To ensure optimal cloud resource utilization, I would implement a combination of auto-scaling policies based on demand forecasts, right-sizing instances to match workload requirements, and employing cost management tools to monitor and adjust resources. Regularly reviewing usage metrics and setting up alerts for underutilized or overutilized resources would also be key. This approach ensures efficiency, reduces waste, and maintains performance without unnecessary expenditure.

Capacity planning in a cloud environment involves analyzing historical usage data, understanding business growth trends, and forecasting future demands. I would leverage cloud monitoring tools to gather insights and use predictive analytics to anticipate needs. Collaborating with different teams to understand their requirements and aligning them with the cloud service provider's capabilities ensures that the infrastructure scales seamlessly to support business objectives.

In a previous role, we encountered a sudden spike in traffic that overwhelmed our cloud resources, leading to performance degradation. I quickly identified the bottleneck by analyzing cloud metrics and logs. Implementing auto-scaling rules and optimizing database queries resolved the immediate issue. Post-incident, I conducted a root cause analysis and adjusted our capacity thresholds to prevent recurrence, demonstrating the importance of proactive monitoring and flexible scaling strategies.

I am proficient with a range of tools and technologies for cloud capacity management, including AWS CloudWatch, Azure Monitor, and Google Cloud's operations suite for monitoring. For automation and orchestration, I've used Terraform and Ansible. Additionally, I leverage cost management tools like AWS Cost Explorer and Azure Cost Management to optimize spending. These tools enable effective monitoring, automation, and cost optimization in cloud environments.

Balancing cost and performance involves selecting the right mix of reserved, spot, and on-demand instances based on workload criticality and variability. Implementing tiered storage solutions and optimizing data transfer costs also play a role. Regularly reviewing and adjusting resource allocations based on performance metrics and cost reports ensures that we meet performance SLAs while staying within budget. This dynamic approach allows for efficient resource utilization without compromising on service quality.