9. Increase App Delivery Velocity
DevOps Teams iterate with
continuous insights
Product Managers
identify new
opportunities
Code continuously delivered
to market
Auditors
have visibility
Customers
are happy
9
10. Improve Code Quality
Code Quality Scans Static Security Scans
White BoxDevelopers
check in code
Automated
Acceptance Tests
Dynamic Security
Scans
Black Box
“Chaos Monkey”
Tests
Test Fail:
Return
Test Fail:
Return
Production
QA Prod Pattern
QA Pattern Library
Test Pass:
Promote
Test Pass:
Promote to
Production
Pattern
library used
for test and
QA
10
12. 12
Application Development Testing and Artifact Collection Production
Feedback Services Regression Testing Constraint Analysis
Data
Mining
Requirements Code Development Build Environment Integration / DeploymentCode ReviewTesting and Artifacts
Data Model
Predictive
AnalyticsAnalytics Store
Enhanced
Search
Development & Operational Intelligence
13. Application Development Testing and Artifact Collection Production
App Dynamics Servicenow BSM ALM
VersionOne GitHub Enterprise Jenkins Build Server RunDeckVersionOneSonarQube Artifacts
BUILD TEST RUN
1 2 3 4 5 6
Application Dynamics ServiceNow HP BSM HP ALM
78910
Example Use Cases
14. Developer Values –
Operational Values –
Application Development - Use Cases Breakdown
Use Cases # 1
Availability of
Application
Use Cases # 2
Systematic
Availability
Use Cases # 3
Delivery Health
Score
Use Cases # 4
Data Quality
Scoring
Use Cases # 5
System Metrics
KPI
Use Cases # 6
Code Coverage
Vs Sprints Vs
Technical Debt
Use Cases # 7
Built Time Vs
Technical Debt
Use Cases # 8
Test Coverage Vs
Defects in QA
Use Cases # 9
Development
Activities Vs
Velocity
Use Cases # 10
Sprints Vs
Defects
15. Application Development Testing and Artifact Collection Production
APM Change Management ITOA Documentation
Atlassian Jira Atlassian Bitbucket Bamboo Bamboo / SaltStackSonarQube Artifacts
BUILD TEST RUN
1 2 3 4 5 6
ZipKin ServiceNow
78910
IT Service Intelligence Atlassian Confluence
Example Use Cases
Atlassian Jira
16. Developer Values –
Operational Values –
Use Cases # 1
Time to
Production
Use Cases # 2
Deployment
Analytics
Use Cases # 3
Health of
Deployment
Use Cases # 4
Application
Availability
Use Cases # 5
CT to FTE
Developer
Use Cases # 6
Automation Test
Coverage
Use Cases # 7
Bamboo Agent
Health
Use Cases # 8
Release Cycles &
Hours per
Project
Use Cases # 9
Salt Stack
Deployment
Monitoring
Use Cases # 10
Release
Management &
Version Control
Automation & Deployment - Use Cases Breakdown
17. Application Development Unit Testing Code Quality & Analysis
Metrics & Monitoring APM Automation Tests Deployment
Team Foundation Server Team City
BUILD TEST QA
1 4 5 6
Solarwinds Selenium Octopus
78910
Continuous Build Pipeline
2 3
Dynatrace
SPLUNK PLATFORM
Jasmine Tibco Custom Veracode NDepend
18. Developer Values
Operational Values
Continuous Build – Use Case Breakdown
Use Cases # 1
Build Pipeline
Build, Test, Run
Use Cases # 2
Monitor & Adapt
to Releases Cycles
Use Cases # 3
Release & Builds
Management
Use Cases # 4
Single Pane of Glass
(Cloud, Hybrid)
Use Cases # 5
Predictive Alerts
and Response
Use Cases # 6
Deployment
Frequency to
Velocity of Code
Changes
Use Cases # 7
Lead-Time and
Reaction to
Business Needs
Use Cases # 8
Failure Rates
Compared to
Sprints
Use Cases # 9
Backlogs
Management &
Resource
Allocation
Use Cases # 10
CI / CD End to End
Glass View
Notas do Editor
- You’ve heard the culture story before, let’s go over that briefly
When using Splunk to mine machine data our customers and prospects can
1) INCREASE APP DELIVERY VELOCITY
2) IMPROVE CODE QUALITY
3) INCREASE BUSINESS IMPACT OF APPLICATION DELIVERY
Splunk can provide insight across the entire application delivery lifecycle. Developers can search and visualize data from entire build pipeline and production environments without needing to access production machines.
Fast feedback obtained with analytics improves app delivery velocity. From code definition to production, having insight for all the teams leads to less bugs, faster testing, faster releases, less production issues and accelerated innovation.
Deliver end-to-end visibility across every DevOps toolchain component
Iterate faster with correlated insight across the application delivery lifecycle
Improve DevOps team efficiency by measuring and benchmarking release contributions
Pinpoint and resolve code issues before they impact customers .Find and fix production issues faster Use objective metrics to ensure code is operational and meets quality SLAs