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NETE4631 Managing the Cloud and Capacity Planning. Lecture Notes #8. Lecture Outline. Managing the cloud Administrating the cloud Managing responsibilities Lifecycle management Emerging cloud management standards Capacity Planning Steps for capacity planner Scenario Load testing
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NETE4631Managing the Cloud and Capacity Planning Lecture Notes #8
Lecture Outline • Managing the cloud • Administrating the cloud • Managing responsibilities • Lifecycle management • Emerging cloud management standards • Capacity Planning • Steps for capacity planner • Scenario • Load testing • Resource ceiling • Scaling
Administrating the Cloud • Network management systems are often described as FCAPS (ISO) • Fault/ Configuration/ Accounting/ Performance/ Security • Fundamental features • Administrating/ Configuring / Provisioning of resources, Enforcing security policy, monitoring operations, Optimizing performance, Policy management, Performance maintenance, etc.
Administrating the Cloud (2) • Network management framework tools • BMC ProactiveNet Performance Management • HP OpenView/ HP manager products • IBM Tivoli Service Automation Manager • CA (Computer Associates) Unicenter • Microsoft System Center
Management Responsibilities • What is different from traditional network management? • Cloudy characteristics • Billing is on a pay-as-you-go basis. • The management service is extremely scalable. • The management service is ubiquitous. • Communication between the cloud and other systems uses cloud networking standards. • The type of Cloud affects which tools for monitoring • Level of controlling aspects of operations – IaaS>PaaS>SaaS
What to be Monitored for Cloud? • End-users services such as HTTP, TCP, POP3/ SMTP, etc. • Browser performance on the client • Application monitoring in the cloud such as Apache, MySQL, and so on • Cloud infrastructure monitoring of services such as Amazon Web Services • Machine instance monitoring where the service measures processor utilization, memory usage, disk consumption, queue lengths, etc.
Lifecycle Management • Six different stages in the lifecycle • The definition of the services as a template for creating instances • Client interactions with the service, usually through an SLA (Service Level Agreement) • The deployment of an instance to the cloud and the runtime management of instances • The definition of the attributes of the service while in operation and performance of modification of properties • Management of the operation of instance and routine maintenance • Retirement of service
Cloud Management Products • Very young industry • List of products -> Chapter 11 of Course Book • Core management features • Support of different cloud types • Creation and provisioning of different types of cloud resources such as machine instances, storage, or staged applications • Performance reporting including availability and uptime, response time, resource quota usage • The creation of dashboards that can be customized for a particular client’s needs
Example - CloudKick • www.cloudclick.com
Emerging Cloud Management Standards • Distributes Management Task Force (DMTF) • An industry organization that develops industry system management standards for platform interoperability • Create a working group to help develop interoperability standards for managing transactions between and in public, private, and hybrid cloud systems • Describing resource management and security protocols, packaging methods and network management technologies.
Emerging Cloud Management Standards (2) • Cloud Commons • Initiated by CA and donates to Software Engineering Institute (SEI), CMU, USA • Establishes cloud-based metrics for • file creation and deletion/ Email availability/ console response time/ storage and database benchmark • Using dashboard called CloudSensor to monitor cloud-based services in real time
Capacity Planning • Capacity Planning • Match demand to available resources • Identify critical resources that has resource ceiling and add more resources to remove the bottleneck of higher demands • Not focus on performance tuning or optimization
Steps for Capacity Planner • Iterative process with the following steps • Examine what systems are in place (characteristics) • Measuring their workload for the different resources in the system: CPU, RAM, disk, network and so forth • Load the system until it is overloaded, determine when it breaks, and specify what is required to maintain acceptable performance/ what factors are responsible for the failure (resource ceiling) • Determining usage pattern & predict future demand • Add or tear down resources to meet demand
Scenario • Example (LAMP) • Capacity planner works with a system that has a website on Apache • Also, a site has been processing database transactions (MySQL) • Application-level metrics • Page views (hits/s) • Transactions (trans/s)
Scenario (2) • System-level metrics • What each system is capable of • How resources of such a system affect system-level performance • Example • A machine instance (physical or virtual) • CPU • Memory (RAM) • Disk • Network Connectivity • Measured by tools such as sar command/ Microsoft task manager/ RRDTool for Linux
Load Testing • Load testing seeks to answer the following question. • What is the maximum load that my current system can support? • Which resources represent the bottleneck in the current system that limits the system’s performance? (resource ceiling) • Can I alter the configuration of my server in order to increase capacity? • How does this server’s performance relate to your other servers that might have different characteristics. • Tools • HTTPerf, Siege, Autobench, IBM Rational Performance Tester, HP LodeRunner, Jmeter, OpenSTA
Network Capacity • Three aspects to assessing network capacity • Network traffic to and from the network interface at the server (physical or virtual) • system utilities (I/O), Network monitor (traffic) • Network traffic from the cloud to the network interface • Tools such as those from Apparel Networks • Network traffic from the cloud through your ISP to your local network interface • The connection from the backbone to your computer (through ISP)
Scaling • Scale vertically (scale up) • Add resources to a system to make it powerful • A virtual system can run more virtual machines (operating system instance), more RAM, faster compute times • Example – rendering or memory-limited apps • Scale horizontally (scale out) • Add more nodes to remove I/O bottleneck • Easy to pull resources and partition • Example – web server apps
Scaling Comparison • Cost • Scale up pays more than scale out. • Maintenance • Scale out increases the number of systems you must manage. • Communication • Scale out increases the number of communication between systems. • Scale out introduces additional latency to your system.
References • Chapter 6, 11 of Course Book: Cloud Computing Bible, 2011, Wiley Publishing Inc.