webinar cloud computing and capacity management
DESCRIPTION
It looks as though all organizations will have some form of Cloud implementation over the next few years. This could be a mix of private and public Cloud, and for public cloud it could involve a variety of external providers. What you buy across the cloud could vary from simple Infrastructure As A Service (IaaS) such as processing power and disk storage through to full Software As A Service (SaaS) such as salesforce.com. What is without doubt, is that the range of environments you will have to manage will become ever more complex. What you can and should do in terms of capacity management will vary with the nature of your own implementation. Join us and find out what it will be realistic for the capacity manager to provide to the business in this complex world of interacting services, and how Metron will help you achieve it.TRANSCRIPT
04/10/2023 www.metron-athene.com 1
Metron AtheneCloud Computing and Capacity Management
Leading the way
in
Capacity and Performance Management
Charles Johnson – Principal Consultant
Agenda
• What is Cloud Computing?
• What is Capacity Management?
• Cloud Capacity Management Challenges
• Application Transaction Management
• Reporting and Forecasting
• Summary
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What is Cloud Computing?
To be considered a cloud . . .
• On demand self service
“A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service’s provider.”
• Resource Pooling
“The provider’s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand.”
• Rapid Elasticity
“Capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.”
What is Cloud Computing?
What is Cloud Computing?
Cloud Ownership (or Deployment Models)
• Public / External- Available to General Public- Owned by Organization selling Cloud Services
• e.g. Amazon or Google
• Private / Internal- Solely for organization- Onsite or hosted by 3rd Party
• Community- shared by several organizations and supports a specific community that has shared concerns , i.e.
Policy or Compliance- Managed either on or offsite by organizations or 3rd Party
• Hybrid- composition of two or more clouds (private, community, or public) that remain unique entities but
are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
What is Cloud Computing?
Service Models
• HaaS/IaaS – Hardware or Infrastructure as a Service
• PaaS – Platform as a Service
• SaaS – Software as a Service
• AaaS – Application as a Service
• MaaS – Monitoring as a Service
• Consumption-based / Subscription-based pricing
Popular Public Cloud Applications
What is Capacity Management?
Capacity Management
is Business Decision Support
• Reduces risk of demand exceeding available resources• Protects ROI• Every infrastructure change is a business decision• Every infrastructure change has a cost impact
Capacity Management
equals
Business Decisions
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What is Capacity Management?
Capacity Management is
• Strategic and Proactive• Assists in managing service
quality• Assists in managing cost
expenditures• Aligns business and IT• Match needs and cost during
growth
CAPACITY MANAGEMENT AND THE CLOUD
Cloud Capacity Management Challenges
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Forrester: Cloud needs Capacity Management
Capacity management is the top operational concern--it's also a mystery as the underlying capacity of virtualized servers in public clouds is largely unknown.
Cloud Capacity Management Challenges
• Capacity on Demand - Too Little, Too Much or Just Right?
• Automation and Control
• Protecting your ‘loved ones’
• Scalability - In / Up or Out?
• Old Habits – The Potential Risks
Cloud Capacity Management Challenges
Capacity on Demand
• Too Little (under capacity)- Application Sizing not performed- Controlled by limits- Lower usage costs- Service Levels affected – by how much?- High impact on business?
• Loss of service• SLA breach penalties
Cloud Capacity Management Challenges
Capacity on Demand
• Too Much (over capacity)
• Gartner – “most organizations overprovision their infrastructure by at least 100%”
• Unlimited access to resources• Service Levels unaffected• Costs – higher resource usage, software licensing• Impacts on other services
- Poor performance - Wasted resources (multi virtual CPU (vSMP) & single-threaded
applications)- VM Sprawl- Increased pressure to manage virtual resources
Cloud Capacity Management Challenges
Capacity on Demand
• Just Right?• Application Sizing performed• Efficient use of IaaS• Acceptable Service Levels
- continuous review and adjustment • Controlled by shares, limits and reservations• Continuous monitoring and tuning
- Configuration adjustments (CPU, Memory)- VM consolidation - Power off unused ESX hosts
• Right Balance- Find the equilibrium (service / cost)
Cloud Capacity Management Challenges
Find the right balance
Cloud Capacity Management Challenges
Automation and Control
• Rapid Elasticity - Guest Migration and Portability, Templates, Golden Host
• Resource Pools (limits, shares and reservations)• Load Balancing
- DRS (Automatic, Partial or Manual)• Affinity
- VM to VM or VM to Host- CPU
• Fine grained tweaking for performance gains – Single Threaded Apps
• Licensing
Cloud Capacity Management Challenges
Protecting your ‘loved ones’
• Critical business applications• Service Levels must be met• Highest Priority (shares, unlimited), CPU affinity• Must guarantee resources (reservations)• High Availability Clusters
• VMware - Fault Tolerance• Trade offs
- “just in case” capacity management could impact on other services
- Significant impact? Think about scaling out or up . . .
Cloud Capacity Management Challenges
Scalability – Out
For• Use existing hardware• Short lead time
- No wait for new equipment• No need for hardware upgrade?
- Costs are acceptable - SLA’s are met – but for how long?
Against• Older and slower equipment
- Not 64 bit, latest chipset technology- OK for the short term, but medium or long term?
• Additional Costs- Licensing- Extended hardware support > 3 years- Power consumption and space
Cloud Capacity Challenges
Scaling Up?
Cloud Capacity Management Challenges
Scalability – Up?
For• Upgrade to latest technology
- faster CPUs / more memory- 64 bit compatible, hyperthreading enabled - Consolidation (more workload)- Greener
• Efficiency Savings - All may outweigh scaling out to older systems
Against• Longer lead time
- Procurement of new equipment- Decommission old servers
• Costs- Hardware Upgrade- Licensing
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Cloud Capacity Management Challenges
• More things to measure – rapid response to new needs• Correct sizing – minimize ‘cloudbursts’• Compare performance against SLAs• Constant reassessment of provisioning requirements• Evaluate provider against ‘good practice’
Private Public
Cloud Capacity Management Challenges
Scalability –In?
• Spare capacity?- Sweat the assets by consolidating workloads
• Use periods of inactivity - Migrate workloads between hosts
• Turn off unused hosts- E.g. VMware DPM
• Cost savings - Reduce Power- Reduce licenses
Cloud Capacity Management Challenges
Old Habits – Potential Risks
• Gartner – “Through 2015, more than 70% of private cloud implementations will fail to deliver operational, energy and environmental efficiencies.”
• Infrastructure or application hugging- Silo mentality “what’s mine is mine”
• Lack of resource sharing- Through lack of trust and confidence
• “Just in case” capacity planning- Leads to over provisioning
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Application Transaction Management
Are service levels are being met?
Must understand the application transactions
end-to-end
Cloud Computing
and Business Application Transactions
Application Transaction Management
Cloud Aware!
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Physical
Hybrid
Virtual
Application Transaction Management
• Problem – Ensuring Reliable IT Services
• Solution – Dynamic Transaction Path Detection
Application Transaction Management
Network Firewall
Proxy
VirtualWeb
ServersDirectory
Server
Load Balancer
App Servers DB Server
Mainframe
Partner AppCloudWeb
Services
Msg. Broker
Firewall
VirtualWeb
Servers
App Servers
Partner App
Wire Xfer>$100K
Wire Xfer<$100K
Application Transaction Management
• Tracking transactions through all hops
Real User Experience
Application
Network
Infrastructure
Reporting and Forecasting
• Implement Automated Reporting & Alerting- What do we need?
• What recurrence?• Application and component
- RAG Thresholds – SLA information (capacity, availability, response time)
- Forecasting – Trending or Analytical Modeling or both?
Make effective use of information . . . . . . .
Reporting and Forecasting
Which servers are hosting which applications?
o Understanding the relationships
o Understanding the volumes
o Understanding the resource consumption
Accurately assigning resource usage
Summary
• Cloud Computing provides agility / elasticity to manage resources
• Capacity Management is critical to ensure Service Levels are met
• Capacity Management for Cloud environments is critical to ensure the efficient use of resources
• Application Transaction Management for Cloud applications is a must to become successful
Summary
• Apply same Capacity Management principles
- Gather the necessary information• Business – application sizing, usage periods, growth
numbers
• Service – what are the SLO’s, SLA’s, how do they impact on the business?
• Component – gather and store the data- configuration, performance, application
Summary
• Business runs on transactions, transactions run on IT
• Transactions are the missing link between
• Infrastructure
• Applications
• Business
• Fully track transactions to optimize capacity management
• Valuable business/IT data is created
• Unprecedented visibility is gained
• Enabling the use of this valuable data to drive better capacity
management decisions and predictions