using monitoring and metrics to learn in development
play

Using Monitoring and Metrics to learn in Development Patrick Debois - PowerPoint PPT Presentation

Oct 16, 2022 •109 likes •775 views

Using Monitoring and Metrics to learn in Development Patrick Debois Atlassian http://jedi.be/blog @patrickdebois Monday, May 21, 12 HOSTEDOPS https://my.atlassian.com/ondemand/ http://www.cutter.com http://itrevolution.com Vagrant &

  1. Using Monitoring and Metrics to learn in Development Patrick Debois Atlassian http://jedi.be/blog @patrickdebois Monday, May 21, 12

  2. HOSTEDOPS https://my.atlassian.com/ondemand/ http://www.cutter.com http://itrevolution.com Vagrant & http://devopsdays.org Veewee Monday, May 21, 12

  3. Your Code Monday, May 21, 12

  4. Monday, May 21, 12

  5. “Test Driven Development” - CI Coward Monday, May 21, 12

  6. Testing in Controlled Environment Monday, May 21, 12

  7. Your Code in Test Monday, May 21, 12

  8. “Until code runs in production , your code is just inventory” - Agile Anonymous Monday, May 21, 12

  9. Continuous Delivery DEV OPS CLASH Monday, May 21, 12

  10. Monday, May 21, 12

  11. Shit Happens in production Monday, May 21, 12

  12. “You go to production with the code you have, not the code you wish you had” - Devops Rumsfeld Monday, May 21, 12

  13. Dreamer Realist Critic DEV OPS Three Phases of Creativity (Disney) Monday, May 21, 12

  14. Devops Areas Area 3: Embed Project knowledge into Operations Area 1: Extend delivery to production DEV OPS Area 2: Extend operations feedback to project Area 4: Embed Operations knowledge into Project http://jedi.be/blog/2012/05/12/codifying-devops-area-practices/ Monday, May 21, 12

  15. C ulture A utomate DEV OPS M easure S hare http://www.opscode.com/blog/2010/07/16/what-devops-means-to-me/ Monday, May 21, 12

  16. Smaller and more frequent changes DEV OPS Faster and better feedback Monday, May 21, 12

  17. Area 1: Extend delivery to production “think Jez Humble” Area 1 DEV OPS Monday, May 21, 12

  18. Continuous Integration Maturity Model http://www.slideshare.net/Urbancode/continuous-delivery-maturity-model Monday, May 21, 12

  19. Infrastructure Code Repository DEV TEST PROD WEB WEB WEB APP APP APP DB DB DB Reuse “Infra code” across Environments Monday, May 21, 12

  20. Reuse “workflow” across Environments VM UP PROVISION HALT VM Management DESTROY WEB Simple CLI APP Vagrantfile DB Puppet/Chef Config Basebox JEOS HOST http://vagrantup.com/ Monday, May 21, 12

  21. Integrate with Continuous Integration DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Infrastructure Application Code Repository Code Repository Monday, May 21, 12

  22. Continuous Integration to Continuous Delivery Faster/Delivery DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Faster/Feedback Infrastructure Application Code Repository Code Repository Monday, May 21, 12

  23. Area 2: Extend operations feedback to project think “John Allspaw” DEV OPS Area2 Monday, May 21, 12

  24. Monitoring Layers User/Business External Network/Security Services Service Clustered Services App App Middleware Middleware OS OS Hardware Hardware Network Storage Monday, May 21, 12

  25. Monitoring Layers Behavioral (larger coverage) Diagnostics Monday, May 21, 12

  26. “What part made it fail” ~unit test CPU Memory Network Monday, May 21, 12

  27. “Is it working?” ~behavioral test Monday, May 21, 12

  28. Monitoring Driven Development Create a monitor check before implementing a feature Monday, May 21, 12

  29. Information Radiator Monday, May 21, 12

  30. Monitoring Wonderland http://jedi.be/blog/2012/01/03/monitoring-wonderland-survey-introduction/ http://jedi.be/blog/2012/01/03/monitoring-wonderland-nagios-the-mighty-beast/ http://jedi.be/blog/2012/01/04/monitoring-wonderland-moving-up-the-stack-application-user-metrics/ http://jedi.be/blog/2012/01/03/monitoring-wonderland-metrics-api-gateways/ http://jedi.be/blog/2012/01/04/monitoring-wonderland-visualization/ Monday, May 21, 12

  31. “traditional In house monitoring” Monday, May 21, 12

  32. Monday, May 21, 12

  33. “traditional In house metrics” http://munin-monitoring.org/ http://collectd.org/ Monday, May 21, 12

  34. Ganglia http://ganglia.info/ Monday, May 21, 12

  35. https://github.com/ monitoringsucks Monday, May 21, 12

  36. “1980” style UI Monday, May 21, 12

  37. No API Monday, May 21, 12

  38. Hard to scale Monday, May 21, 12

  39. Static configurations Monday, May 21, 12

  40. Hard to expose “data” UI vs API Monday, May 21, 12

  41. Not self-servicing Monday, May 21, 12

  42. “Monitoring as a service” Monday, May 21, 12

  43. Sonian Cloud Monitoring “Sensu” https://github.com/sensu/sensu Monday, May 21, 12

  44. http://code.google.com/p/rocksteady/ Monday, May 21, 12

  45. Reconnoiter's goal is to better the world of monitoring by marrying fault detection and trending together. Through ease of configuration and ongoing maintenance, Reconnoiter encourages monitoring important technical metrics along side critical business metrics to improve awareness and ultimately accountability. http://labs.omniti.com/labs/reconnoiter Monday, May 21, 12

  46. Scalable writes http://opentsdb.net/ Monday, May 21, 12

  47. Selfservicing Graphs http://graphite.wikidot.com/ Monday, May 21, 12

  48. “App Metrics” Monday, May 21, 12

  49. “End-User Metrics” Monday, May 21, 12

  50. http://www.appdynamics.com/ Monday, May 21, 12

  51. https://github.com/lookfirst/jmxtrans Monday, May 21, 12

  52. GRAPHITE APP STATSD counting timing sampling https://github.com/etsy/statsd Monday, May 21, 12

  53. Metrics Java Library http://metrics.codahale.com/ https://github.com/tritonrc/metricsd Monday, May 21, 12

  54. Business Level Metrics Usage patterns - Google Analytics Monday, May 21, 12

  55. A/B Testing in Prod Metrics / Information Monday, May 21, 12

  56. Meta-Ops Metrics Know context Monday, May 21, 12

  57. Logs as feedback http://logstash.net/ http://graylog2.org/ https://github.com/rashidkpc/Kibana Monday, May 21, 12

  58. Unix Pipe Analogy Monday, May 21, 12

  59. Integrate with Continuous Integration DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Infrastructure Application Code Repository Code Repository Monday, May 21, 12

  60. Reuse Tools across dev & ops DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Monitoring/ Metrics Infrastructure Application Code Repository Code Repository Monday, May 21, 12

  61. Integrate with Continuous Monitoring DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Monitoring/ Monitoring/ Monitoring/ Metrics Metrics Metrics Infrastructure Application Code Repository Code Repository Monday, May 21, 12

  62. Reuse Workflow Debugging Post-Mortem DEV TEST PROD APP APP WEB DB APP WEB DB APP WEB DB INFRA APP WEB DB APP WEB DB APP WEB DB Monitoring/ Monitoring/ Monitoring/ Metrics Metrics Metrics Monday, May 21, 12

  63. Metrics Driven Engineering http://www.slideshare.net/mikebrittain/metricsdriven- engineering Monday, May 21, 12

  64. Monday, May 21, 12

  65. “The future is metrics are here they are just not evenly distributed yet” - Morpheus Monitoring Monday, May 21, 12

  66. http://jedi.be/blog https://github.com/monitoringsucks Monday, May 21, 12

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

5 Years of Metrics & Monitoring Lindsay Holmwood @auxesis Cultural & Technical

5 Years of Metrics & Monitoring Lindsay Holmwood @auxesis Cultural & Technical

5 Years of Metrics & Monitoring Lindsay Holmwood @auxesis Cultural & Technical Key retrospective questions What did we do well? What did we learn? What should we do differently next time? What still puzzles us?

2.13k views • 163 slides
A Map for Monitoring PostgreSQL #PgDaySF @LukasFittl @LukasFittl > 100 Metrics We Could

A Map for Monitoring PostgreSQL #PgDaySF @LukasFittl @LukasFittl > 100 Metrics We Could

A Map for Monitoring PostgreSQL #PgDaySF @LukasFittl @LukasFittl > 100 Metrics We Could Talk About > 100 Metrics We Could Talk About Historic Metrics Current Activity Logs Tuning Actions Query Workload

1.48k views • 100 slides
Monitoring Team Effectiveness: Measuring with Metrics, Not to Metrics Lynn Spragens, MBA

Monitoring Team Effectiveness: Measuring with Metrics, Not to Metrics Lynn Spragens, MBA

Monitoring Team Effectiveness: Measuring with Metrics, Not to Metrics Lynn Spragens, MBA President, Spragens & Associates, LLC Lynn@LSpragens.com Practical Tools for Making Change November 8 - 10 Orlando, FL Pre- Conference

579 views • 36 slides
1 Current Security Monitoring Current Network Monitoring Visualization Humans learn visually

1 Current Security Monitoring Current Network Monitoring Visualization Humans learn visually

Overview The Thin Blue Line: Security SysAdmins Current state of Internet Security Better Tools for System Administration: all metrics show bad -> worse unpatched software vulnerabilities Enhancing the Human-Computer

583 views • 6 slides
KAFKA STREAMS CLOUD MONITORING AWS CLOUD MONITORING AWS APP CLOUD MONITORING AWS HTTP APP

KAFKA STREAMS CLOUD MONITORING AWS CLOUD MONITORING AWS APP CLOUD MONITORING AWS HTTP APP

FROM USE CASE TO PRODUCTION KAFKA STREAMS CLOUD MONITORING AWS CLOUD MONITORING AWS APP CLOUD MONITORING AWS HTTP APP CLOUD MONITORING AWS METRICS NRDB HTTP APP CLOUD MONITORING SCHDLR JOBS AWS NRDB METRICS HTTP WORKER CLOUD

1.43k views • 124 slides
JVM Web Application Metrics & Monitoring FOLIO @krrrr38 2 3 1. 2. 3. JVM Web

JVM Web Application Metrics & Monitoring FOLIO @krrrr38 2 3 1. 2. 3. JVM Web

JVM Web Application Metrics & Monitoring FOLIO @krrrr38 2 3 1. 2. 3. JVM Web Application 4 5 Metrics 6 Metrics JVM http JMX jcmd, jstat, ... 7 Metrics server/process pull /push 8 pull /push push server -(process)->

528 views • 36 slides
Development Metrics You Should Use (but dont) Development Metrics You Should Use (but

Development Metrics You Should Use (but dont) Development Metrics You Should Use (but

Development Metrics You Should Use (but dont) Development Metrics You Should Use (but Dont) @catswetel at #gotochgo @catswetel at #gotochgo QUALITY RESPONSIVENESS PRODUCTIVITY PREDICTABILITY QUALITY RESPONSIVENESS Troy Magennis

889 views • 67 slides
What we learned from Community Metrics Agenda Why are metrics used? How metrics are used

What we learned from Community Metrics Agenda Why are metrics used? How metrics are used

What we learned from Community Metrics Agenda Why are metrics used? How metrics are used in two Open Source communities Common pitfalls and ways to avoid them Why use Metrics? Transparency Who is contributing to the

166 views • 14 slides
Improving reporting and monitoring: EU-wide shortage definition and metrics Multi-stakeholder

Improving reporting and monitoring: EU-wide shortage definition and metrics Multi-stakeholder

Improving reporting and monitoring: EU-wide shortage definition and metrics Multi-stakeholder meeting with the HMA/EMA Task Force on availability of authorised medicines 9 November 2018 Brendan Cuddy Annette Byrholt Hansen Head of

488 views • 19 slides
CORE METRICS & UNIVERSITY BENCHMARKS Core Metric Subject or Programme University Benchmark

CORE METRICS & UNIVERSITY BENCHMARKS Core Metric Subject or Programme University Benchmark

ANNUAL MONITORING 2020 (ABOUT 2019-20) Inputs: Data analysis: Core Metrics, University KPIs, Gap Metrics (new) , External Examiners Reports Benchmarks set by Office for Students for University Evaluation: Evaluation of performance

560 views • 12 slides
Monitoring Rohit Jnagal Anushree Narasimha Outline Overview Monitoring for containers

Monitoring Rohit Jnagal Anushree Narasimha Outline Overview Monitoring for containers

Container native Monitoring Rohit Jnagal Anushree Narasimha Outline Overview Monitoring for containers Monitoring in a distributed system cAdvisor Application Metrics In cAdvisor Plumbing through a cluster Future

396 views • 27 slides
MONITORING DEHCR BUREAU OF COMMUNITY DEVELOPMENT MONITORING PROCESS On

MONITORING DEHCR BUREAU OF COMMUNITY DEVELOPMENT MONITORING PROCESS On

MONITORING DEHCR BUREAU OF COMMUNITY DEVELOPMENT MONITORING PROCESS On site Visit or Desktop Monitoring at least once during the Performance Period 30 Day

436 views • 29 slides
REACH eCVSP Metrics Monitoring Project The Problem Today, law enforcement officials enter data

REACH eCVSP Metrics Monitoring Project The Problem Today, law enforcement officials enter data

REACH eCVSP Metrics Monitoring Project The Problem Today, law enforcement officials enter data into the FMCSAs electronic CVSP (eCVSP) system regarding their planned safety activities and anticipated incidents (crashes); then, they manually

537 views • 29 slides
AGENCY OPERATIONS METRICS The Metrics of Me The Metrics of Me x 159 13,006 5 days old books

AGENCY OPERATIONS METRICS The Metrics of Me The Metrics of Me x 159 13,006 5 days old books

Dont trust your gut AGENCY OPERATIONS METRICS The Metrics of Me The Metrics of Me x 159 13,006 5 days old books read so far in 2018 The Metrics of Me 6.3 4.5 4 0 hours of sleep hours in dance class hours cooking hours commuting

549 views • 20 slides
Metrics: How Will the ELL Pilot Define Success? Carlos Bravo, California Workforce Development

Metrics: How Will the ELL Pilot Define Success? Carlos Bravo, California Workforce Development

Workforce Goals and Metrics: How Will the ELL Pilot Define Success? Carlos Bravo, California Workforce Development Board Cory Rayala, California Department of Education Neil Kelly, Community Colleges Chancellors Office Common Metrics

283 views • 25 slides
Monitoring the Impact of the ACA July 8, 2014 3:00 p.m. ET Common Metrics Current Insurance

Monitoring the Impact of the ACA July 8, 2014 3:00 p.m. ET Common Metrics Current Insurance

Monitoring the Impact of the ACA July 8, 2014 3:00 p.m. ET Common Metrics Current Insurance Coverage Prior Insurance Coverage Future Insurance Coverage Plans Cost of Coverage and Care Affordability Challenges

1.29k views • 32 slides
Common Loon ( Gavia immer ) Mortality and Human Attitudes Brooke Hafford MacDonald, M.S.

Common Loon ( Gavia immer ) Mortality and Human Attitudes Brooke Hafford MacDonald, M.S.

Common Loon ( Gavia immer ) Mortality and Human Attitudes Brooke Hafford MacDonald, M.S. LakeSmart Program Manager Maine Lakes Society 1 Common Loon ( Gavia immer ) Nest on freshwater lakes and ponds during the summer months in Canada

716 views • 44 slides
Week 13 - Friday What did we talk about last time? Exam 2 post mortem Heaps Lab

Week 13 - Friday What did we talk about last time? Exam 2 post mortem Heaps Lab

Week 13 - Friday What did we talk about last time? Exam 2 post mortem Heaps Lab hours Wednesdays at 5 p.m. in The Point 113 Saturdays at noon in The Point 113 (Cancelled this Saturday! Contact Olivia Langley at

466 views • 28 slides
SWEN 256 Software Process & Project Management Agile Methods o cowboys and

SWEN 256 Software Process & Project Management Agile Methods o cowboys and

SWEN 256 Software Process & Project Management Agile Methods o cowboys and hackers o undisciplined o low quality Plan Driven Methods o process worship o document laden o excessive discipline Its not that black and

423 views • 20 slides
How to design a phase-II study Regina Berger Medical University of Innsbruck AGO-Austria GCIG

How to design a phase-II study Regina Berger Medical University of Innsbruck AGO-Austria GCIG

Gynecologic Cancer InterGroup How to design a phase-II study Regina Berger Medical University of Innsbruck AGO-Austria GCIG Education Symposium, November 2017, Vienna Two components outcome R outcome Operational Scientific design

541 views • 17 slides
BIG DATA AND US 2 GARTNER HYPE CYCLE www.gartner.com www.wikipedia.org GARTNER HYPE CYCLE 3

BIG DATA AND US 2 GARTNER HYPE CYCLE www.gartner.com www.wikipedia.org GARTNER HYPE CYCLE 3

BIG DATA AND US 2 GARTNER HYPE CYCLE www.gartner.com www.wikipedia.org GARTNER HYPE CYCLE 3 Emerging technologies 2014 www.gartner.com 4 TIME TO BE PRODUCTIVE Large data hide true quantitative signal Large data generate spurious

446 views • 21 slides
Course intro, RE Overview, Requirement types Lecture 1, DAT230, Requirements Engineering Robert

Course intro, RE Overview, Requirement types Lecture 1, DAT230, Requirements Engineering Robert

Course intro, RE Overview, Requirement types Lecture 1, DAT230, Requirements Engineering Robert Feldt, 2012-09-04 tisdag 4 september 12 Who am I? Who are you? tisdag 4 september 12 What is Software Engineering? How different from Computer

982 views • 75 slides
CS 6360: Educational Technology Lecture 1: Overview Promise Why should you take this class?

CS 6360: Educational Technology Lecture 1: Overview Promise Why should you take this class?

CS 6360: Educational Technology Lecture 1: Overview Promise Why should you take this class? What is this class? How will you be evaluated? What are the first assignments? Promise Why should you take this class? What is

1.14k views • 60 slides
Build it, Break it, Fix it Build-it Lecture Prof. Eric Bodden Build It, Break It, Fix It SS

Build it, Break it, Fix it Build-it Lecture Prof. Eric Bodden Build It, Break It, Fix It SS

Build it, Break it, Fix it Build-it Lecture Prof. Eric Bodden Build It, Break It, Fix It SS 17 Today Introduction n Theoretical Part: How to Build Secure Software n Brief Problem Overview n Setup HowTo for Phase I n 2 Prof. Eric

610 views • 50 slides

More recommend