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GitHub Actions introduces native AI-powered workflow optimization

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(@david_jenkins)
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Joined: 7 months ago
Posts: 0
Topic starter  

Just saw this announcement and wanted to share with the community. GitHub Actions introduces native AI-powered workflow optimization

This could have significant implications for teams using Jenkins. What does everyone think about this development?

Key points:
- Improved performance
- Breaking changes to watch for
- Limited beta access

Anyone planning to adopt this soon?



   
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(@mark.murphy761)
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Joined: 12 months ago
Posts: 1
 

Resource consumption is a concern. What's your experience? Looking for real-world benchmarks if anyone has them.



   
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(@jason.brooks11)
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Joined: 2 months ago
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Just implemented this last week. Already seeing improvements!



   
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(@jennifer.bailey132)
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Joined: 11 months ago
Posts: 0
 

We implemented this using the following approach:
1. First step...
2. Then we...
3. Finally...
Results: significant improvement in deployment speed. Setup: Azure, ECS, 77 services.



   
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(@benjamin.taylor696)
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Joined: 4 months ago
Posts: 0
 

Pro tip: if you're implementing this, make sure to configure resource quotas correctly. We spent 2 weeks debugging random failures only to discover the default timeout was too low. Changed from 30s to 2min and all issues disappeared.



   
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(@donald.stewart436)
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Joined: 9 months ago
Posts: 1
 

Been using this for 6 months. Here's what I learned...



   
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(@david.johnson369)
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Joined: 10 months ago
Posts: 0
 

Consider the long-term maintenance burden before adopting.



   
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(@christine.carter463)
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Joined: 10 months ago
Posts: 0
 

Cautionary tale: we rushed this implementation without proper testing and it caused a 4-hour outage. The issue was memory leak in the worker. Lesson learned: always test in staging first, especially when dealing with authentication services.



   
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(@angela.nguyen556)
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Joined: 11 months ago
Posts: 0
 

For those asking about cost: in our case (AWS, us-east-1, ~500 req/sec), we're paying about $5000/month. That's 70% vs our old setup with ArgoCD. ROI was positive after just 2 months when you factor in engineering time saved.



   
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(@rebecca.brown460)
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Joined: 8 months ago
Posts: 0
 

Be careful with this approach. We had production issues.



   
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(@benjamin.taylor696)
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Joined: 4 months ago
Posts: 0
 

This aligns with our experience. Highly recommend this approach.



   
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(@katherine.nelson24)
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Joined: 4 months ago
Posts: 0
 

Cautionary tale: we rushed this implementation without proper testing and it caused a 4-hour outage. The issue was DNS resolution delay. Lesson learned: always test in staging first, especially when dealing with payment processing.



   
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(@jason.brooks11)
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Joined: 2 months ago
Posts: 0
 

Spot on. This is the direction the industry is moving.



   
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(@samantha.brown47)
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Joined: 1 year ago
Posts: 0
 

Pro tip: if you're implementing this, make sure to configure retry policy correctly. We spent 2 weeks debugging random failures only to discover the default timeout was too low. Changed from 30s to 2min and all issues disappeared.



   
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(@michelle.gutierrez269)
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Joined: 4 months ago
Posts: 1
 

For those asking about cost: in our case (AWS, us-east-1, ~500 req/sec), we're paying about $2000/month. That's 40% vs our old setup with ArgoCD. ROI was positive after just 2 months when you factor in engineering time saved.



   
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