Is capacity planning still relevant in hybrid and multi-cloud setups? With autoscaling and FinOps in place, how are teams actually handling right sizing forecasting, cost control, and risk today?

Thank you for your detailed response! I completely agree that capacity planning remains crucial, especially given the financial and operational risks you mentioned.<br>As our enterprise is beginning to invest in capacity planning for our hybrid infrastructure, I’d love to hear more about your practical experience:<br>1. Are there specific tools, platforms, or methodologies you recommend for effective capacity planning in hybrid and multi-cloud environments?<br>2. How do you integrate capacity planning with autoscaling and FinOps practices?<br>3. Any lessons learned or best practices you could share for forecasting, right-sizing, and cost control?<br>Your insights would be incredibly helpful as we shape our approach. Thanks again!

There are many Application Resource Management tools that can help to optimize performance and costs across hybrid and multi-cloud environments. These tools also help with the FinOps side of governance. While there are many options, one of the tools I have seen widely used is Turbonomic.<br><br>These ARM tools/platform provide capabilities to monitor resource utilization in real-time that can be used for automatic adjustment of resources. Now, there are mission-critical platforms where companies are usually more careful to make sure there is a human-in-the loop approach as opposed to less critical apps that greatly benefit from a fully automated approach.

Thank you for your thoughtful response! I appreciate your emphasis on the increased complexity and the importance of governance and executive involvement in capacity planning for hybrid and multi-cloud environments.<br>As our organization is starting to formalize our capacity planning and governance processes, I’m interested in learning more about how your team approaches this:<br> • What tools, platforms, or frameworks do you use to manage capacity planning, reservations, and savings plans across hybrid and multi-cloud environments?<br> • How do you ensure effective tagging, monthly reviews, and renegotiations with cloud providers?<br> • Are there any best practices or lessons learned you can share regarding executive engagement and decision-making for cost control and risk mitigation?<br>Your insights would be extremely valuable as we build out our strategy. Thank you again for sharing your expertise!

As our cloud landscape matured, we realized that capacity planning and cost governance in a hybrid and multi‑cloud environment require far more than tools alone, they require discipline, transparency, and leadership ownership. Below is how we structured our approach and what has worked well for us.<br><br>1. Our Tooling Approach: Keep It Simple, Keep It Ours<br>Rather than investing in expensive third‑party FinOps platforms, we chose to build a lean governance model using tools we already mastered internally:<br>- Monthly CSP invoices are ingested into a SQL database<br>- From there, we surface all relevant data through a Power BI report<br>- Unrecognized or untagged resource groups are automatically flagged<br>- A Copilot agent reaches out to the resource owners and prompts them to complete the missing metadata<br><br>This approach keeps cost under control and gives us maximum flexibility. We evaluated multiple commercial FinOps suites, but found the ROI unconvincing for our use case, licensing costs were high, while our internal toolchain was more than capable.<br><br>2. Our Monthly Governance Rhythm<br>Each first Friday of the month, we hold a dedicated cost and capacity meeting involving:<br>- Our FinOps engineer<br>- Our Infrastructure team lead<br>- Myself (Director)<br><br>During this session, we cover:<br>- Newly created resources<br>- Resource groups showing rapid growth<br>- Status updates on previously requested actions<br>- Trends that pose future capacity or budget risks<br><br>This ensures that cloud governance is a continuous process, not an annual afterthought.<br><br>3. Executive Insight and Decision-Making<br>I summarize the monthly highlights and escalate them to the IT leadership team. This ensures that:<br>- Costs and risks remain visible at the highest level<br>- Decisions involving commitments (e.g., reservations, savings plans, architectural adjustments) are made with full context<br>- Cloud governance becomes a strategic competency, not a technical silo<br><br>Executive engagement has been essential in reducing surprises and enforcing accountability across teams.<br><br>4. Best Practices and Lessons Learned<br>Some of the most valuable things we’ve learned:<br>- Strong Naming Convention: A consistent naming convention is non‑negotiable. It is the foundation of tagging, ownership tracking, chargeback, and lifecycle management.<br>- Mandatory Azure Cost Calculator Use: Any new workload must be validated through the Azure calculator before deployment. This eliminates surprises and prevents “accidental architecture.”<br>- Monthly Follow-Up Is Crucial: Cloud environments change constantly. You cannot “trust” that everyone will automatically follow the rules, audit and follow-up are needed every month.<br>- Savings Plans Are Very Effective: For organizations with consistent consumption patterns, savings plans deliver strong value.<br>- Be Cautious with Reservations: Reservations can be attractive, but only when you are truly confident in your long‑term workload stability. We avoid locking in too early.<br><br>Closing Thoughts<br>Building a mature capacity planning and governance model doesn’t require complex tooling. It requires:<br>- Clear processes<br>- Consistent accountability<br>- A rhythm of monthly governance<br>- Executive visibility<br>- A culture that treats cloud cost as a strategic asset, not a technical byproduct<br><br>This approach has allowed us to maintain tight control over cost and capacity while giving our teams the agility they need to innovate. We have a total spend between 1 and 1,5 milion/year on the cloud.

Thanks so much for your detailed response! You’ve highlighted some great points about how capacity planning is evolving in the cloud, especially with the focus on availability zones, cost optimization, and disaster recovery. That’s really helpful.<br><br>I’m curious how these practices translate to on-premises data centers or hybrid environments, since a lot of organizations (ours included) are still running a mix of both. I have a couple of follow-up questions for the group:<br><br>Application Right Sizing & Scaling:<br>For on-prem or hybrid setups, how are teams handling application right sizing? Is there a standard approach for creating scaling plans—do you rely on performance testing before release to set your metrics, or is it more reactive? Any tools or frameworks you’ve found useful here?<br><br>Hybrid/DC Right Sizing:<br>For those using platforms like OpenShift, VMware, or Kubernetes in a hybrid model, how do you approach right sizing in the data center? Are there tools that help bridge the gap between on-prem and cloud capacity planning?<br><br>Would love to hear about any real-world experiences, tools, or best practices that have worked for others.