Is AI The New DevOps

This is an Ignite talk delivered at DevOpsDays Singapore on 22 March 2024

Transcript

1. Is AI the new DevOps? Harish Pillay h.pillay@ieee.org @harishpillay@floss.social
2. Why Do I Care? You care because you've shown that you are forward looking and radical enough to adopt "best current practises"
3. What does AI offer to DevOps that DevOps itself doesn't already do? • Tasks such as predictive analysis and CI/CD.
4. • Tasks such as predictive analysis and CI/CD. • A DevOps raison d'etre - to automate software development processes, reducing manual intervention and increasing productivity. What does AI offer to DevOps that DevOps itself doesn't already do?
5. • Tasks such as predictive analysis and CI/CD. • A DevOps raison d'etre - to automate software development processes, reducing manual intervention and increasing productivity. • AI becomes another tool in the suite of tools for DevOps practises. What does AI offer to DevOps that DevOps itself doesn't already do?
6. • Analyze large amounts of data from various sources to identify anomalies and potential issues before they become critical. Can AI help DevOps teams with monitoring and incident response?
7. • Analyze large amounts of data from various sources to identify anomalies and potential issues before they become critical. • AI-enabled tools helping DevOps teams to respond more quickly and effectively to incidents, reducing downtime and improving customer experience. Can AI help DevOps teams with monitoring and incident response?
8. • Analyze large amounts of data from various sources to identify anomalies and potential issues before they become critical. • AI-enabled tools helping DevOps teams to respond more quickly and effectively to incidents, reducing downtime and improving customer experience. • All of these do not absolve the responsibilities of the developers. They are part and parcel of the DevOps process with the whole notion of "human-in-the-loop" in play. Can AI help DevOps teams with monitoring and incident response?
9. • AI chatbots and virtual assistants can facilitate communication between team members, automate repetitive tasks, and provide real-time feedback. Provided these chatbots are trained on corpus specific to the organization so that relevance is maintained. AI enhancing collaboration and comms within DevOps teams
10. • AI chatbots and virtual assistants can facilitate communication between team members, automate repetitive tasks, and provide real-time feedback. Provided these chatbots are trained on corpus specific to the organization so that relevance is maintained. • It is possible that collaborative AI tools helping teams to work more effectively together by providing suggestions and recommendations based on data analysis. AI enhancing collaboration and comms within DevOps teams
11. • AI chatbots and virtual assistants can facilitate communication between team members, automate repetitive tasks, and provide real-time feedback. Provided these chatbots are trained on corpus specific to the organization so that relevance is maintained. • It is possible that collaborative AI tools helping teams to work more effectively together by providing suggestions and recommendations based on data analysis. • These tools need to be reviewed and re-assessed periodically for currency and accuracy, otherwise mistakes could be magnified unwittingly. AI enhancing collaboration and comms within DevOps teams
12. • Yes! Does AI require a cultural shift in DevOps practises?
13. • Yes! • Embrace the use of AI/ML to stay competitive and deliver quality work in a quick enough manner that surpasses today's throughput. Does AI require a cultural shift in DevOps practises?
14. • Yes! • Embrace the use of AI/ML to stay competitive and deliver quality work in a quick enough manner that surpasses today's throughput. • This might involve investing in new tools, upskilling team members, and adopting new processes and workflows. Does AI require a cultural shift in DevOps practises?
15. • Ethical concerns around data privacy, security, and bias. Ethical considerations and potential risks
16. • Ethical concerns around data privacy, security, and bias. • Teams need to ensure that they are using AI responsibly and transparently, with clear policies and guidelines for data collection, storage, and usage. Ethical considerations and potential risks
17. • Ethical concerns around data privacy, security, and bias. • Teams need to ensure that they are using AI responsibly and transparently, with clear policies and guidelines for data collection, storage, and usage. • Active and continuous review of these tools are a necessary and required action. Ethical considerations and potential risks
18. • Not adopting AI tools by DevOps teams risk sidelining them in favour of teams that do use AI tools. Summary
19. • Not adopting AI tools by DevOps teams risk sidelining them in favour of teams that do use AI tools. • Lean forward and learn all that you can to discover the areas that DevOps can benefit for AI tools and change your culture. Summary
20. • Not adopting AI tools by DevOps teams risk sidelining them in favour of teams that do use AI tools. • Lean forward and learn all that you can to discover the areas that DevOps can benefit for AI tools and change your culture. • Have fun! Summary Thank you! Harish Pillay, h.pillay@ieee.org @harishpillay@floss.social