DevOps and Splunk
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This document discusses how Splunk can help organizations with DevOps practices through concise 3 sentence summaries: Splunk allows organizations to increase application delivery velocity by providing continuous insights to devops teams from planning through monitoring. It also improves code quality by enabling code quality scans, security scans, and automated acceptance tests across the development lifecycle. Splunk further drives impact by providing visibility across infrastructure, applications, services, and tools to give insights across the entire IT environment.
DevOps and Splunk
- 1. Copyright © 2015 Splunk Inc. DevOps and Splunk Hal Rottenberg, Staff Practitioner
- 2. Why DevOps?
- 3. “DEVOPS IS A SUPERSET, NOT A SUBSET”
- 4. How Shall We Get There? Culture Data Analysis Continuous Improvement 4
- 5. How?
- 6. INCREASE VELOCITY IMPROVE QUALITY DRIVE IMPACT Improve the Impact of Application Delivery
- 7. 7 API SDKs UI Server, Storage. N/W Server Virtualization Operating Systems Infrastructure Applications Mobile Applications Cloud Services Other Tools Ticketing/Help Desk No rigid schemas – add in data from any other source. Custom Applications Visibility Across the Ops Environment API Services
- 8. 8 API SDKs UI Other Tools Escalation/ Collaboration No rigid schemas – add in data from any other source. Visibility Across the Dev Lifecycle Plan Code Build Test/QA Stage Release Config Monitor
- 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
- 11. Use Case Deep Dives
- 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
Editor's Notes
- #5: - You’ve heard the culture story before, let’s go over that briefly
- #7: 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
- #9: 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.
- #10: 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
- #11: 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