case study: hcl technologies on capacity planning for cloud and virtualized environments
DESCRIPTION
Learn from renowned author of “Cloud Capacity Management,” Navin Sabharwal (HCL Technologies) about the unique challenges of planning for capacity in hybrid cloud and virtualized environments. He reveals the capacity planning tools and processes needed to successfully plan for and predict the most cost-effective and reliable infrastructure needed in today’s cloud environments. For more information on DevOps solutions from CA Technologies, please visit: http://bit.ly/1wbjjqXTRANSCRIPT
![Page 1: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/1.jpg)
ca Opscenter
Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments
Navin Sabharwa
OCT60S #CAWorld
HCL Technologies Practice Head Public Cloud, Cloud Mgmt, Automation, Analytics, DevOps
![Page 2: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/2.jpg)
3
Objective
o The goal of the Capacity Management
process is to ensure that cost-
justifiable IT capacity in all areas of IT
always exists and is matched to the
current and future agreed needs of
the business, in a timely manner.
![Page 3: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/3.jpg)
4
Traditional Capacity Model Concerns
A pessimistic approach as there was focus on providing highest possible unit of capacity to support applications to run desirably in peak hours. In off peak hours, procured resources sat idle and were underutilized.
On the other hand, constrained resources would lead to overutilization of available resources leading to performance issues.
There was a lack of balance between demand and capacity because capacity requirements did not flow from business level to service level and then to component level.
This was a short term approach (incident based) with focus on component capacity.
A lack of proper planning resulted from an absence of an inter-process relationship for capacity planning and forecasting.
![Page 4: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/4.jpg)
5
New Age/Cloud Capacity Solution
The focus is on providing the smallest possible unit of capacity to support an application.
The smallest possible unit for capacity has reduced from a complete Hardware Stack to a Flexible Virtual Server which can be provisioned and de-commissioned based on need.
Virtualization in cloud computing allows for workload migration and optimum capacity utilization.
Cloud computing provides scalable infrastructure which can be provisioned in minutes as compared to weeks in traditional environments.
Ensure services meet their performance targets with cost economies and flexibility to the consumer to scale capacity.
![Page 5: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/5.jpg)
6
Delivery Process Interdependencies
![Page 6: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/6.jpg)
7
Support Process Interdependencies
![Page 7: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/7.jpg)
8
Iterative Capacity Management
Ongoing/Iterative capacity management procedures are required by service providers when existing service needs to be implemented and optimized for business and performance.
![Page 8: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/8.jpg)
9
Capacity Management Meeting Demand
Capacity must be able to intelligently tune itself according to criticalities that may arise due to business dynamics, seasonal and irregular variations.
![Page 9: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/9.jpg)
10
Capacity Aware Provisioning
![Page 10: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/10.jpg)
11
Capacity Demand Coupling
The ability of the cloud provider to anticipate the rise and fall in demand is the key to being a successful cloud provider.
In case of under capacity, the cloud consumers will not be able to provision resources or the performance SLAs will suffer; resulting in customer dissatisfaction and financial loss.
![Page 11: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/11.jpg)
12
Resource Reclamation Process
This process identifies workload inefficiencies and validates the same.
Identified underutilized resources are reclaimed.
Environment is monitored for further resource and cost optimization.
![Page 12: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/12.jpg)
13
Modeling and Forecasting
![Page 13: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/13.jpg)
14
Capacity Forecasting
In optimistic capacity forecasting, we would reserve more capacity for redundancy and other factors.
![Page 14: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/14.jpg)
15
Application Performance Simulation
![Page 15: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/15.jpg)
16
Workloads
![Page 16: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/16.jpg)
17
Hourly CPU Load Optimized by time of day
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Load
Hour
25% Savings
![Page 17: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/17.jpg)
18
RD
S D
B S
erv
ers
Days of the Month
1 3 5 7 9 11 13 15 17 19 21 23
75% Savings Daily CPU Load
Monthly Optimization Optimized during a month
![Page 18: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/18.jpg)
19
Worst Case Scenario – AWS CloudFront
http://www.reviewmylife.co.uk/blog/2011/05/19/amazon-cloudfront-and-s3-maximum-cost/
Author calculated maximum possible charge: – Used default limit of 1000 requests per second and 1000 megabits per second
– At the end of 30 days a maximum of 324TB of data could have been downloaded (theoretically)
– $42,000 per month for a single edge location
– CloudFront has 30 edge locations
![Page 19: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/19.jpg)
20
Stories And Lessons Learned
Anecdotal user experience – Personal website hacked by file sharers
– Received bill for $10,000
Note: AWS only charges for data out – All data transfer in is at $0.000 per GB
– Mitigates costs – if you don’t respond to requests, it doesn’t cost you anything
![Page 20: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/20.jpg)
21
CA Capacity Management Increase Efficiency, Assure Delivery and Reduce Costs With Confidence
DECISION SUPPORT FOR IT INVESTMENTS
Model growth Assess capacity efficiency
across IT Identify utilization impact
to business services
PR
EDIC
TIV
E A
NA
LYTI
CS
Anticipate potential issues before they impact the customer experience
Strategic Business Value
![Page 21: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/21.jpg)
22
What is CCM in real-life?
![Page 22: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/22.jpg)
23
Looking Closer…Increased Visibility
Capacity across IT
Capacity across facilities
Unified view
![Page 23: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/23.jpg)
24
Looking Closer…Increased Visibility
Capacity across IT
Capacity across facilities
Unified view
Monitor breaker used by VM clusters
Power issues visible before they present a problem
View IT Utilization on same clusters
Alarm = power exceeds capacity rating
![Page 24: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/24.jpg)
25
Looking Closer…Increased Visibility
Capacity across IT
Capacity across facilities
Unified view
Unproductive power = potential to reduce IT Equipment
Reduced IT equipment = increased efficiency & less power
Indication of productive and unproductive power usage
![Page 25: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/25.jpg)
26
Looking Closer…Improved Provisioning Capabilities
Capacity analysis - What
‘What-if’ analysis - Where
Deployment - How
![Page 26: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/26.jpg)
27
Looking Closer…Reduced CapEx and OpEx
Optimization of software
Optimization of hardware
Risk mitigation
![Page 27: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/27.jpg)
28
For More Information
To learn more about DevOps, please visit:
http://bit.ly/1wbjjqX
Insert appropriate screenshot and text overlay from following “More Info Graphics” slide here;
ensure it links to correct page DevOps
![Page 28: Case Study: HCL Technologies On Capacity Planning for Cloud and Virtualized Environments](https://reader034.vdocument.in/reader034/viewer/2022052623/559a42601a28abcd398b486b/html5/thumbnails/28.jpg)
29
For Informational Purposes Only
© 2014 CA. All rights reserved. All trademarks referenced herein belong to their respective companies.
This presentation provided at CA World 2014 is intended for information purposes only and does not form any type of warranty. Content provided in this presentation has not been reviewed for accuracy and is based on information provided by CA Partners and Customers.
Terms of this Presentation