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Monitoring Cloud
  Applications
             Amit Pathak




                           1
Agenda
                              
 ontext

                              
 hallenges

                              
 onitoring-as-a-Service

                              
 ey Highlights

                          2
                              
 enefits
Context
 Are agreed service levels met?

 Overall how many applications are healthy vs non-healthy?

 Is the health getting worse over time?

 Are the business functions being performed as expected?

 Do you have capacity within applications?




                                                             3
Context
 Cloud Complexity

  Scale and diversity of the infrastructure

    - Servers, network devices, storages, etc.

    - Hundreds, even thousands of machines

  Massive number of user applications

    - Catastrophic consequence of failure / security breach /
      performance degradation



                                                                4
Context
 Resource utilization is tightly coupled with cost incurred by
 customers

 Monitoring is indispensable

  Availability, failure detection

  Performance, provisioning

  Security, anomaly detection

  Application-level monitoring


                                                                 5
Challenges - Overview
 Inherits performance monitoring challenges of virtualized world

 End user response time – a primary metric

 Mechanism to collect data from various sources

 Managing agents

 Monitor, identify & heal bottlenecks




                                                               6
Challenges - Overview
  Detect performance degradation:

 Single malfunctioning application on a guest has a potential to
  degrade performance of host and other resources

 Resource contention among applications executing on VMs may
  hamper performance

 Virtual machines not configured with sufficient resource to
  handle workload




                                                                    7
Challenges – A Closer Look




Source: Monitis
                             8
Challenges – A Closer Look


                           System
                          Challenges

User          Cloud
Challenges   Monitoring

                           Network
                          Challenges




                                       9
Challenges – System Level
Efficient Scalability:

  Monitor tasks – tens of thousands

  Cost effective - minimize resource usage

 Facilitating service




                                             10
Challenges – System Level
Efficient Scalability:

  Massive Scale

 Monitor inherent large scale tasks

 Large number of users
           - Infrastructure monitoring
           - Application monitoring

 Monitor tasks with high cost e.g. Resources with high consumption




                                                              11
Challenges – System Level
Monitoring QoS Assurance:

  SLA management

  Application security

 Federated identity of cloud applications

 Secured integration of cloud apps with on-premise apps

  Multi-tenant environment

 Authorization & access control

  Monitor contention between monitoring tasks
                                                           12
Challenges – User Level
  Continuous violation detection

 Need of different detection model - Dynamically add/remove
  servers based on performance

 Achieve efficiency at the same time




      Short-term burst             Persistent violation




                                                               13
Challenges – Network Level
  Resource-aware monitoring fabric

 Monitoring the functioning of both systems and applications running
  on large-scale distributed systems

 Continuous collecting detailed attribute values
      - A large number of nodes
      - A large number of attributes

 Overhead increases quickly as the system, application and
  monitoring tasks scales up


                                                               14
Performance Monitoring
 Understand performance of virtual infrastructure – outside in
 approach

 Troubleshoot bottlenecks

 Plan future needs




                                                                 15
Key Parameters To Monitor
 CPU

 Memory

 Network

 Disk




                            16
CPU
  CPU saturated?

   High Ready time

 Problematic if it is sustained for high periods

  Possible contention for CPU resources among VMs

 Workload Variability?

 Resource limits on VMs?

 Actual over commitment?

  High SwapWait time
                                                    17
Memory
Swap in rate

Swap out rate

Swap used




                18
Disk
  What should I look for to figure out if disk is an issue?

 IOPs?

 Bandwidth (read/write)?

 Latencies?




                                                              19
Network
  What should I look for to figure out if network is an issue?

 Packate rate?

 Bandwidth (read/write)?

 NIC status?




                                                                 20
Monitoring-as-a-Service




                          21
Monitoring-as-a-Service
  Similar to other cloud services

 Database service (e.g. SimpleDB, Datastore)

 Storage service (e.g. S3)

 Application service (e.g. AppEngine)




                                                22
High Level Solution
        Applications,      Events & Alerts
        Server – CPU,      Customization
        memory, disk IO




         Packate rate,     Gather data from
         bandwidth, NICs   various resources
                           Trend analysis




                                               23
Monitoring-as-a-Service
External monitoring   Web server, file server, mail server, VOIP

Server monitoring     CPU, memory, processes, storage

Network monitoring    Http, SSH, SNMP, discovery

Transaction           Multi-step apps, workflows
monitoring

Cloud monitoring      Track running instances, auto-deploy,
                      usage
Web Traffic monitor   Visitor, page views




                                                                   24
Key Highlights
 Scale dynamically

 Have minimum (or no) impact on the monitored infrastructure

 Should be portable and has to be light weight

 Easy feature customization. Not all metrics will need to be
 monitored in the cloud for everyone

 Heavy network based monitoring tools may not be a good fit




                                                               25
Key Highlights
  Comprehensive monitoring of resource performance and
  availability

 Applications, databases, middleware and web servers

  Provide innovative ideas to fetch data as business need grows

 Dashboard, views, reports

  Co-relate information from different sources

  Trends analysis

  Predict bottlenecks
                                                              26
Benefits
 End-to-end support

 Easy to use & maintain

 Reliable service

 Feature customization

 Cost effective




                          27
Summary
 Cloud is complex; monitoring needs are indispensable

 End user response time is primary focus

 Cloud services must be treated differently to on-premise
  software when it comes to systems monitoring

 Do not rely on vendors completely. If SLAs are serious,
  maintain your own logs

 Existing tools are good but use programmatic APIs for specific
  needs

                                                                   28
Thank You



            29
References
•   http://developer.vmware.com

•   http://www.cc.gatech.edu/

•   http://portal.monitis.com/index.php/resources

•   http://www.hyperic.com/

•   http://mypublicstrangeworld.posterous.com/cloud-monitoring-services-a-resource-guide

•   http://www.itpro.co.uk/630655/dont-leave-cloud-monitoring-to-vendors-expert-warns

•   http://www.virtualizationpractice.com

•   http://virtualization.sys-con.com/

•   http://blog.newrelic.com/


                                                                                    30

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Monitoring applications on cloud - Indicthreads cloud computing conference 2011

  • 1. Monitoring Cloud Applications Amit Pathak 1
  • 2. Agenda  ontext  hallenges  onitoring-as-a-Service  ey Highlights 2  enefits
  • 3. Context Are agreed service levels met? Overall how many applications are healthy vs non-healthy? Is the health getting worse over time? Are the business functions being performed as expected? Do you have capacity within applications? 3
  • 4. Context Cloud Complexity  Scale and diversity of the infrastructure - Servers, network devices, storages, etc. - Hundreds, even thousands of machines  Massive number of user applications - Catastrophic consequence of failure / security breach / performance degradation 4
  • 5. Context Resource utilization is tightly coupled with cost incurred by customers Monitoring is indispensable  Availability, failure detection  Performance, provisioning  Security, anomaly detection  Application-level monitoring 5
  • 6. Challenges - Overview Inherits performance monitoring challenges of virtualized world End user response time – a primary metric Mechanism to collect data from various sources Managing agents Monitor, identify & heal bottlenecks 6
  • 7. Challenges - Overview Detect performance degradation:  Single malfunctioning application on a guest has a potential to degrade performance of host and other resources  Resource contention among applications executing on VMs may hamper performance  Virtual machines not configured with sufficient resource to handle workload 7
  • 8. Challenges – A Closer Look Source: Monitis 8
  • 9. Challenges – A Closer Look System Challenges User Cloud Challenges Monitoring Network Challenges 9
  • 10. Challenges – System Level Efficient Scalability: Monitor tasks – tens of thousands Cost effective - minimize resource usage  Facilitating service 10
  • 11. Challenges – System Level Efficient Scalability: Massive Scale  Monitor inherent large scale tasks  Large number of users - Infrastructure monitoring - Application monitoring  Monitor tasks with high cost e.g. Resources with high consumption 11
  • 12. Challenges – System Level Monitoring QoS Assurance: SLA management Application security  Federated identity of cloud applications  Secured integration of cloud apps with on-premise apps Multi-tenant environment  Authorization & access control Monitor contention between monitoring tasks 12
  • 13. Challenges – User Level Continuous violation detection  Need of different detection model - Dynamically add/remove servers based on performance  Achieve efficiency at the same time Short-term burst Persistent violation 13
  • 14. Challenges – Network Level Resource-aware monitoring fabric  Monitoring the functioning of both systems and applications running on large-scale distributed systems  Continuous collecting detailed attribute values - A large number of nodes - A large number of attributes  Overhead increases quickly as the system, application and monitoring tasks scales up 14
  • 15. Performance Monitoring Understand performance of virtual infrastructure – outside in approach Troubleshoot bottlenecks Plan future needs 15
  • 16. Key Parameters To Monitor CPU Memory Network Disk 16
  • 17. CPU CPU saturated? High Ready time  Problematic if it is sustained for high periods Possible contention for CPU resources among VMs  Workload Variability?  Resource limits on VMs?  Actual over commitment? High SwapWait time 17
  • 18. Memory Swap in rate Swap out rate Swap used 18
  • 19. Disk What should I look for to figure out if disk is an issue?  IOPs?  Bandwidth (read/write)?  Latencies? 19
  • 20. Network What should I look for to figure out if network is an issue?  Packate rate?  Bandwidth (read/write)?  NIC status? 20
  • 22. Monitoring-as-a-Service Similar to other cloud services  Database service (e.g. SimpleDB, Datastore)  Storage service (e.g. S3)  Application service (e.g. AppEngine) 22
  • 23. High Level Solution Applications, Events & Alerts Server – CPU, Customization memory, disk IO Packate rate, Gather data from bandwidth, NICs various resources Trend analysis 23
  • 24. Monitoring-as-a-Service External monitoring Web server, file server, mail server, VOIP Server monitoring CPU, memory, processes, storage Network monitoring Http, SSH, SNMP, discovery Transaction Multi-step apps, workflows monitoring Cloud monitoring Track running instances, auto-deploy, usage Web Traffic monitor Visitor, page views 24
  • 25. Key Highlights Scale dynamically Have minimum (or no) impact on the monitored infrastructure Should be portable and has to be light weight Easy feature customization. Not all metrics will need to be monitored in the cloud for everyone Heavy network based monitoring tools may not be a good fit 25
  • 26. Key Highlights Comprehensive monitoring of resource performance and availability  Applications, databases, middleware and web servers Provide innovative ideas to fetch data as business need grows  Dashboard, views, reports Co-relate information from different sources Trends analysis Predict bottlenecks 26
  • 27. Benefits End-to-end support Easy to use & maintain Reliable service Feature customization Cost effective 27
  • 28. Summary  Cloud is complex; monitoring needs are indispensable  End user response time is primary focus  Cloud services must be treated differently to on-premise software when it comes to systems monitoring  Do not rely on vendors completely. If SLAs are serious, maintain your own logs  Existing tools are good but use programmatic APIs for specific needs 28
  • 29. Thank You 29
  • 30. References • http://developer.vmware.com • http://www.cc.gatech.edu/ • http://portal.monitis.com/index.php/resources • http://www.hyperic.com/ • http://mypublicstrangeworld.posterous.com/cloud-monitoring-services-a-resource-guide • http://www.itpro.co.uk/630655/dont-leave-cloud-monitoring-to-vendors-expert-warns • http://www.virtualizationpractice.com • http://virtualization.sys-con.com/ • http://blog.newrelic.com/ 30