêtes

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Oui d’accord et ?

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Exemple 1 : Firebase

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Exemple 2 : GKE

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Exemple 3 : CUD

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💡 Committed Use Discounts (CUDs) Spend-based CUDs Exemple: $50/hour spend in Cloud SQL (PgSQL) dans us-central1 Services pris en charge : Cloud SQL, Cloud Spanner, Cloud Run, Google Cloud VMware Engine, Google Kubernetes Engine (Mode Autopilot Resource-based CUDs Ex: 50 vCPU pour N2D dans us-central1 Services pris en charge : Compute Engine, Dataproc, Google Kubernetes Engine (Standard)

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Réserver un engagement de 3 ans pour économiser $164,160 sur ce projet

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Exemple 4 : Cloud Native Dev

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Développer en respectant les Cloud Patterns

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Conclusion

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● 👍 Un sujet tendance avec de vrais concepts ● 🔐 Démarche essentielle comme le SRE ou la Securité ● 💪 Une culture “FinOps” à diffuser ○ Autoscaling de 0 à N – par env (hors-prod / prod) ○ Respect de 12-Factors côté dev ○ Profiter au maximum du pricing model du Serverless ○ Choisir le bon outil pour faire la bonne chose ○ Observer, mesurer et maîtriser son architecture ○ Savoir quand se “commit” et sur quelle durée Les points à retenir

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🚀 Next

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💚 #GreenIT

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https:/ /greensoftware.foundation

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🙌 Merci ! jlandure.dev @jlandure Introduction au FinOps avec Google Cloud ☁