I'm curious about how the platform team approaches continuous learning and knowledge acquisition. Do they rely solely on post-mortems and incidents, or do they also incorporate insights from training? Are there any benchmarks for success?
Thank you so much for sharing the article; I really appreciate the presentation and concise description of the platform
This is a profoundly insightful blog. Complexities of managing Kubernetes, resonates deeply. It's interesting to see how these challenges manifest in real-world scenarios and the impact they have on team dynamics and innovation.
Liked the concepts described here which impact every single platform team. Do you see teams abandoning k8s because of the monotonous increase in its complexity as your infrastructure grows?
Burned by the shared responsibility model way more than we would have liked. AWS said that they will “take the muck away” back in 2011. I guess we are back to owning the muck now :)
I thought we were the only ones that had these issues :)
I wonder how other teams are solving the hiring vs automation challenges?
Thank you for sharing insights into the burning issues of platform engineers. Cloud complexity is an old problem that requires new solutions. Standardization and knowledge sharing will save both time and efforts. Good luck
Platform engineering has been a core theme with in cloud native community for last couple of years. Thanks for highlighting the systemic scalability and complexity challenges in platform engineering today. The CVE for availability is an interesting solution and could be a breakthrough in taming endemic complexity and human bottlenecks.