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A301
From Startup to Enterprise, learn how
performance monitoring can help you
scale your application
Michael Dawson, IBM Runtime Technologies
© 2016 IBM Corporation 2
About Michael Dawson
Senior Software Developer @ IBM
IBM Runtime Technologies Node.js Technical Lead
Node.js collaborator and CTC member
Active in LTS, build, benchmarking , api
and post-mortem working groups
Contact me:
michael_dawson@ca.ibm.com
Twitter: @mhdawson1
https://www.linkedin.com/in/michael-dawson-6051282
© 2016 IBM Corporation 3
About Toby Corbin
Software Developer @ IBM
IBM Runtime Technologies monitoring lead
15 years at IBM
Last 8 working on monitoring solutions for Java and more
recently Node.js
Contact me:
corbint@uk.ibm.com
Twitter: @TobesCorbin
Agenda
• Common scaling problems
• Common problems – what can I do ?
• Applying performance monitoring
• “Classic” deployment environment
• Demo
• ”Cloud” deployment environment
• Collecting data in the cloud
• Demo
• Summary
© 2016 IBM Corporation 4
• Lower than expected throughput in the application
© 2016 IBM Corporation 5
Common Scaling Problems
• Lower than expected throughput in the application
• Poor response time
© 2016 IBM Corporation 6
Common Scaling Problems
• Lower than expected throughput in the application
• Poor response time
• Higher than expected CPU usage for the level of
throughput/load
© 2016 IBM Corporation 7
Common Scaling Problems
• Lower than expected throughput in the application
• Poor response time
• Higher than expected CPU usage for the level of
throughput/load
• Extremely slow progression looking similar to a
hang or becoming unresponsive
© 2016 IBM Corporation 8
Common Scaling Problems
• Essentially single threaded
© 2016 IBM Corporation 9
Common Scaling Problems – Node.js Context
© 2016 IBM Corporation 10
Common Scaling Problems – Node.js Context
• Identify limiting factor
• CPU
• I/O
• Memory
• Synchronization
• Performance monitoring is the tool for the job
© 2016 IBM Corporation
Common Scaling Problems – What can I do ?
11
• CPU
• Faster CPU
• More CPUs (+ more Node.js instances)
• Reduce CPU Usage
• Extract CPU Intensive work
© 2016 IBM Corporation
Common Scaling Problems – What can I do ?
12
• I/O
• Identify which I/O is bottleneck
• Optimize I/O provider (database, file system etc.)
• Optimize requests profile
© 2016 IBM Corporation
Common Scaling Problems – What can I do ?
13
• Memory
• Heap - garbage collector
• Tune heap size
• Optimize allocation profile
• Native memory
• Increase system memory
• Optimize allocation profile
• Node.js
• Default heap ~ 1.5 G
• --max-old-space-size=XXX
© 2016 IBM Corporation
Common Scaling Problems – What can I do ?
14
Investigating - “Classic” Deployments
• “Classic” : desktop development, on premise
deployment
© 2016 IBM Corporation 15
• “Classic” : desktop development, on premise
deployment
© 2016 IBM Corporation
Investigating - “Classic” Deployments
Capture and evaluate
post-mortem
16
• Capture and evaluate post-mortem
• Turn on application logging and send to a file
• Capture verbosegc output
• Generate a heap dump to see where memory is being
used – https://github.com/bnoordhuis/node-heapdump
• nodereport - https://github.com/nodejs/nodereport
© 2016 IBM Corporation
--trace_gc
--trace_gc_nvp
--trace_gc_verbose
Investigating - “Classic” Deployments
17
• “Classic” : desktop development, on premise
deployment
© 2016 IBM Corporation
Investigating - “Classic” Deployments
Live
Monitoring
18
• Understand your applications behavior as it
occurs
• Connect a remote debugger
• Use live performance monitoring tools
© 2016 IBM Corporation
Investigating - “Classic” Deployments
© 2016 IBM Corporation
© 2016 IBM Corporation
Investigating - “Classic” Deployments
• “Classic” : desktop development, on premise
deployment
• Use the same tools for both
20
• “Classic” : desktop development, on premise
deployment
• Use the same tools for both
© 2016 IBM Corporation
Investigating - “Classic” Deployments
21
© 2016 IBM Corporation
Investigating - “Classic” Deployments
• “Classic” : desktop development, on premise
deployment
• Use the same tools for both
22
Live Performance Monitoring
Provides insight into your applications behavior
At runtime, you connect a GUI to your application to
visualize the data
© 2016 IBM Corporation 23
Live monitoring demo
• Demo of Health Center, development monitoring solution
• Free from Eclipse marketplace
• http://marketplace.eclipse.org/content/ibm-monitoring-and-diagnostic-tools-health-center
• http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/
© 2016 IBM Corporation 24
• “Cloud” : desktop development, on cloud
deployment
• Can we use the same tools for both ?
© 2016 IBM Corporation
Investigating - “Cloud” Deployments
25
© 2016 IBM Corporation
Investigating - “Cloud” Deployments
• “Cloud” : desktop development, on cloud
deployment
• Can we use the same tools for both ?
26
• No persistent local file system
• What happens if the container drops and
restarts ?
• Where do you now send your log data ?
© 2016 IBM Corporation
Investigating - “Cloud” Deployments
27
© 2016 IBM Corporation
Investigating - “Cloud” Deployments
• “Cloud” : desktop development, on cloud
deployment
• Can we use the same tools for both ?
28
• Application could be anywhere in the cloud
• Can’t just attach a remote debugger anymore
• Blocked ports
• Multiple instances
• Proxies
• We need a new approach for collecting data in the
© 2016 IBM Corporation
Investigating - “Cloud” Deployments
29
• Elastic Search - https://www.elastic.co/products/elasticsearch
• Logstash - https://www.elastic.co/products/logstash
• Kibana - https://www.elastic.co/products/kibana
© 2016 IBM Corporation
Collecting data in the cloud – ELK (open source)
30
Collecting data in the cloud
• Data now has to be sent somewhere and stored
app
server
app
server
Log data
Log data
© 2016 IBM Corporation 31
• Send data to logstash
app
server
app
server
logstash
Log data
Log data
© 2016 IBM Corporation 32
Collecting data in the cloud
• Elasticsearch can aggregate over this data
app
server
app
server
logstash Elasticsearch
Log data
Log data
© 2016 IBM Corporation 33
Collecting data in the cloud
• Kibana can be used to visualize
app
server
app
server
logstash Elasticsearch
Log data
Log data
© 2016 IBM Corporation 34
Collecting data in the cloud
What about performance monitoring data ?
• ELK + appmetrics
• Build your own
• appmetrics API – capture
• push to elastic search
• appmetrics-elk
• – prebuilt integration
© 2016 IBM Corporation
3
5
Collecting data in the cloud
• Elasticsearch can correlate log and metrics data
app
server
app
server
logstash Elasticsearch
Log data
Log data
Monitored data
Monitored data
© 2016 IBM Corporation 36
Appmetrics-elk demo
• Code walkthrough and demo
• https://github.com/RuntimeTools/appmetrics
• https://github.com/RuntimeTools/appmetrics-elk
37© 2016 IBM Corporation
Appmetrics-elk demo
• Same data, different visualization
© 2016 IBM Corporation 38
Managed monitoring solutions
• Transactions and utilizations vs code
• Products like IBM Application Performance
Management (APM) provide contextual monitoring
software.
• E.g. your transactions are going slow
• Generally focus on high level dash boarding, not
low level detail of the VM
© 2016 IBM Corporation 39
Summary
• Common scaling problems
• Common problems – what can I do ?
• Applying performance monitoring
• “Classic” deployment environment
• Demo
• ”Cloud” deployment environment
• Collecting data in the cloud
• Demo
© 2016 IBM Corporation 40
Summary
• Performance monitoring is key tool for scaling
your applications
• “Classic” and “Cloud” environment may require
different approaches
• The same data can be used in both cases
© 2016 IBM Corporation 41
Michael Dawson
Thank you very much.
IBM
Runtime Technologies
michael_dawson@ca.ibm.com
© 2016 IBM Corporation 42
Toby Corbin
IBM
Runtime Technologies
corbint@uk.ibm.com
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© 2016 IBM Corporation 43
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Copyright © 2016 by International Business Machines Corporation (IBM). No part of this document may be reproduced or transmitted in any form without written permission
from IBM.
U.S. Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM.
Information in these presentations (including information relating to products that have not yet been announced by IBM) has been reviewed for accuracy as of the date of
initial publication and could include unintentional technical or typographical errors. IBM shall have no responsibility to update this information. THIS DOCUMENT IS
DISTRIBUTED "AS IS" WITHOUT ANY WARRANTY, EITHER EXPRESS OR IMPLIED. IN NO EVENT SHALL IBM BE LIABLE FOR ANY DAMAGE ARISING FROM THE
USE OF THIS INFORMATION, INCLUDING BUT NOT LIMITED TO, LOSS OF DATA, BUSINESS INTERRUPTION, LOSS OF PROFIT OR LOSS OF OPPORTUNITY. IBM
products and services are warranted according to the terms and conditions of the agreements under which they are provided.
Any statements regarding IBM's future direction, intent or product plans are subject to change or withdrawal without notice.
Performance data contained herein was generally obtained in a controlled, isolated environments. Customer examples are presented as illustrations of how those customers
have used IBM products and the results they may have achieved. Actual performance, cost, savings or other results in other operating environments may vary.
References in this document to IBM products, programs, or services does not imply that IBM intends to make such products, programs or services available in all countries in
which IBM operates or does business.
Workshops, sessions and associated materials may have been prepared by independent session speakers, and do not necessarily reflect the views of IBM. All materials
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laws. IBM does not provide legal advice or represent or warrant that its services or products will ensure that the customer is in compliance with any law.
Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has
not tested those products in connection with this publication and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products.
Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products. IBM does not warrant the quality of any third-party products, or the
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The provision of the information contained herein is not intended to, and does not, grant any right or license under any IBM patents, copyrights, trademarks or other
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• IBM, the IBM logo, ibm.com, Aspera®, Bluemix, Blueworks Live, CICS, Clearcase, Cognos®, DOORS®, Emptoris®, Enterprise Document Management System™,
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A301 ctu madrid2016-monitoring

  • 1. A301 From Startup to Enterprise, learn how performance monitoring can help you scale your application Michael Dawson, IBM Runtime Technologies
  • 2. © 2016 IBM Corporation 2 About Michael Dawson Senior Software Developer @ IBM IBM Runtime Technologies Node.js Technical Lead Node.js collaborator and CTC member Active in LTS, build, benchmarking , api and post-mortem working groups Contact me: michael_dawson@ca.ibm.com Twitter: @mhdawson1 https://www.linkedin.com/in/michael-dawson-6051282
  • 3. © 2016 IBM Corporation 3 About Toby Corbin Software Developer @ IBM IBM Runtime Technologies monitoring lead 15 years at IBM Last 8 working on monitoring solutions for Java and more recently Node.js Contact me: corbint@uk.ibm.com Twitter: @TobesCorbin
  • 4. Agenda • Common scaling problems • Common problems – what can I do ? • Applying performance monitoring • “Classic” deployment environment • Demo • ”Cloud” deployment environment • Collecting data in the cloud • Demo • Summary © 2016 IBM Corporation 4
  • 5. • Lower than expected throughput in the application © 2016 IBM Corporation 5 Common Scaling Problems
  • 6. • Lower than expected throughput in the application • Poor response time © 2016 IBM Corporation 6 Common Scaling Problems
  • 7. • Lower than expected throughput in the application • Poor response time • Higher than expected CPU usage for the level of throughput/load © 2016 IBM Corporation 7 Common Scaling Problems
  • 8. • Lower than expected throughput in the application • Poor response time • Higher than expected CPU usage for the level of throughput/load • Extremely slow progression looking similar to a hang or becoming unresponsive © 2016 IBM Corporation 8 Common Scaling Problems
  • 9. • Essentially single threaded © 2016 IBM Corporation 9 Common Scaling Problems – Node.js Context
  • 10. © 2016 IBM Corporation 10 Common Scaling Problems – Node.js Context
  • 11. • Identify limiting factor • CPU • I/O • Memory • Synchronization • Performance monitoring is the tool for the job © 2016 IBM Corporation Common Scaling Problems – What can I do ? 11
  • 12. • CPU • Faster CPU • More CPUs (+ more Node.js instances) • Reduce CPU Usage • Extract CPU Intensive work © 2016 IBM Corporation Common Scaling Problems – What can I do ? 12
  • 13. • I/O • Identify which I/O is bottleneck • Optimize I/O provider (database, file system etc.) • Optimize requests profile © 2016 IBM Corporation Common Scaling Problems – What can I do ? 13
  • 14. • Memory • Heap - garbage collector • Tune heap size • Optimize allocation profile • Native memory • Increase system memory • Optimize allocation profile • Node.js • Default heap ~ 1.5 G • --max-old-space-size=XXX © 2016 IBM Corporation Common Scaling Problems – What can I do ? 14
  • 15. Investigating - “Classic” Deployments • “Classic” : desktop development, on premise deployment © 2016 IBM Corporation 15
  • 16. • “Classic” : desktop development, on premise deployment © 2016 IBM Corporation Investigating - “Classic” Deployments Capture and evaluate post-mortem 16
  • 17. • Capture and evaluate post-mortem • Turn on application logging and send to a file • Capture verbosegc output • Generate a heap dump to see where memory is being used – https://github.com/bnoordhuis/node-heapdump • nodereport - https://github.com/nodejs/nodereport © 2016 IBM Corporation --trace_gc --trace_gc_nvp --trace_gc_verbose Investigating - “Classic” Deployments 17
  • 18. • “Classic” : desktop development, on premise deployment © 2016 IBM Corporation Investigating - “Classic” Deployments Live Monitoring 18
  • 19. • Understand your applications behavior as it occurs • Connect a remote debugger • Use live performance monitoring tools © 2016 IBM Corporation Investigating - “Classic” Deployments © 2016 IBM Corporation
  • 20. © 2016 IBM Corporation Investigating - “Classic” Deployments • “Classic” : desktop development, on premise deployment • Use the same tools for both 20
  • 21. • “Classic” : desktop development, on premise deployment • Use the same tools for both © 2016 IBM Corporation Investigating - “Classic” Deployments 21
  • 22. © 2016 IBM Corporation Investigating - “Classic” Deployments • “Classic” : desktop development, on premise deployment • Use the same tools for both 22
  • 23. Live Performance Monitoring Provides insight into your applications behavior At runtime, you connect a GUI to your application to visualize the data © 2016 IBM Corporation 23
  • 24. Live monitoring demo • Demo of Health Center, development monitoring solution • Free from Eclipse marketplace • http://marketplace.eclipse.org/content/ibm-monitoring-and-diagnostic-tools-health-center • http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/ © 2016 IBM Corporation 24
  • 25. • “Cloud” : desktop development, on cloud deployment • Can we use the same tools for both ? © 2016 IBM Corporation Investigating - “Cloud” Deployments 25
  • 26. © 2016 IBM Corporation Investigating - “Cloud” Deployments • “Cloud” : desktop development, on cloud deployment • Can we use the same tools for both ? 26
  • 27. • No persistent local file system • What happens if the container drops and restarts ? • Where do you now send your log data ? © 2016 IBM Corporation Investigating - “Cloud” Deployments 27
  • 28. © 2016 IBM Corporation Investigating - “Cloud” Deployments • “Cloud” : desktop development, on cloud deployment • Can we use the same tools for both ? 28
  • 29. • Application could be anywhere in the cloud • Can’t just attach a remote debugger anymore • Blocked ports • Multiple instances • Proxies • We need a new approach for collecting data in the © 2016 IBM Corporation Investigating - “Cloud” Deployments 29
  • 30. • Elastic Search - https://www.elastic.co/products/elasticsearch • Logstash - https://www.elastic.co/products/logstash • Kibana - https://www.elastic.co/products/kibana © 2016 IBM Corporation Collecting data in the cloud – ELK (open source) 30
  • 31. Collecting data in the cloud • Data now has to be sent somewhere and stored app server app server Log data Log data © 2016 IBM Corporation 31
  • 32. • Send data to logstash app server app server logstash Log data Log data © 2016 IBM Corporation 32 Collecting data in the cloud
  • 33. • Elasticsearch can aggregate over this data app server app server logstash Elasticsearch Log data Log data © 2016 IBM Corporation 33 Collecting data in the cloud
  • 34. • Kibana can be used to visualize app server app server logstash Elasticsearch Log data Log data © 2016 IBM Corporation 34 Collecting data in the cloud
  • 35. What about performance monitoring data ? • ELK + appmetrics • Build your own • appmetrics API – capture • push to elastic search • appmetrics-elk • – prebuilt integration © 2016 IBM Corporation 3 5
  • 36. Collecting data in the cloud • Elasticsearch can correlate log and metrics data app server app server logstash Elasticsearch Log data Log data Monitored data Monitored data © 2016 IBM Corporation 36
  • 37. Appmetrics-elk demo • Code walkthrough and demo • https://github.com/RuntimeTools/appmetrics • https://github.com/RuntimeTools/appmetrics-elk 37© 2016 IBM Corporation
  • 38. Appmetrics-elk demo • Same data, different visualization © 2016 IBM Corporation 38
  • 39. Managed monitoring solutions • Transactions and utilizations vs code • Products like IBM Application Performance Management (APM) provide contextual monitoring software. • E.g. your transactions are going slow • Generally focus on high level dash boarding, not low level detail of the VM © 2016 IBM Corporation 39
  • 40. Summary • Common scaling problems • Common problems – what can I do ? • Applying performance monitoring • “Classic” deployment environment • Demo • ”Cloud” deployment environment • Collecting data in the cloud • Demo © 2016 IBM Corporation 40
  • 41. Summary • Performance monitoring is key tool for scaling your applications • “Classic” and “Cloud” environment may require different approaches • The same data can be used in both cases © 2016 IBM Corporation 41
  • 42. Michael Dawson Thank you very much. IBM Runtime Technologies michael_dawson@ca.ibm.com © 2016 IBM Corporation 42 Toby Corbin IBM Runtime Technologies corbint@uk.ibm.com
  • 43. Your feedback is valuable Please complete your session or lab evaluation! Session number [A301] Provide your evaluations by: Evaluation forms: Fill out a form at the end of each session Paper forms are located in each of the session or lab rooms Complete the session survey on Event Connect Portal: https://portal.ibmeventconnect.com/m adrid2016 Select Sessions, then Session Finder, and complete the survey - Or - © 2016 IBM Corporation 43
  • 44. IBMTA16 Twitter @IBMCloud | @IBMWebSphere LinkedIn IBM Cloud YouTube IBM Cloud | IBM WebSphere Facebook IBM Cloud ibmcloud Facebook Event Page IBM Techical Academy 2016 websphere
  • 45. Copyright © 2016 by International Business Machines Corporation (IBM). No part of this document may be reproduced or transmitted in any form without written permission from IBM. U.S. Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM. Information in these presentations (including information relating to products that have not yet been announced by IBM) has been reviewed for accuracy as of the date of initial publication and could include unintentional technical or typographical errors. IBM shall have no responsibility to update this information. THIS DOCUMENT IS DISTRIBUTED "AS IS" WITHOUT ANY WARRANTY, EITHER EXPRESS OR IMPLIED. IN NO EVENT SHALL IBM BE LIABLE FOR ANY DAMAGE ARISING FROM THE USE OF THIS INFORMATION, INCLUDING BUT NOT LIMITED TO, LOSS OF DATA, BUSINESS INTERRUPTION, LOSS OF PROFIT OR LOSS OF OPPORTUNITY. IBM products and services are warranted according to the terms and conditions of the agreements under which they are provided. Any statements regarding IBM's future direction, intent or product plans are subject to change or withdrawal without notice. Performance data contained herein was generally obtained in a controlled, isolated environments. Customer examples are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual performance, cost, savings or other results in other operating environments may vary. References in this document to IBM products, programs, or services does not imply that IBM intends to make such products, programs or services available in all countries in which IBM operates or does business. Workshops, sessions and associated materials may have been prepared by independent session speakers, and do not necessarily reflect the views of IBM. All materials and discussions are provided for informational purposes only, and are neither intended to, nor shall constitute legal or other guidance or advice to any individual participant or their specific situation. It is the customer’s responsibility to insure its own compliance with legal requirements and to obtain advice of competent legal counsel as to the identification and interpretation of any relevant laws and regulatory requirements that may affect the customer’s business and any actions the customer may need to take to comply with such laws. IBM does not provide legal advice or represent or warrant that its services or products will ensure that the customer is in compliance with any law.
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