Challenges of Cloud Cost estimation and Performance Management optimization for Hybrid Cloud and On Prem environments

Companies are considering adopting cloud platforms because of the significant advantages they have in developing new Digital Transformation applications faster and decreasing costs with their pay-as-you-go model. It is becoming critically urgent now for many organizations to move workloads to the Cloud to handle spikes in the workload demand caused by coronavirus and requirements for IT to do more with less. But, migrating to the Cloud comes with two critical challenges.

The first challenge is selecting a cloud and DBMS platform capable of scaling well while meeting rapidly growing business needs. User populations are increasing rapidly because of digital transformation. Meanwhile, data volumes are exploding because of IoT, social media and other trends. With the wrong cloud or data platform it becomes impossible to meet goals for cost; for online performance; or for the timely delivery of business recommendations.

The second challenge is controlling resource allocation in the Cloud to meet business Service Level Goals (SLG) with the lowest cost. How can you create workload management and resource allocation rules that reflect workload seasonality? How can you optimize performance and continuously meet business SLGs most effectively?

IconThe “Trial and Error” approach of selecting and managing a Cloud platform for Data Warehouse and Big Data workloads is too risky: it can take far too long and cost much more than expected to find a workable solution.
  • Constantly growing and changing workloads affect performance
  • How to Select Appropriate Cloud for Data Warehouse and Big Data workloads
  • How to optimize performance of On Prem and in Cloud environments
  • How to reduce Risk of Performance Surprises

BEZ Talk with Thought Leaders in Modeling and Performance Prediction