How to manage FinOps for Cloud Financial Engineering & Cost Management

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Cost Challenges in Large Business
Large infrastructure: Large organizations have large on-demand infrastructures to run their multiple businesses. This leads to blowing up the cloud budgets without any certain clues.
Large teams: When working with very large teams where engineers are continuously bringing up resources to expand businesses but don’t have visibility of their cost spending.
No Accountability between teams: Lack of accountability in large teams & no ownership. Due to this, there is no visibility on cloud cost allocations.
Decentralized communication & No planning. Lack of planning & communication between finance, IT teams & business team. Teams should share the same language & processes so they can manage cloud spending while maintaining business continuity.
FinOps to the Rescue
FinOps is not a technology or Tool. FinOps is a cultural practice for managing cloud costs where engineering, finance, technology, and business teams collaborate & take ownership of their cloud usage supported by a central best-practices group

Bringing the FinOps culture into an organization enables it to get maximum business value, minimize cost & at the same time gain visibility and control over spending without compromising delivery velocity.

This way businesses can increase the usage of the cloud & minimize their bills.

FinOps: Principles & Practices

Principles:

Teams need to collaborate

  • This means engineering, finance, technology, and business teams should collaborate & break the silos between teams. This helps all to plan to cloud spending. Cost should be considered as a new efficiency metric. Define governance & control for cloud usage.
  • Everyone takes ownership of their cloud usage
  • Enable accountability between teams to manage their own cloud usage against the budget & gain full visibility at all levels.

A centralized team drives FinOps

  • Centralized FinOps practitioner who brings best practices & bridges all teams by enabling evidence-based decisions in new real-time to help optimize cloud cost & increase business value.
  • Reports should be accessible and timely
  • Continuous feedback & tracking to increase the visibility of cloud cost to determine under or over-provisioned resources.
  • Cost analysis to determine & understand why costs increased. Benchmarking in teams & industry to determine performance.

Practices:

  • Understanding cloud usage & cost
  • Performance tracking & benchmarking
  • Real-Time decision making
  • Cloud rate optimization
  • Cloud Usage optimization
  • Organizational alignment
  • Cloud Cost Management & Analysis
  • Planning & budgeting for business & technical needs.
  • Enable collaboration & Accountability in all teams
  • Rate Optimization & setup cost visibility
  • Set up timely reports & measurements of cost at each level.
  • Forecasting the cloud cost.
  • Realize the spending & drive decisions
  • Resource Optimization
  • Tooling & accelerate the management.

Core components for cost management & analysis

  • Accountability and enablement
  • Measurement and realization
  • Cost optimization
  • Planning and forecasting
  • Tools and accelerators

FinOps Tools on the globe

  • Harness
  • Viratana
  • Kubecost
  • Infracost
  • Cast-AI
  • Finout
  • Spot by Netapp

Written by 

Rahul Miglani is Vice President at Knoldus and heads the DevOps Practice. He is a DevOps evangelist with a keen focus to build deep relationships with senior technical individuals as well as pre-sales from customers all over the globe to enable them to be DevOps and cloud advocates and help them achieve their automation journey. He also acts as a technical liaison between customers, service engineering teams, and the DevOps community as a whole. Rahul works with customers with the goal of making them solid references on the Cloud container services platforms and also participates as a thought leader in the docker, Kubernetes, container, cloud, and DevOps community. His proficiency includes rich experience in highly optimized, highly available architectural decision-making with an inclination towards logging, monitoring, security, governance, and visualization.

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