David S. Linthicum
         David@bluemountainlabs.com
         Twitter: @DavidLinthicum




Capacity Management in a Cloud Computing World
Shameless Self Promotion Slide




                                    PODCAST ON CLOUD
BOOK ON           BLOG ON           COMPUTING WITH OVER
CLOUD COMPUTING   CLOUD COMPUTING   10,000 LISTENERS
FYI
• Slides will be on on
  www.slideshare.net/linthicum by tonight.
  – Slides are open source
• You can reach me with further questions at
  david@bluemountainlabs.com.
4 Myths of Capacity Management and
          Cloud Computing
• Myth 1: I don’t need
  capacity management
  when leveraging cloud
  computing.
• Myth 2: Clouds are
  “elastic.”
• Myth 3: Costs are
  always lower.
• Myth 4: Architecture
  and planning less
  important.
The Big Picture
Datacenters Emerge

1940


   1950                   Rise of Timesharing


          1960


                                                               Distributed
                   1970
                                                               Computing
                                                     Grids
                                  1980


                                            1990
                       Rise of the PC
                                                     2000
                             Rise of Client/Server

                                          Rise of the Web         2010
                                         Rise of “The Cloud”
Hardware/Software/Infrastructure On-Demand

2010


   2012                          IT On-Demand
  Rise of
  “Big Data” 2014
          Rise of
Rise of   “IT In-a-Box”
“Home                     2016
Clouds”                                                        Distributed
        Rise of                                                Service Sharing
        “Commodity                    2018
        Data Services”

            The “Big                              2020
            Migration” Begins    Rise of Shared
                                 Enterprise Business      2022
                                 Services

                                                                        2024
Where we are now with cloud computing.
Reflecting on the Hype!
• Gartner - Cloud computing revenue will soar faster than
  expected and will exceed $150 billion within five years.
• Forrester - Cloud-Based Email Is Often Cheaper Than
  On-Premise Email
• Vivek Kundra, CTO of Obama Government: “Growing
  adoption of cloud computing could improve data sharing
  and promote collaboration among federal, state and local
  governments.” E.g: fedbizopps.gov
• Merrill Lynch: “By 2011 the volume of cloud computing
  market opportunity would amount to $160bn, including
  $95bn in business and productivity apps (email, office,
  CRM, etc.) and $65bn in online advertising.”
• IDC: “Spending on IT cloud services will triple in the
  next 5 years, reaching $42 billion and capturing 25% of
  IT spending growth in 2012.”
                                                                                                                               9
                 Sources: http://www.infosysblogs.com/cloudcomputing/2009/08/the_cloud_computing_quotes.htm and http://www.mytestbox.com
Latest News
Emerging cloud computing trends.
• Moving from talking cloud to doing
  cloud.
• Government entering the cloud
  computing game now.
• Security continues to be a priority.
• Little or no expertise in corporate
  and government IT.
• Moving to IaaS and then PaaS.
• Leading with private clouds, but
  public clouds are the destination.
• Rise of “Big Data.”
Why the focus on the data?
Big Data Trends
• Data aggregation in
  the cloud for
  common analytics
  within verticals.
• Combining enterprise
  data into common
  data sets.
• Critical BI.
Where we are now with cloud computing.
NIST defines cloud computing as a set of characteristics, delivery
models, and deployment models

       5 Characteristics
 On-demand self-service

 Ubiquitous network access          3 Delivery Models
                               Software as a Service (SaaS)
 Resource pooling
                               Platform as a Service (PaaS)         4 Deployment Models
 Rapid elasticity
                                                                Private Cloud
                               Infrastructure as a Service
 Pay per use
                                (IaaS)
                                                                Community Cloud

                                                                Public Cloud

                                                                Hybrid Cloud
Delivery Models Morphing
• Software as a Service (SaaS)
    – Applications as a Service
    – Utilities as a Service
    – Connected and Disconnected
• Platform as a Service (PaaS)
    – Design as a Service
    – Process as a Service
    – Testing as a Service
• Infrastructure as a Service (IaaS)
    –   Database as a Service
    –   Management as a Service
    –   Middleware as a Service
    –   Integration as a Service
    –   Information as a Service

                  …and more.
New Stack Emerging
                                                          Testing-as-a-Service

                                                   Management/Governance-as-a-Service
                        Integration-as-a-Service




                                                               Application-as-a-Service
Security-as-a-Service




                                                             Process-as-a-Service




                                                                                          Platform-as-a-Service
                                                            Information-as-a-Service

                                                             Database-as-a-Service

                                                           Storage-as-a-Service

                                                    Infrastructure-as-a-Service
• Buzzword “cloud
  computing” is absorbed
  into computing.
• Focus on fit and
  function, and not the hype.
• Security moves to
  “centralized trust” models.
• Centralized data becomes a
  key strategic advantage.
• Mobile devices become
  more powerful, but thin.
• The rise of the “composite
  cloud.”
Cloud computing and capacity management.
4 Myths of Capacity Management and
          Cloud Computing
• Myth 1: I don’t need
  capacity management
  when leveraging cloud
  computing.
• Myth 2: Clouds are
  “elastic.”
• Myth 3: Costs are
  always lower.
• Myth 4: Architecture
  and planning less
  important.
No Surprise
So, What’s Changed?
• We can no longer assume that computing capacity is dedicated to
  a group of users or a group of processes.
   – Everything in a cloud computing environment is shared using some
     sort of multitenant model.
   – This makes capacity modeling and planning much more complex.
• Auto provisioning makes some aspects of capacity planning not
  as important since capacity can be allocated when needed.
   – However, considering that cost is a core driver for leveraging cloud
     computing, using capacity that’s not needed reduces the value of
     cloud computing.
• We now have the option to leverage cloud computing systems as
  needed to cost effectively provide temporary capacity.
   – Called “cloud bursting,” this type of architecture was difficult to cost
     justify until cloud computing provided us with a cheaper “public”
     option.
So, What’s the Same?
• What has not changed in the world of cloud computing
  is that it’s still computing.
   – Many in the emerging cloud computing space have a
     tendency to define cloud computing as the “new
     disruptive model” that will change the way we do
     computing from now on.
• While many would argue that cloud computing does
  not require as much planning as traditional
  systems, including capacity modeling and
  management, the more enterprises leverage
  clouds, the opposite is proving to be true.
   – Indeed, the core value of cloud computing is the effective
     and efficient use of resources.
CM/Cloud computing best practices.
Best Practice One
• Model capacity should consider the
  characteristics of a multi-tenant platform.
  – We’ve been here before with traditional multi-
    user, but the emerging cloud-based systems are a
    bit different animal.
  – Clouds typically offer up services or APIs to access
    very fine-grained and primitive resources (e.g.,
    storage).
  – APIs call back to physical resources, typically
    virtualized servers that many other tenants share.
Best Practice Two
• Make sure to account for distribution.
  – Cloud providers typically don’t centralize your
    processing in a single physical data center unless you
    specify that in the agreement (at an additional fee).
  – Thus, your request for 100 server instances to support
    processing may mean that some virtualized servers
    are allocated in a primary center, but dozens of others
    could be allocated to remote data centers, some
    perhaps out of the country.
Best Practice Three
• Focus on understanding, modeling, and
  monitoring services, not systems.
  – Most cloud computing implementations leverage core
    patterns of SOA, including the decomposition and use
    of services to create and recreate solutions.
  – Thus, when creating a capacity plan where cloud
    computing systems are in play, the most productive
    approach is to focus on the services (APIs to the
    resources), and how they behave under dynamic
    loading versus modeling a system holistically.
Centralized Monitoring Systems
   Become More Important
• Focus on the reorganization and
  outplacement of data.
• Focus on PaaS, and service
  companies that are good at PaaS.
• Focus on centralized trust,
  including moving to identity
  management models.
• SOA patterns and technology find
  new value in the cloud.
• Continued focus on mobile
  computing.
• Home clouds (e.g., iCloud) create a
  new track of application and
  appliance development.
• Rise of the “cloud aggregator.”
Q&A

Capacity Management in a Cloud Computing World

  • 1.
    David S. Linthicum David@bluemountainlabs.com Twitter: @DavidLinthicum Capacity Management in a Cloud Computing World
  • 2.
    Shameless Self PromotionSlide PODCAST ON CLOUD BOOK ON BLOG ON COMPUTING WITH OVER CLOUD COMPUTING CLOUD COMPUTING 10,000 LISTENERS
  • 3.
    FYI • Slides willbe on on www.slideshare.net/linthicum by tonight. – Slides are open source • You can reach me with further questions at david@bluemountainlabs.com.
  • 4.
    4 Myths ofCapacity Management and Cloud Computing • Myth 1: I don’t need capacity management when leveraging cloud computing. • Myth 2: Clouds are “elastic.” • Myth 3: Costs are always lower. • Myth 4: Architecture and planning less important.
  • 5.
  • 6.
    Datacenters Emerge 1940 1950 Rise of Timesharing 1960 Distributed 1970 Computing Grids 1980 1990 Rise of the PC 2000 Rise of Client/Server Rise of the Web 2010 Rise of “The Cloud”
  • 7.
    Hardware/Software/Infrastructure On-Demand 2010 2012 IT On-Demand Rise of “Big Data” 2014 Rise of Rise of “IT In-a-Box” “Home 2016 Clouds” Distributed Rise of Service Sharing “Commodity 2018 Data Services” The “Big 2020 Migration” Begins Rise of Shared Enterprise Business 2022 Services 2024
  • 8.
    Where we arenow with cloud computing.
  • 9.
    Reflecting on theHype! • Gartner - Cloud computing revenue will soar faster than expected and will exceed $150 billion within five years. • Forrester - Cloud-Based Email Is Often Cheaper Than On-Premise Email • Vivek Kundra, CTO of Obama Government: “Growing adoption of cloud computing could improve data sharing and promote collaboration among federal, state and local governments.” E.g: fedbizopps.gov • Merrill Lynch: “By 2011 the volume of cloud computing market opportunity would amount to $160bn, including $95bn in business and productivity apps (email, office, CRM, etc.) and $65bn in online advertising.” • IDC: “Spending on IT cloud services will triple in the next 5 years, reaching $42 billion and capturing 25% of IT spending growth in 2012.” 9 Sources: http://www.infosysblogs.com/cloudcomputing/2009/08/the_cloud_computing_quotes.htm and http://www.mytestbox.com
  • 10.
  • 13.
  • 14.
    • Moving fromtalking cloud to doing cloud. • Government entering the cloud computing game now. • Security continues to be a priority. • Little or no expertise in corporate and government IT. • Moving to IaaS and then PaaS. • Leading with private clouds, but public clouds are the destination. • Rise of “Big Data.”
  • 15.
    Why the focuson the data?
  • 16.
    Big Data Trends •Data aggregation in the cloud for common analytics within verticals. • Combining enterprise data into common data sets. • Critical BI.
  • 17.
    Where we arenow with cloud computing.
  • 18.
    NIST defines cloudcomputing as a set of characteristics, delivery models, and deployment models 5 Characteristics  On-demand self-service  Ubiquitous network access 3 Delivery Models  Software as a Service (SaaS)  Resource pooling  Platform as a Service (PaaS) 4 Deployment Models  Rapid elasticity  Private Cloud  Infrastructure as a Service  Pay per use (IaaS)  Community Cloud  Public Cloud  Hybrid Cloud
  • 19.
    Delivery Models Morphing •Software as a Service (SaaS) – Applications as a Service – Utilities as a Service – Connected and Disconnected • Platform as a Service (PaaS) – Design as a Service – Process as a Service – Testing as a Service • Infrastructure as a Service (IaaS) – Database as a Service – Management as a Service – Middleware as a Service – Integration as a Service – Information as a Service …and more.
  • 20.
    New Stack Emerging Testing-as-a-Service Management/Governance-as-a-Service Integration-as-a-Service Application-as-a-Service Security-as-a-Service Process-as-a-Service Platform-as-a-Service Information-as-a-Service Database-as-a-Service Storage-as-a-Service Infrastructure-as-a-Service
  • 22.
    • Buzzword “cloud computing” is absorbed into computing. • Focus on fit and function, and not the hype. • Security moves to “centralized trust” models. • Centralized data becomes a key strategic advantage. • Mobile devices become more powerful, but thin. • The rise of the “composite cloud.”
  • 23.
    Cloud computing andcapacity management.
  • 24.
    4 Myths ofCapacity Management and Cloud Computing • Myth 1: I don’t need capacity management when leveraging cloud computing. • Myth 2: Clouds are “elastic.” • Myth 3: Costs are always lower. • Myth 4: Architecture and planning less important.
  • 25.
  • 26.
    So, What’s Changed? •We can no longer assume that computing capacity is dedicated to a group of users or a group of processes. – Everything in a cloud computing environment is shared using some sort of multitenant model. – This makes capacity modeling and planning much more complex. • Auto provisioning makes some aspects of capacity planning not as important since capacity can be allocated when needed. – However, considering that cost is a core driver for leveraging cloud computing, using capacity that’s not needed reduces the value of cloud computing. • We now have the option to leverage cloud computing systems as needed to cost effectively provide temporary capacity. – Called “cloud bursting,” this type of architecture was difficult to cost justify until cloud computing provided us with a cheaper “public” option.
  • 27.
    So, What’s theSame? • What has not changed in the world of cloud computing is that it’s still computing. – Many in the emerging cloud computing space have a tendency to define cloud computing as the “new disruptive model” that will change the way we do computing from now on. • While many would argue that cloud computing does not require as much planning as traditional systems, including capacity modeling and management, the more enterprises leverage clouds, the opposite is proving to be true. – Indeed, the core value of cloud computing is the effective and efficient use of resources.
  • 28.
  • 29.
    Best Practice One •Model capacity should consider the characteristics of a multi-tenant platform. – We’ve been here before with traditional multi- user, but the emerging cloud-based systems are a bit different animal. – Clouds typically offer up services or APIs to access very fine-grained and primitive resources (e.g., storage). – APIs call back to physical resources, typically virtualized servers that many other tenants share.
  • 30.
    Best Practice Two •Make sure to account for distribution. – Cloud providers typically don’t centralize your processing in a single physical data center unless you specify that in the agreement (at an additional fee). – Thus, your request for 100 server instances to support processing may mean that some virtualized servers are allocated in a primary center, but dozens of others could be allocated to remote data centers, some perhaps out of the country.
  • 31.
    Best Practice Three •Focus on understanding, modeling, and monitoring services, not systems. – Most cloud computing implementations leverage core patterns of SOA, including the decomposition and use of services to create and recreate solutions. – Thus, when creating a capacity plan where cloud computing systems are in play, the most productive approach is to focus on the services (APIs to the resources), and how they behave under dynamic loading versus modeling a system holistically.
  • 32.
    Centralized Monitoring Systems Become More Important
  • 33.
    • Focus onthe reorganization and outplacement of data. • Focus on PaaS, and service companies that are good at PaaS. • Focus on centralized trust, including moving to identity management models. • SOA patterns and technology find new value in the cloud. • Continued focus on mobile computing. • Home clouds (e.g., iCloud) create a new track of application and appliance development. • Rise of the “cloud aggregator.”
  • 34.

Editor's Notes

  • #3 Thought leadership:Most read blog … Most listened to Podcast (10,000+ listeners) …