In my point of view, the first step is to analyze usage patterns and right-size resources based on actual demand rather than assumptions. Ensure all the key stakeholders are made aware of 'out of control' costs and gain support on strategically controlling them Implement auto-scaling to adjust capacity dynamically and eliminate idle or underutilized instances. Leverage cost monitoring tools to track spending in real-time and set alerts for unexpected spikes. Adopt a reserved instance or savings plan strategy for predictable workloads to optimize long-term costs. Regularly review and refine configurations, ensuring teams follow governance policies to prevent unnecessary provisioning.

To control cloud costs and avoid over-provisioning, implement autoscaling to match resource usage with demand dynamically. Regularly monitor and analyze usage patterns to identify underutilized resources, leveraging rightsizing tools to optimize instance types. Adopt a cost-aware architecture by using reserved instances, spot instances, and serverless options where applicable. Set up budgeting alerts and enforce governance policies to prevent unnecessary spending. Continuously review and refine your cloud strategy to ensure efficiency without compromising performance.

Cloud vendors intentionally design pricing models to lure organizations into over-provisioning, creating unnecessary expenses. This is where we, as professionals, step in to stop the phishing scheme. I apply Little’s Law (L = λW), which states that system load (L) depends on request rate (λ) and processing time (W). By reducing W through efficient workload management and auto-scaling, I prevent idle resources. I also right-size instances, use reserved capacity, and implement real-time monitoring to ensure optimal provisioning. By controlling λ and W, I keep cloud costs lean, efficient, and free from vendor traps.

If I am understanding correct - this question is in context reference to ITOM in Servicenow ? If yes - 1)ServiceNow Cloud Management (CMP) to provision Cloud resources efficiently. We can define Policies for limitations to prevent over provisioning. 2)We need to use Auto Scaling - which provides us the facility to reduce kr increase the resources that we have been taking based on traffic. 3)Servicenow ITOM Visibility to track AWS instances and their utilization. We also have an amazing feature i.e AWS cost explorer which we can integrate for granular level. 4)We can leverage ITOM Orchestration to automate instance functioning in peak and non-peak hours.

Think of cloud costs like your electricity bill. If you leave the lights and appliances on all day, your bill skyrockets. But if you turn off what you’re not using and switch to energy-saving options, you cut costs without sacrificing comfort. Auto-scaling is like having a smart thermostat. When it’s hot, the AC kicks in, and when it cools down, it shuts off. This way, you're not wasting energy (or money). Similarly, auto-scaling in the cloud ensures you’re only using resources when demand is high. And just like checking your monthly expenses to spot unnecessary subscriptions, conducting cloud audits helps you find and remove unused or oversized resources, keeping your costs in check.

To avoid over-provisioning resources and control your cloud costs, it’s important to regularly assess your usage and adjust your resources to match actual demand

Cloud costs soaring signal over-provisioning gone wild—time to rein it in. Regular monitoring with analytics tools, like AWS CloudWatch, tracks usage, letting you trim fat on the fly. Auto-scaling kicks in to match resources to demand, no excess, no waste. Periodic audits sniff out idle or bloated assets, slashing what’s not needed, echoing Adolescence’s lean, focused intensity. It’s about precision—watch, scale, cut—to pay only for what works. Spiraling stops when oversight rules.

Utilize auto-scaling features offered by cloud providers to dynamically adjust resources based on demand, ensuring efficiency during peak and off-peak periods. For predictable workloads, consider using reserved instances or savings plans, which offer discounted rates for long-term commitments. Additionally, leverage tools like Azure Cost Management or AWS Cost Explorer to monitor resource usage, identify inefficiencies, and eliminate waste.

To avoid over-provisioning, assess usage patterns, implement auto-scaling and right-sizing, and adjust resources as needed. Use monitoring tools for tracking and alerts and collaborate with teams to optimize workloads. Regular evaluations and cost management tools help control expenses while maintaining performance and scalability.