Kubernetes adds undeniable benefits when it comes to flexibility and agility, but providing suboptimal resource specifications at the container or node level creates tremendous inefficiencies at scale, leaving resources stranded and utilization very low. Learn how the practice of Capacity Operations can augment DevOps and FinOps initiatives and enable greater agility for your operations organization.

The promise of autoscaling is that workloads receive exactly the cloud computational resources they require at any given time, and you only pay for the server resources you need, when you need them.

Monitoring big data cloud performance in the cloud with unified visibility across the entire ecosystem is critical to the success of any cloud deployment. In both the data center and cloud deployments, a proliferation of diverse performance solutions and microservice applications across infrastructures and networks can severely complicate cluster performance management. Hidden network dependencies and the complexity of managing many different solutions can negatively impact the application experience for both internal and external users.

Big data with cloud computing is a powerful combination that can transform your organization, process, and analyze your big data faster, and improve your products and business with actionable insights. Bringing your big data cluster to the cloud presents huge opportunities, but there are some challenges that need to be overcome. Is your organization really ready for the complexity of managing big data analytics in the cloud?

As corporate big data leaders look to improve data quality, turn around some of their big data projects in 2021, and optimize and improve application and cluster performance to meet business objectives, big data and analytics remain essential resources for companies to survive in a highly competitive big data environment. As you help your organization plan for the future and prepare for where big data is going in 2021, join presenter, Pepperdata Field Engineer, Kirk Lewis for this webinar.

At Pepperdata we have been analyzing many thousands of Spark jobs on many different clusters, on-prem and cloud production clusters running Spark across a variety of industries and applications, and even workload types. In this presentation, Alex and I are going to cover a very brief intro to Spark, and we'll discuss some of the common issues we have seen and the symptoms of those issues and also how you can address and overcome some issues like that without having to think too hard.

See how Autodesk reined in Amazon Web Services (AWS) costs with a comprehensive, cross-functional FinOps program. Densify enables successful cloud financial management at Autodesk by providing each team—Finance, Engineering, and application owners—reliable cloud optimization recommendations and trustworthy justification, creating cross-silo collaboration that delivers reliable applications at the right cost.