data-driven devops: mining machine data for 'metrics that matter' in a devops workflow
TRANSCRIPT
Copyright © 2016 Splunk Inc.
Mining Machine Data for ‘Metrics that Matter’ in a DevOps Workflow
Abstract (Hidden)
IT organizations are increasingly using machine data – including in DevOps practices – to get away from ‘vanity metrics’ and instead to generate ‘metrics that matter’. These metrics provide visibility into the delivery of new application code and the business value of DevOps, to both IT and business stakeholders.
Machine data provides DevOps teams and others – including QA, secops, CxOs and LOB leaders – with meaningful and actionable metrics. This allows stakeholders to monitor, measure, manage, and continuously improve the velocity and quality of code throughout the software lifecycle, from dev/test to customer-facing outcomes and business impact.
In this session Andi Mann, chief technology advocate at Splunk, will share core methodologies, interesting case studies, key success factors and ‘gotcha’ moments from real-world experiences with mining machine data to produce ‘metrics that matter’ in a DevOps context.
DevOps is a Culture of Empathy & Sharing
INTEGRATION
COLLABORATION
COMMUNICATION
BETWEEN DEV AND OPSTO DELIVER BETTER SOFTWARE, FASTER
METHODS FOR IMPROVING
Shared Feedback Enables ‘The Three Ways’
Gene Kim, “DevOps Cookbook” and “The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win.”
Empowered DevOps Teams
Empathy - more than understanding
• Feel your teammates’ pain
• Understand their work and your impact
Empowerment - more than making decisions
• Be responsible in decisions, activities
• Be accountable to your team of teams
DevOps Workflow is Becoming Complex and Opaque
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Build(Jenkins, Bamboo)
Code(Git,
MS-TFS)
Plan(Jira, Rally)
Test/QA(Cucumber, SonarQube)
Stage(Pivotal,
AWS)
Release(Jenkins, Octopus)
Data Center
Device Data
Engagement Data
Config(Puppet, Ansible)
Monitor(NewRelic, Dynatrace)
Cloud Services Network Services
www/HTTPData
Social Sentiment
Wire Data
Application Data
Continuous Integration (CI) / Continuous Delivery (CD)
Site Reliability Engineering
Business Impact Monitoring
API ServicesSecurity/Compliance
DevOps complexity raises risk of failure● Slower Speed
● Longer MTTR
● Lower Quality
● Reduced Agility
● Poor Visibility
● Hard to Scale
● Increased Waste
● Impaired Collaboration
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DevOps
From Hype Cycle for Application Services 2015, Gartner Group, July 2015, Betsy Burton, Philip Allega, http://www.gartner.com/document/3096018
From every tool, every process, every component, on-prem or off
The One Constant: Machine Data
Common Data Fabric
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API
SDKs UI
Other ToolsEscalation/
Collaboration
Visibility Across the Whole Dev Lifecycle
Plan Code Build Test/QA Stage Release Config Monitor
Common Data Fabric
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API
SDKs UI
Server, Storage. N/W
Server Virtualization
Operating Systems
Infrastructure Applications
Mobile Applications
Cloud Services
Other ToolsTicketing/Help
Desk
Custom Applications
Visibility Across the Whole Ops Environment
API Services
Machine Data From DevOps Tools
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Provisioning and Config Metrics
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Machine Data from QA/Pre-Prod/Staging
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Machine Data from Release Servers
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Machine Data from Infrastructure Systems
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Machine Data from Database Servers
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Machine Data from Customer Systems
What do you measure and why?
I’m working super hard!!
That’s my stapler.
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Yeah, but … … what are you
achieving?
I’m gonna need you to come in Sunday.
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Daily Active Users?
Installs?
Downloads?Sales?
DevOps Metrics that Matter
Culturee.g.
• Retention
• Satisfaction
• Callouts
Processe.g.
• Idea-to-cash
• MTTR
• Deliver time
Qualitye.g.
• Tests passed
• Tests failed
• Best/worst
Systemse.g.
• Throughput
• Uptime
• Build times
Activitye.g.
• Commits
• Tests run
• Releases
Impacte.g.
• Signups
• Checkouts
• Revenue
Gartner’s DevOps ‘Metrics that Matter’
Gartner Inc., Data-Driven DevOps: Use Metrics to Help Guide Your Journey, 29 May 2014 G00264319, Analyst(s): Cameron Haight | Tapati Bandopadhyay
IDC’s DevOps ‘Metrics that Matter’
What Are Your ‘Metrics That Matter’?
Finding Your Metrics That Matter
Work from business backwards
Mine realtime machine data
Close the feedback loops
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Outcomes
Measurement drives Feedback loops
Velocity
Deliver on time & on budget
IT is delivering on
time, on budget
IT and Business Leaders
Impact
Deliver code for business needs
IT is achieving
business goals
IT and Business Leaders, Customers, Staff
Show you when you deliver. And when you don’t.
Quality
Deliver the quality you promised
We deliver a quality
experience for users
Dev and Ops Organizations
Measurement identifies ‘Waste’
Plan
Develop (UI)
Develop (Db)
Develop (M’ware)
Develop (Backend)
SecurityTest
Monitor
Build(Prod)
Architect
Secure/Comply
DeployAccept
UnitTest
Document
Cap Plan
Train
Feedback
IntegrationTest
Configure
System Test
Launch
CAB
Develop(APIs)
Budget
Build(Dev)
Mgmt/Tooling
W
W
W
W
W
W
W
W
W
16 40 52 35 96 40 48 24 --8 2 5 6 8 2 12
Measurement Ensures Transparency
• Release when ready, not a date!
• Best / worst developers
• Best / worst providers
• Impact of new code on ops
• Impact of new code on biz
Measurement Enables Continuous Improvement
Defect Information
CapacityPlanning
Quality Standards
Enhancement Requests
Integration Requirements
Acceptance Metrics
Service Levels and KPIs
Application Development Test and Acceptance Production
BuildCodePlan Test/QA Stage Release Config Monitor
InfrastructureDependencies
Measurement Improves Quality
Code quality scans Static security scans
White BoxDeveloper checks in code
Automated Acceptance Tests
Dynamic Security Scans
Black Box
“Chaos Monkey” tests
Test Fail: Return
Test Fail: Return
X
X
Production
QA Prod Pattern
QA Pattern Library
Test Pass: Promote
Test Pass: Promote to Production
Pattern library used for test and
QA
Measurement Accelerates Velocity
Pivot & improve with Continuous Insights
Product Managers identify new opportunities
Continuously delivered to market
… and Auditors are “happy”
Measurement Aligns Business Impact
Fast-feedback loop for actionable commercial insights
So You Can Innovate at Market Speed
BUSINESS DEV/OPS CUSTOMERS
HOW IS OUR:
• Security?
• Quality?
• Stability?
• Performance?
• Compliance?
HOW IS OUR:
• Market Launch?
• Feature Usage?
• Marketing Changes?
• Prioritization?
• Customer Sat?
Summary
Metrics that Matter Drive Better Feedback Loops
Improve Application Velocity
Visibility across silos, tools, and processes
exposes bugs and bottlenecks so you
can remediate, iterate, and innovate
faster.
Improve Application Quality
Track quality across multiple teams,
tools, systems, and service providers, so you can find and fix more issues before
production
Improve Application Impact
Real-time analytics correlates
application delivery with business goals,
so you can drive better experience and iterate faster
Sources/Additional Reading● splunk.com/DevOps - Resources on Splunk for DevOps incl. case studies, customer stories, partners, products, videos, etc.
● dev.splunk.com – Resources for developing with or on ther Splunk platform, incl. SDKs, API Docs, guides, etc.
● blogs.splunk.com – Check the ‘DevOps’ and ‘Ansible’ tags for specifics, including how to deploy Spunk w/ Ansible
● splunkbase.splunk.com – Splunk add-ons and applications incl. Ansible Tower App for Splunk and 1000+ more
● DevOps Review 2016: Accelerating Innovation, Computing Research UK, July 2016
● 2016 State of DevOps Report, DevOps Research and Assessment
● The DevOps Cookbook, John Allspaw, Patrick Debois, Damon Edwards, Jez Humble, Gene Kim, Mike Orzen, and John Willis
● The Phoenix Project, Gene Kim, Kevin Behr, George Spafford
● Data-Driven DevOps: Use Metrics to Help Guide Your Journey, Gartner Inc. 2014, Cameron Haight and Tapati Bandopadhyay
● Metrics that Matter, Mark Michaelis, IntelliTect
● DevOps and the Cost of Downtime: Fortune 1000, IDC
● DevOps Best Practice Metrics: Fortune 1000 Survey, IDC, 2014
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Copyright © 2016 Splunk Inc.
Thank You!
Andi Mann
Chief Technology Advocate, Splunk
@andimann