Azure Databricks has become very popular as a computing framework for big data. The rise of Apache Spark as a processing engine for everything from machine learning to streaming data is formidable. However, customers are finding unexpected costs eating into their cloud budget. Furthermore, lack of visibility to root cause and general inefficiency is costing organizations thousands, if not millions in operating their Azure Databricks environment.
Read this white paper to learn:
- Typical cost of ownership for Azure Databricks project costs
- Top contributors to cost overruns
- 6 money saving techniques to help avoid cost overruns
