Azure Cost Optimization: 4-week Assessment

TCS - Azure

Optimize your Azure resources' consumption and maximize cost savings

Cloud Cost optimization is a key priority for Enterprises today that have adopted Public Cloud. Rapidly growing Cloud spend spiraling out of control, lack of visibility into the utilization of Cloud resources, and lack of guidance for optimization are some of the common concerns. TCS Azure Cost Optimization offering helps enterprises derive the maximum benefit out of their Azure investments and also helps them address their sustainability goals. In-depth analysis is performed on the utilization of Azure resources along with identifying the most optimal combination of cost optimization levers to derive maximum savings for a given Azure resource. Our TCS Cloud Governance and Optimization Platform (TCGOP) includes an intelligent and extensible rule engine to analyze Azure resources based on proven cost optimization practices and generates actionable recommendations.

DIFFERENTIATORS
  • Maximize cost savings through all possible cost optimization levers relevant on Azure such as Right Sizing, Service Tiers, Reservations, Usage Patterns etc.
  • End-to-end coverage of all types of resources offered on Azure: VMs, SQL DBs, Storage, App Service Plans and many more
  • Extensible to support future Azure resource type and pricing models
  • Customizable based on your Azure preference and standards
  • Targeted recommendations can be generated based on the environment and/or workload types
DELIVERABLES

    During the 4-week assessment, TCS will perform a cost optimization assessment on a defined scope of Azure resources. Cost optimization models on our platform will be fine-tuned based on your enterprise Azure standards and preferences if any. Cost optimization opportunities will be identified, and recommendations will be generated. Key deliverables include:
  1. Insights on current Azure utilization
  2. Recommendations to save cost on a resource-by-resource basis
  3. Guidance on the implementation of Cloud cost optimization
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