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Kanban India 2024 | Sreejith NT and Harshith Bhaskar | AI in Flow improvement of DevOps
- 1. AI EnabledFlowEfficiencyinDevOps Sreejith NT & Harshith Bhaskar 2024 Kanban India Kanban India – 2024 https://www.kanbanindia.org
- 2. AGENDA • Significance ofFlow • DevOps Pipeline • Challenges and impediments in the DevOps Pipeline • AI tools in DevOps • Q&A Kindly note that we are opening a window to the available technology and advancement happening. Not a detailed tools review Kanban India – 2024 https://www.kanbanindia.org
- 3. FlowinKanban Fast smooth flowmeans our system is creating value quickly, which is minimizing risk and avoiding (opportunity) cost of delay, and is also doing so in a predictable fashion - Kanban University Flow = Regulated movement of work items through a system from start to finish. Flow Efficiency (%) = (Active work time / Lead time) x 100 Kanban India – 2024 https://www.kanbanindia.org
- 4. When is Floweffective ? Flow depends on what? Continuous improvement is key to optimizing flow. FlowinKanban Kanban India – 2024 https://www.kanbanindia.org
- 5. DevOps Pipeline Like anassembly line in car manufacturing ChallengesandimpedimentsinDevOpsPipeline Kanban India – 2024 https://www.kanbanindia.org Development Testing Continuous Integration Continuous Deployment Monitoring
- 6. Top 3 frustrationsfor developers • Amount of technical debt • Complexity of Tech stack. InsightsfromStackOverflow2024survey Top frustrations for developers • Amount of technical debt • Complexity of Tech stack. 61% of all respondents spend more than 30 minutes a day searching for answers or solutions to problems. Kanban India – 2024 https://www.kanbanindia.org
- 7. AIasacompanionforDevelopment Development with supportof AI Tools • Identify and fix errors • Optimize code • Give recommendations • Code analysis AI Tools for Software development • Github copilot • Microsoft copilot • Amazon Code whisperer Kanban India – 2024 https://www.kanbanindia.org
- 8. ExamplesfromGithubCopilot Highlight the codeand prompt to write unit test!! Done Create a new button component!!! Done Kanban India – 2024 https://www.kanbanindia.org
- 9. AIEnabledTesting AI Enabled Testing •Review / Prepare the functional test cases • Effort less test data generation • improve your testing efficiency by using the automated recommendations on creating reusable components Unit Test Integration Test Automated API Test System Test End to End Functional test Cyber Defence Test Kanban India – 2024 https://www.kanbanindia.org
- 10. AIenablingTestingExamples Kanban India –2024 https://www.kanbanindia.org Katalan • AI assisted Test case generation • AI assisted test case analysis Lambda Test • Kane AI testing assistant – Natural language based. • Log trends to forecast and monitor failures
- 11. AIenablingCI AI in CI •Automatedcode review •Code Analysis and debugging •Security scanning Examples •Gitlab Duo •Github Co pilot Kanban India – 2024 https://www.kanbanindia.org
- 12. ExamplesofAIenabledCI/CD Kanban India –2024 https://www.kanbanindia.org Calling out mis spelled variable name Giving suggestion on SQL
- 13. AIenablingDeployment With AI support •Modifying the Deployment Strategies as per need • Machine learning models can predict issues before they occur • Automated Rollbacks • Orchestration of deployment environments CD Tools with AI Capabilities • Harness • Spinnaker • GitLab Kanban India – 2024 https://www.kanbanindia.org
- 14. AIenablingContinuousMonitoring With AI support •keep the system robust • High availability • Forecast potential failures Monitoring with AI support - Examples • Dynatrace • New Relic • Splunk • Data dog Kanban India – 2024 https://www.kanbanindia.org
- 15. BenefitsandDrawbacks Benefits • Efficiency andspeed gain • Increased reliability and higher quality • Better insights and metrics Drawbacks • Careful consideration for having small batch size to reduce risk • Frequent upskilling will be required • Integrating new tools to existing environment can be challenging Kanban India – 2024 https://www.kanbanindia.org
- 16. • In conclusion,leveraging AI in DevOps can lead to substantial improvements in flow efficiency, collaboration, and overall productivity. • As technology evolves, embracing these innovations will be crucial for organizations aiming to stay competitive in the market. • Upskilling with AI tools in DevOps is a necessity Kanban India – 2024 https://www.kanbanindia.org
- 17. Thanks! DO YOU HAVEANY QUESTIONS? Kanban India – 2024 https://www.kanbanindia.org
- 18. TopAItoolsineachSDLCphases Develop Build/CI CD Test Deploy OperateMonitor • Copilots • AWS Code whisperer • Github Copilot • Gitlab Duo • Lambda Test • Katalan • Harness • Spinnaker • GitLab • Newrelic • Splunk • Dynatrace • Datadog Kanban India – 2024 https://www.kanbanindia.org
- 19. AIinthedevelopmentworkflow- Whereitisused? Kanban India –2024 https://www.kanbanindia.org Downloaded under the Open Database License
- 20. AIinthedevelopmentworkflow- Whereitisused? Kanban India –2024 https://www.kanbanindia.org Downloaded under the Open Database License
- 21. In the nextyear, most developers agree that AI tools will be more integrated mostly in the ways they are documenting code (81%), testing code (80%), and writing code (76%). Thinking about how your job and process changes over time, how integrated in your workflow do you anticipate AI tools you are currently using will be 1 year from now? Color Expectation for next year Much More integrated More integrated No change Less integrated Much less integrated InsightsfromStackOverflow2024survey Kanban India – 2024 https://www.kanbanindia.org Downloaded under the Open Database License
Editor's Notes
- #4 Predictable flow Less wait time Less bottlenecks ---- Limiting Work in Progress (WIP) Eliminating Waste / Addressing the bottle necks Task transfer in the team is supported by tools Reduce the time for active work items Reduce the time we spend on NOT working on work items Flow Efficiency: A Kanban Metric Introduction Track the total number of tasks entering the workflow and gather completed tasks over time. Shorten gap time between lead time and cycle time Eliminate bottlenecks Adjust workflow and improve team efficiency Lead time and Cycle Time and the importance of Flo... - Atlassian Community minimizing idle time, optimizing workflows, and addressing bottlenecks promptly.
- #5 Set of processes and tools dev and ops use to develop, build, test and deploy. Components of DevOps Pipeline Development Testing Integration & Continuous Delivery (CI/CD) Deployment Operations Monitoring Feedback & Improvement Development Waiting for peer reviews Need an expert suggestion on a functionality to be created Testing Identifying functional test cases Identifying negative test scenarios Test data creation Repetitive Testing Cycle CI Code branching management is complex when multiple teams are involved. Code merge conflicts CD Business impact of production deployment checks Manual Production readiness sign off Manual rollback if any issues Monitoring Write the scripts and build alerts Root cause analysis will require detailed log reviews
- #6 Online resources to learn coding – Top 3 Technical documentation Stack Overflow Written tutorials. Developers want more, more, more: the 2024 results from Stack Overflow’s Annual Developer Survey - Stack Overflow 2024 Stack Overflow Developer Survey AI | 2024 Stack Overflow Developer Survey
- #7 Leverage machine learning and large language models Static and dynamic code analysis Rule based systems
- #8 Pic Github Pic Key Roles and Responsibilities of the Software Development Team (orientsoftware.com)
- #9 Gen AI based; Mimic the peer review concept into testing; Katalon – A no code or Full code test automation software platform Lambda Test
- #10 Kane AI testing assistant – create, evolve and debug testing using natural language. AI-powered Test Case Generation: Katalon uses AI to automatically generate test cases based on existing user stories and requirements. This significantly speeds up test creation and improves test coverage. AI-assisted Test Case Analysis: Katalon analyzes test results and provides insights into potential issues, such as test failures or performance bottlenecks. This helps testers identify and address problems more efficiently.
- #11 AI enabled code review and documentation – Ex : Gitlab Duo Code commit support – AI can analyze commit histories, identify patterns and give recommendations Ex : Github Copilot Code merging – AI tools can predict merge conflicts and suggest recommendations – Ex : Github Code Analysis and debugging made easy Snyk – Identifies security vulnerabilities Code Guru – Code review recommendations Pyling – Static code analyzer Example : Gitlab and github
- #12 https://docs.github.com/en/copilot/using-github-copilot/code-review/using-copilot-code-review
- #13 Automated Canary Analysis: Spinnaker uses AI to perform automated canary analysis, which helps in assessing the performance and stability of new deployments by comparing them against a baseline. This ensures that only stable and reliable updates are promoted to production 1 . Predictive Analytics: AI-driven predictive analytics in Spinnaker can forecast potential issues in the deployment pipeline, allowing teams to proactively address them before they impact the production environment 1 . Anomaly Detection: AI algorithms in Spinnaker can detect anomalies in deployment metrics, such as unusual spikes in error rates or latency, enabling quick identification and resolution of issues 1 . Resource Optimization: AI helps optimize resource allocation during deployments, ensuring efficient use of infrastructure and reducing costs 1
- #14 AI enabled continuous monitoring helps to keep the system robust and keep availability high Uses historical and real-time performance data to forecast potential failures Actionable insights and recommendations, aiding in informed decision-making regarding infrastructure utilization. Manage risks associated with infrastructure performance using historical data
- #16 Faster development Increased productivity Visibility to address longer build time, improper resource handling & process slowdown Lessor incidents due to improved test coverage, increased code quality and anomaly detection
- #20 Developers want more, more, more: the 2024 results from Stack Overflow’s Annual Developer Survey - Stack Overflow 2024 Stack Overflow Developer Survey AI | 2024 Stack Overflow Developer Survey AI enables through Minimizing waste elements in the process Increase the automation Predictive analytics driven decision making Create and scale infrastructure based on the learning etc Manual errors are reduced Seamlessly deployed with predictable time
- #21 Developers want more, more, more: the 2024 results from Stack Overflow’s Annual Developer Survey - Stack Overflow 2024 Stack Overflow Developer Survey AI | 2024 Stack Overflow Developer Survey AI enables through Minimizing waste elements in the process Increase the automation Predictive analytics driven decision making Create and scale infrastructure based on the learning etc Manual errors are reduced Seamlessly deployed with predictable time