Merge pull request #22 from leongc/main

discuss/2024-december.txt

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+Date and Time: 17 December 2024
+
+Topics discussed:
+
+OpenAI Kubernetes failure Dec 11
+https://status.openai.com/incidents/ctrsv3lwd797
+[Quick takes on the recent OpenAI public incident write-up – Surfing Complexity](https://surfingcomplexity.blog/2024/12/14/quick-takes-on-the-recent-openai-public-incident-write-up/)
+- It was fun to use a well-written incident report from a different company to ask questions of our local cluster team
+- Control Plane can create brittleness. E.g. people claim about AZ robustness, but often AWS control planes run in us-east-1, so even if people "don’t deploy to us-east-1" they can still be vulnerable to failures in that AWS region because of AWS control plane
+- Designers often overlook the control plane when designing robustness for their systems
+- Question to stimulate wider design thinking: "if you lost access to the system, how would you restart with just a key to the datacenter?"
+
+LLM-based automation to manage infrastructure and its impact on safety
+- Known uses of LLMs have been a buddy or assistant
+- Seen proposals to have LLM power decision making. Haven’t seen stories of anyone doing this
+- We know LLMs have non-deterministic behaviors.
+- When this happens, what will be the consequences for safety and reliability? For understanding the incidents?
+
+Did seasonal holiday spending affect anyone?
+- could automate scaling. but not databases. cannot reshard under load; that requires additional capacity. 
+- Use historical, not current data to predict seasonal load + lead time.
+incidents might be more damaging to reputation and revenue than the cost of over-provisioning
+- live adjustment to prices is similar to control plane capabilities on top of the primary functionality
+

discuss/index.md

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 ## Summaries of recent discussions
 
+* [2024-December](2024-december.txt)
 * [2024-January](2024-january.txt)
 * [2023-October](2023-october.txt)
 * [2023-September](2023-september.txt)

discuss/stats.txt

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 2023-08-15: 25 attendees, 41m average duration
 2023-09-19: 36 attendees, 68m average duration
 2023-10-18: 25 attendees, 46m average duration
-2024-01-16: 20 attendees, 46m average duration
+2024-01-16: 20 attendees, 46m average duration
+2024-09-17: 18 attendees, 35m average duration
+2024-10-15: 4 attendees, 44m average duration
+2024-11-19: 8 attendees, 44m average duration
+2024-12-17: 5 attendees, 56m average duration