Challenges
Challenges of cloud data platform selection and Dynamic Capacity Management of Hybrid Multi-Cloud Environment
- How to select appropriate cloud data platform for data warehouse workloads
- How to continuously support Service Level Goals (SLG) and control cost
- Security Implications
- How to continuously control performance and cost for all workloads on all platforms
- How to optimize DevOps decisions prior to new applications deployment
- How to optimize FinOps decisions in a Hybrid Multi-Cloud environment
The “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
- Increasing number of users, volume of data and new application implementations
- New sources of data
- How to Select Appropriate Cloud for Data Warehouse and Big Data workloads
- Organizations have many options providing different performance, scalability and cost
- How to optimize performance of On Prem and in Cloud environments
- Complexity
- How to discover anomalies and their Root Causes
- How to optimize Workload Management and proactively fix the problems
- How to select right Algorithms, Architecture, Hardware and Software configuration
- How to reduce risk of performance and financial surprises
- Complex interconnected and interdependent environments
- How to select right algorithms
- How to predict the impact of the expected workload and volume of data growth
- How to set the realistic expectations