Application Monitoring in a Post-Server World: Why Data Context is Critical
Download as PPTX, PDF0 likes608 views
The document discusses the evolution of computing, emphasizing the transition from traditional server usage to containerization technologies like Docker and AWS services such as Lambda that enable disposable compute. It highlights the significance of monitoring tools to manage the dynamic nature of cloud infrastructure and the necessity of context for understanding computational performance and intent. Additionally, it covers the importance of analytics in evaluating resource provisioning and operational efficiency within AWS environments.
Application Monitoring in a Post-Server World: Why Data Context is Critical
- 2. 2Confidential ©2008-15 New Relic, Inc. All rights reserved.
- 3. The Decline of the Server ▪ Containerization ▪ Docker ▪ Amazon ECS ▪ Zero config infrastructure-less compute ▪ AWS Lambda ©2008-15 New Relic, Inc. All rights reserved.
- 4. Lessons learned from Docker ©2008-15 New Relic, Inc. All rights reserved.
- 5. Docker is the app’s lightweight VM Long livedShort lived VM Amazon EC2 ©2008-15 New Relic, Inc. All rights reserved.
- 6. 6 Well, that was surprising Confidential ©2008-15 New Relic, Inc. All rights reserved. 49 ACCOUNTS USING DOCKER IN LAST 24 HOURS 9,974 CONTAINERS REPORTING IN IN LAST 24 HOURS ©2008-15 New Relic, Inc. All rights reserved.
- 7. 7 Apparent usage Confidential ©2008-15 New Relic, Inc. All rights reserved. Long livedShort lived Amazon EC2 VM ©2008-15 New Relic, Inc. All rights reserved.
- 8. 8 Along came New Relic Synthetics… Confidential ©2008-15 New Relic, Inc. All rights reserved. ▪ Test external availability and performance ▪ User authored selenium scripts run in our data center ▪ Each run in its own container for security isolation ▪ Most run for under a minute ©2008-15 New Relic, Inc. All rights reserved.
- 9. 9 Disposable compute container Confidential ©2008-15 New Relic, Inc. All rights reserved. Long livedShort lived VM Amazon EC2 AWS Lambda ©2008-15 New Relic, Inc. All rights reserved.
- 10. What the heck’s going on? Confidential ©2008-15 New Relic, Inc. All rights reserved. Long livedShort lived ? ? ? VM Amazon EC2 AWS Lambda ©2008-15 New Relic, Inc. All rights reserved.
- 11. We’re Data Nerds! Confidential ©2008-15 New Relic, Inc. All rights reserved.©2008-15 New Relic, Inc. All rights reserved.
- 12. Docker container age, count vs. hours 10 0 10 K 1 M 3.7 M 83 days 333 days ©2008-15 New Relic, Inc. All rights reserved.
- 13. Docker container age, count vs. hours 10 0 10 K 1 M 3.7 M VM’ish ©2008-15 New Relic, Inc. All rights reserved.
- 14. Docker container age, count vs. hours Confidential ©2008-15 New Relic, Inc. All rights reserved. 10 0 10 K 1 M 3.7 M EC2’ish ©2008-15 New Relic, Inc. All rights reserved.
- 15. Docker container age, count vs. hours Confidential ©2008-15 New Relic, Inc. All rights reserved. 10 0 10 K 1 M 3.7 M Lambda’ish ©2008-15 New Relic, Inc. All rights reserved.
- 16. Container age, by hour under 24 hours Confidential ©2008-15 New Relic, Inc. All rights reserved. 3,741,000 46% under one hour ©2008-15 New Relic, Inc. All rights reserved.
- 17. Container age, by minute under an hour Confidential ©2008-15 New Relic, Inc. All rights reserved. 950,000 11% under one minute ©2008-15 New Relic, Inc. All rights reserved.
- 18. Container age, by minute under an hour Confidential ©2008-15 New Relic, Inc. All rights reserved. 27% under 5 minutes (versus a VM?) ©2008-15 New Relic, Inc. All rights reserved.
- 19. A surprising result Confidential ©2008-15 New Relic, Inc. All rights reserved. Long livedShort lived VMVM Amazon EC2 AWS Lambda ©2008-15 New Relic, Inc. All rights reserved.
- 20. June versus now: 5x data, same shape Confidential ©2008-15 New Relic, Inc. All rights reserved.©2008-15 New Relic, Inc. All rights reserved.
- 21. The evolution of computation as a service Short startup time (orders mag.) allows very short lived computing Containers only exist, and only for as long, as they provide value. Full stop. Containers are created Do their work Go away ©2008-15 New Relic, Inc. All rights reserved.
- 22. Elements of monitoring computation as a service ▪ A mere list of instances doesn’t scale, nor help ▪ De-provisioned containers still contribute to knowledge ▪ Raw metrics just table stakes ▪ Context matters to identify computational intent ©2008-15 New Relic, Inc. All rights reserved.
- 23. Monitoring servers ©2008-15 New Relic, Inc. All rights reserved.
- 24. Monitoring computation ©2008-15 New Relic, Inc. All rights reserved.
- 25. Low friction install New Relic AWS EC2 Beta addresses Confidential ©2008-15 New Relic, Inc. All rights reserved. Managing the dynamic nature of AWS Managing the scale of AWS ©2008-15 New Relic, Inc. All rights reserved.
- 26. Increased visibility Application Monitoring Server Monitoring EC2 AWS Metadata ©2008-15 New Relic, Inc. All rights reserved.
- 27. SaaS to SaaS monitoring, under one minute ©2008-15 New Relic, Inc. All rights reserved.
- 28. Dynamic management Provides AWS status Maintains accurate EC2 list Detects blind spots Shows instance state ©2008-15 New Relic, Inc. All rights reserved.
- 29. Context via tags and metadata as labels AWS metadata AWS custom tags ©2008-15 New Relic, Inc. All rights reserved.
- 30. EC2 instance name AWS metadata Custom label Customer example ©2008-15 New Relic, Inc. All rights reserved.
- 31. New Relic by instance type Selected label Instance count Health status ©2008-15 New Relic, Inc. All rights reserved.
- 32. New Relic by availability zone ©2008-15 New Relic, Inc. All rights reserved.
- 33. New Relic by instance type in us-east-1 ©2008-15 New Relic, Inc. All rights reserved.
- 34. Confidential ©2008-15 New Relic, Inc. All rights reserved. Future requirements for monitoring tools The obvious ones Should handle scale Should handle dynamic lifecycle of resources The less obvious ones It’s a big data problem Ops needs ways of quickly pivoting and drilling in Deeper understanding requires analytics (raw metrics not enough) ©2008-15 New Relic, Inc. All rights reserved.
- 35. We all love… … and yet Common AWS scenarios No large infrastructure build out Quickly provision Scale out to meet demand Am I under-provisioned? Am I over-provisioned? How well am I responding to demand? ©2008-15 New Relic, Inc. All rights reserved.
- 36. Prototype examples of Analytics Application and Server metrics Enriched with context from AWS As New Relic Insights events ©2008-15 New Relic, Inc. All rights reserved.
- 37. Detecting under-provisioned Hmm, that’s bad The smoking gun Aha! ©2008-15 New Relic, Inc. All rights reserved.
- 38. Detecting over-provisioned Hmm, that’s too good Aha!That’s a waste ©2008-15 New Relic, Inc. All rights reserved.
- 39. Evaluating availability elasticity Through scale out But never de-provisioned Response time settles back Increased load ©2008-15 New Relic, Inc. All rights reserved.
- 40. The Ultimate AWS control panel Confidential ©2008-15 New Relic, Inc. All rights reserved. RESOURCES CUSTOMER EXPERIENCE COST ©2008-15 New Relic, Inc. All rights reserved.
- 41. newrelic.com/aws Sign up for Beta notification AWS Monitoring resources Demo videos Come by the booth!