Advancing DevOps practices with AI —lessons from AWS re:Invent

Zaizi

Computing DevOps Excellence Award nominee Emily reflects on her experience attending AWS re: Invent, where she explored the latest in AI and DevOps.

From the moment I stepped into the bustling halls of Las Vegas’ Venetian Convention Center, I knew attending AWS re:Invent would be a career highlight for me.

I’m proud to say that AWS awarded me the ‘AWS All Builders Welcome’ grant to attend the annual event in December. The grant gives underrepresented groups the chance to experience the re:Invent conference.

AWS selected only 400 people in the world for the grant, so I was incredibly grateful to receive the opportunity.  

No surprise that generative Al was a hot topic at the conference. But I’ll talk about one particular session that stood out: “Supercharge your DevOps practice with generative AI.”.

The session highlighted the AWS generative AI tech stack, including the awesome updates to Amazon Q Business and Amazon Q Developer. The talk emphasised how we can use AI to impact delivery and operations.

Supercharging DevOps with AI

On the delivery side, AI can accelerate engineering productivity, identify SDLC bottlenecks and reduce developer distractions.

We were shown a cool demo on writing efficient Jira tickets using AWS Bedrock. The demo walked us through the infrastructure behind the concept. It showed how they have trained an LLM to recognise what a ‘good’ ticket looks like vs a ‘poor‘ ticket. If the LLM deems it ‘poor’, the ticket is re-assigned to you with a comment explaining why it’s rejected.

This offers dual benefits: developers know every ticket contains all the necessary information, while delivery managers are confident the tickets have concrete acceptance criteria with full descriptions.

On the operations side, AI will improve code quality and reviews. The presenter demonstrated how AI can enhance monitoring and dashboards almost instantly compared to the time-consuming process of creating custom dashboards. Gen AI can also help streamline the incident response process — anomaly detection, sending real-time notifications, and making playbook recommendations based on past incidents.

We saw a fab demo of Amazon Q Developer identifying errors in the AWS Console and offering detailed analysis followed by recommendations. Some really cool stuff!

Along with the other events I attended, the session sparked many ideas for internal projects we’re doing this year, which will improve our productivity and efficiency. 

I want to say thank you to the AWS All Builders Welcome programme for this fantastic experience! I networked with amazing and inspiring people, gaining valuable connections and insights.

If you are eligible, I recommend applying next year. Applications open around June, so check the AWS website for updates!

Thanks for joining us! We’ll keep you informed with regular updates.

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