Improve the Impact of DevOps
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The document discusses enhancing DevOps-driven application delivery through machine data insights, highlighting the challenges of low visibility and code quality issues leading to business impacts. It emphasizes the importance of analyzing machine data from various sources to improve collaboration and performance tracking across departments. Ultimately, it argues for developers' focus on innovation rather than on creating monitoring tools, promoting the accessibility of machine data through Splunk software.
Improve the Impact of DevOps
- 1. Improve the Impact of DevOps — Driven Application Delivery with Machine Data Insights Stela Udovicic, Product Marketing, Splunk
- 2. MOBILE & CLOUD FIRST SOFTWARE-DEFINED WORLD INTERNET OF THINGS CONTINUOUS APP DELIVERY
- 4. Expectations Are High! No Pressure!
- 5. COMPLEXITY
- 6. Low Visibility Leads to Long MTTR
- 8. What is the Business Impact?
- 9. Do You Understand Security Risk?
- 12. Where Does Machine Data Come From?
- 13. Code Repository Automation Systems Application Monitoring CI / Build Servers Project & Issue Tracking Dev/Test/ Staging Servers InfrastructureCloud Explore Visualize Dashboards ShareAnalyze
- 15. Deliver Faster With Analytics
- 16. DEV - BUILDS OPS - PERFORMANCE
- 17. r MOBILE APP CRASHES $$$ AT RISK DUE TO API LATENCY $$$ AT RISK DUE HTTP ERRORS CRASH RATE BY OS VERSION Know The Business Impact
- 18. Practice Empathy With Insight
- 19. “Developers can focus on innovation and not on building monitoring tools.” “Web Ops can track performance of releases in pre-prod, prod and in QA” “Gather all data, and it starts looking like one big system, instead of a bazillion teeny ones that hate each other” Really, eh?
- 21. Relax and Enjoy the Journey Stela Udovicic, Product Marketing, IT Markets Splunk software makes machine data accessible, usable and valuable to everyone Try for free: http://www.splunk.com/free-trials Twitter: @stela_udo Blog: blogs.splunk.com/author/sudovicic/
Editor's Notes
- #3: We are experiencing a digital revolution everywhere around us. Mobility and IoT are pushing old boundaries into the cloud. With new software-defined everything, applications are delivered continually.
- #4: You the DevOps practitioners are at the center of this revolution. Business demands you to be agile and iterate faster in order to succeed. While at the same time you need to create a quality product.
- #5: Gartner currently places DevOps at the peak of inflated expectations. How can you avoid falling to the trough of disillusionment. What are the risks which can bring you down?
- #6: Complexity is your archenemy. The old systems are not going away quickly. In the new stack, containerized world you lack visibility into build pipeline with ever growing number of tools from code definition to test to production.
- #7: Lack of visibility across app delivery slows everyone. Troubleshooting that piece of code that resulted in increased production latency takes time. While your customers are switching to competitor's site.
- #8: When you don’t know how your code behaves across the build pipeline, bugs go into production. Can you connect the JIRA task with the build tag that brought the site down? What was the code coverage against that feature?
- #9: Do you know which code push increased revenue? Which one resulted in abandoned carts? In which branch you need to invest resources?
- #10: As you are integrating open-source piece in your products, is your SECOPS team involved from the get go? Are you doing vulnerability analysis as an afterthought? Does it take two days for them to get back to you?
- #11: Does everyone know how much resources the new build will consume? Are your IT and dev teams talking about same metrics and using a common language? How does the app availability in production relates to network outage?
- #12: We are seeing a growing evidence that using analytics to mine and explore machine data is that bright light. It is giving you visibility across the entire build pipeline.
- #13: Machine data comes from behind API endpoints, containers, logs, sites, mobile apps, databases, even streaming network data! You get access to all data without worrying about compliance issues.
- #14: Machine data is a digital trail from all your systems. It helps you explore, visualize and share insights between different teams. It is a strong glue for your app delivery.
- #15: To get machine data to do the work for you, start simple – and log. Time stamp your events, use key value pairs, rotate and don’t spam the log. Don’t build monitoring tools – focus on business innovation instead.
- #16: From code definition to production, having insight for all your teams leads to less bugs, faster testing, faster releases, less production issues and accelerated innovation.
- #17: When you know how your code behaves in all stages, you can catch bugs early in the dev test cycle, before they impact customers. Everybody knows it is never the code, but machine data can help you prove or fix that.
- #18: You booked a weekend ski trip, skipped a few QA tests and pushed the new build on Friday. Will all hell break loose on Monday? When business metrics are directly tied to app prod performance and back to a particular build you can enjoy your weekend. CREATIVE Can we shaw a small chart below each of the titles (from my original picture) I also need to show the title “know the business impact” – that is a very important message
- #19: Know the performance of your teams. Reward top performers and help others, assign resources, invest in training and sharing knowledge. Machine data can help you easily manage teams and projects.
- #20: And here are some quotes from DevOps folks like you. Focus on innovation, don’t re-invent the wheel, track releases, start seeing the big picture of your app delivery.
- #21: And to summarize, use analytics to help you deliver quality code faster while knowing exactly what the business impact is. And with that our journey ends
- #22: Come chat with us at our Splunk booth. Grab the coolest T-shirt in the industry.