The idea to take the FOCUS specification as baseline is indeed good.
The talk's topic is original, and the exposition clear. However the approach explained seems over engineering the solution to the talks's problem.
First of all, cloud costs managements of a multi-cloud initiative is a super-niche problem: costs control for a cloud vendor is a niche, GCP / Oracle are a niche, so costs control for other than AWS or Azure is a super-niche.
Secondly, the fact a technology is "exploding" it is not a sufficient condition to use it like the salt. LLMs are not appropriate to perform a conversion from one schema to another schema: ontologies for instance could make a better job and costs for development, maintenance are surely lower. To not mention the costs of inference of a 70B neural network used to convert one field in another with an accuracy that in the best case is 90%. And it is not neither discussed the impact of wrong conversion given by the LLM. And the costs for guard railing and monitor the results of LLM.
In my opinion, it should be revisited the approach involving LLMs as totally unnecessary, but the idea of collecting all the measures and the costs in order to take data-driven decisions is really interesting.
Caso d'uso davvero interessante e un sacco di lezioni apprese sul campo spiegate con la cultura giusta a mio avviso. Non sono riuscito a cogliere del tutto vantaggi e differenzianti a livello tecnico rispetto altre soluzioni, ma la mia curiosità è stata stimolata.
I found very inspirational this talk. The importance of adequate training is always undervalutaed at least in Italy, where the principle "sink and swim" is very common.
The blameless culture is fundamental, especially in tech and siloed organisations.
Io ho faticato molto a seguire il "senso" di questa talk, secondo me molto interessante. Avrei forse capito meglio (ma sono fatto male io, me ne rendo conto) se ci fosse stato un caso d'uso concreto (healthcare, finanza, retail) dove i requisiti di policy guidavano e facevano spiegare scelte e strumenti.
Questo è un argomento molto interessante, soprattutto in questi tempi. Tuttavia, molti aspetti del "dopo" della produzione (guardrailing, drift detection, lifecycle) io li ho visti poco/niente discussi. Cosi come l'aspetto dei costi l'ho visto un po' troppo poco discusso: tutte opportunità per sentirci raccontare altre cose su questo interessantissimo tema.
I liked this talk, even the level of abstraction was high and the intention was to give an inspirational talk, I've found many concrete points in my daily work (FinOps consultant). Really appreciated.
One of the best talk today. As it was in Italian, I switch language.
Lo speaker, a sua detta newbie, è stato davvero bravo, non annoiando mai pur entrando in qualche tecnicità. Si capiva la lunga esperienza in gitlab. Avevo, a cavallo del 2019-20 utilizzato Gitlab-CI con Kubernetes, ma poi avevo lasciato perdere in funzione di Jenkins proprio per i motivi che aveva spiegato bene. Ora cambia tutto! Sicuramente una comunità da tener d'occhio. Bravo, perché non c'è bisogno di scomodare argomenti buzz per dare concretezza.
I didn't know Crossplane. I liked the idea to operate infrastructure through kubernetes API. The examples were intelligible. The talk stimulated my curiosity. Cool.
Very well scoped talk. I loved the vision and the actionable hints/suggestions that gave.
Very interesting talk. For sure realtime/online ML is a really interesting topic related to observability and large scale application. The talk focused on the platform and it was a bit difficult for me to switch from the general approach presented and the concrete examples. I think I'll re-watch the video!