It's valuable to know where waste in your applications and infrastructure is occurring, and to have recommendations for how to reduce that waste—but finding waste isn't necessarily fixing the problem. Check out this conversation between Shashi Raina, AWS Partner Solution Architect, and Kirk Lewis, Pepperdata Senior Solution Architect, as they dispel the first myth of Apache Spark optimization: observability and monitoring.

There are several techniques and tricks when developers are tasked with optimizing their Apache Spark workloads, but most of them only fix a portion of the problem when it comes to price and performance. Watch this conversation between AWS Senior Partner Solution Architect Shashi Raina and Pepperdata Senior Solution Architect Kirk Lewis to understand the underlying myths of Apache Spark optimization, and how to ultimately fix the issue of wasted cloud resources and inflated costs.

Pepperdata has saved companies over $200M over the last decade by reclaiming application waste and increasing your hardware utilization to reduce costs in the cloud. It completely eliminates the need for manual tuning, applying recommendations, or changing application code: it's autonomous, real-time cost optimization.

Not every application has wasted capacity in it—or do they? Watch Ben Smith, VP Technical Operations at Extole, discuss how he discovered that there's around 30% of application waste within every running app, and how Extole went about saving that wasted capacity.