This document discusses key challenges in modern data centers and how to overcome them. It addresses strategies like server consolidation, infrastructure optimization, and automation/orchestration. Server consolidation involves reducing physical servers by virtualizing workloads, but challenges include understanding application dependencies and ensuring performance after migration. Infrastructure optimization aims to utilize server capacity at 80-90% by adding critical workloads, while providing performance and security assurances. Automation and orchestration can help prevent "VM sprawl" by standardizing deployments and integrating platforms. The goal is to create an agile, dynamic datacenter that delivers on-demand, standardized IT services securely across environments.
1. Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation Birendra Gosai Date: September 13, 2011
12. Questions2 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
13. Virtualization maturity lifecycle 3 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
14. Server consolidation – definition and challenges An approach that makes efficient use of available compute resources Reduces the total # of physical servers Significant savings in hardware, facilities, operations and energy costs Key challenges: Gaining insight into application configuration, dependency, and capacity requirements Quick and accurate workload migrations in a multi-hypervisor environment Ensuring application performance after the workload migration The lack of virtualization expertise 4 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
15. Server consolidation – sample project plan Project description Implementation plan Tier 2/tier 3 departmental server consolidation project. Convert ~250 production and test physical servers onto about 40 hosts. ~2-3 person implementation team ~8 week timeframe 5 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation Note: The tasks and timelines will vary with the size and scope of the project, available resources, number and complexity of candidate applications, and other parameters.
16. Infrastructure optimization – definition and challenges Gain visibility and control Reduce costs and do more with fewer resources (thus reducing CapEx) Virtualize tier1 applications Increase % capacity utilization of virtual hosts Key Challenges: providing performance and SLA assurance to the business deploying and maintaining capacity on an automated basis securing access to the virtual environment ensuring business continuity in the event of a failure 6 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
17. Infrastructure optimization - sample project plan Project description Implementation plan Tier 1 infrastructure optimization project. Add ~10 critical production workloads onto about 40 hosts with existing workloads, resulting in 80-90% capacity utilization on the hosts ~3-4 person implementation team ~8 week timeframe 7 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation Note: The tasks and timelines will vary with the size and scope of the project, available resources, number and complexity of candidate applications, and other parameters.
18. Automation and orchestration – definition and challenges Arrest ‘VM sprawl’ Gain OpEx savings Help IT staff focus on strategic initiatives Key challenges Faster provisioning of standardized servers / applications that reduce customizations Process integration across heterogeneous platforms, applications and IT groups Reduce the MTTR for application problems Standardize configuration and ensure compliance 8 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
19. Automation & orchestration - sample project plan Project description Implementation plan Lab management system enables IT organizations to provide a web-based self-service reservation system so users can reserve and deploy customized server and virtual machine instances without administrator intervention. Other sample projects -production / staging environment mgmt, demos on demand capability, etc ~3-4 person implementation team ~6 week timeframe 9 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation Note: The tasks and timelines will vary with the size and scope of the project, available resources, number and complexity of candidate applications, and other parameters.
20. Dynamic datacenter – definition and challenges An agile IT infrastructure, based on an optimized and automated virtual infrastructure, that is: service oriented - delivering on-demand, standardized services to the business scalable - with the ability to span physical, virtual and cloud environments, and secure – providing security as a service to internal / external customers. Key challenges with successful server consolidation providing a comprehensive service interface that serves as a visual communication tool between IT and the business delivering a standard set of tiered-services (with well defined SLAs) that are consumable by business users service oriented automation and orchestration to span across heterogeneous physical, virtual and cloud environments, and ensuring security, compliance and QoS across hybrid environments. 10 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation
21. Dynamic datacenter - sample project plan Project description Implementation plan Support expanding business initiatives with agility. Deliver existing internal business services to partners. (e.g. billing, shipping, EMR, etc) ~4-6 person implementation team ~6 month timeframe Note: The tasks and timelines will vary with the size and scope of the project, available resources, number and complexity of candidate applications, and other parameters. 11 Key challenges in today’s dynamic data center – overcoming them and delivering agility, efficiency, and innovation