Cost analysis and allocation tools like CloudHealth, CloudCheckr, and Cloudability play an important role in many organizations’ FinOps journeys by assisting with keeping Finance informed, enabling forecasting, and driving accountability. These tools may also help provide visibility and direction around long-term purchases like Savings Plans and RIs. But, slicing and dicing your cloud costs is only the tip of the FinOps iceberg: 85%+ of your cloud savings potential lies beyond refining how you buy cloud services. You also need to optimize what you’re actually purchasing.

Hi everyone. My name is Heidi Carson and I’m a product manager here at Pepperdata. Today, I’m going to share a bit about how you can tame the cost of autoscaling your cloud clusters. As you may well be aware, the incredible flexibility and scalability of the public cloud make it an appealing environment for modern software development. But, that same flexibility and scalability can lead to runaway costs when the cloud doesn't scale the way you might expect.

Pepperdata has engineered a big data APM solution that empowers operators to automatically optimize the performance and capacity of their big data infrastructure while enabling developers to improve the performance of their applications.

Engineering job #1 is maximizing availability and performance. Engineering must proactively balance workload and service delivery with finding efficiencies and ensuring optimal cloud spend.The only way for engineers to tackle FinOps is to embed more awareness of capacity and cost into their operational processes. Watch and learn.