Monitoring applications on cloud - Indicthreads cloud computing conference 2011


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Session presented at the 2nd Conference on Cloud Computing held in Pune, India on 3-4 June 2011.

Session Abstract:
Today’s end users expect ever increasing speed and complex media-rich web applications. Performance, response time and speed at which services are being delivered to customer are a critical metric for any business. Traditional application monitoring tools are powerful but have a perspective of monitoring applications in a data center.

What you lose primarily when the apps are moved to cloud is the visibility that comes monitoring performance using traditional tool in a data center. Next generation monitoring applications have to understand the cloud factor and need to be ‘cloud aware’.

In a cloud environment, SLAs and applications really cover anything that is beyond server uptime. Monitoring should provide visibility into the infrastructural aspects along with performance of applications. Approach should be adopted to have a mechanism of gathering data from all possible sources across locations, analyzing it intelligently and presenting through a dashboard which can be drilled down up to granular levels. You should be able trace any problem to its source. You should receive automated alerts even to isolated problems that may be affecting end users.

Monitoring of cloud applications cannot be left up to the service providers only. While service providers may provide their services to monitor your applications, you may not rely completely on that and must need to handle it in your own way for your individual needs.

This session will look at:

Why traditional monitoring tools can’t work efficiently on cloud?
Which parameters need monitoring?
How to identify bottlenecks on clouds, what are self-heal actions, what level of automation can be
Cloud Best practices in cloud application monitoring
How virtual infrastructure monitoring goes hand in hand with application monitoring on cloud?
How can you build your own monitoring applications using APIs? What are use cases?

Amit Pathak has 12+ years of experience and is currently working as a project manager in product engineering services division of Patni Computer System Ltd. Amit has a development back ground in Java/J2EE stack. From last 3 years he is in the field of virtualization and cloud computing providing solutions to business needs to adopt virtualization in enterprises and providing automation solutions.

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Monitoring applications on cloud - Indicthreads cloud computing conference 2011

  1. 1. Monitoring Cloud Applications Amit Pathak 1
  2. 2. Agenda  ontext  hallenges  onitoring-as-a-Service  ey Highlights 2  enefits
  3. 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. 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. 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. 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. 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. 8. Challenges – A Closer LookSource: Monitis 8
  9. 9. Challenges – A Closer Look System ChallengesUser CloudChallenges Monitoring Network Challenges 9
  10. 10. Challenges – System LevelEfficient Scalability: Monitor tasks – tens of thousands Cost effective - minimize resource usage Facilitating service 10
  11. 11. Challenges – System LevelEfficient 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. 12. Challenges – System LevelMonitoring 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. 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. 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. 15. Performance Monitoring Understand performance of virtual infrastructure – outside in approach Troubleshoot bottlenecks Plan future needs 15
  16. 16. Key Parameters To Monitor CPU Memory Network Disk 16
  17. 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. 18. MemorySwap in rateSwap out rateSwap used 18
  19. 19. Disk What should I look for to figure out if disk is an issue? IOPs? Bandwidth (read/write)? Latencies? 19
  20. 20. Network What should I look for to figure out if network is an issue? Packate rate? Bandwidth (read/write)? NIC status? 20
  21. 21. Monitoring-as-a-Service 21
  22. 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. 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. 24. Monitoring-as-a-ServiceExternal monitoring Web server, file server, mail server, VOIPServer monitoring CPU, memory, processes, storageNetwork monitoring Http, SSH, SNMP, discoveryTransaction Multi-step apps, workflowsmonitoringCloud monitoring Track running instances, auto-deploy, usageWeb Traffic monitor Visitor, page views 24
  25. 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. 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. 27. Benefits End-to-end support Easy to use & maintain Reliable service Feature customization Cost effective 27
  28. 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. 29. Thank You 29
  30. 30. References••••••••• 30