HN user
Datadog can give organizations this functionality. You can pull in traces/spans, logs, metrics, and fully correlate across all of those different sources. Specifically for this blog post I would focus on APM + Log Management
(Full Disclosure: I work at Datadog)
The old Trending algorithm was definitely flawed, but it was simple, objective, and ever so slightly ruthless. It heavily skewed toward JavaScript and web development, but under-indexed a lot of backend and AI stuff.
Isn't that super contradictory? How is the old algorithm both objective AND skewed towards Javascript?
> *from my high school years, where I first tasted the god-like feeling of dominance over software*
WeWork has $33.9 Billion in Non-canceable lease commitments, and it's lease payments are increasing 100% YoY. I think that is the true ticking time bomb for this company. In a world where billion dollar losses (Uber) seems somewhat normal, those lease obligations are still outrageous, and those payments will come due eventually, whether they have the money or not. In 2019 they attributed over $800 Million to operating lease costs. Every year, based on static growth that will double, and my bet is that it may even more than double in some cases. This isn't so much a company as it is a race to light cash on fire and run away.
This just in: "Money doesn't buy happiness"
Is this truly new or even newsworthy information?
In my opinion the lesson to be learned here is not design related, but requirements related. Gather your requirements from your users before you implement a change, otherwise you're just working off of assumptions, and that's just bad practice.
If you have Product Management the failure was on them for not driving the customer need. Also, this is not me just scapegoating PM... it's actually what I do
Howard Husock, who wrote this article, is a VP for policy research at the Manhattan Institute. The Manhattan Institute is a conservative think tank with an agenda, so please take this column with a grain of salt. Howard stated his opinion but did not provide any evidence that reducing rent stabilization in New York would effect housing prices positively. Please keep this context in mind while reading this article, and stay informed.
Two points here really hit home with me about AWS (not in comparison to GCE though since I've never tried it).
1) Reserved Instances: I think the pricing model for this has become very outdated since the beginning of AWS, and it is definitely becoming cumbersome (and therefore scary) to use.
2) ELB + Traffic Spikes: I have tried (unsuccessfully) to pre-scale an ELB to prepare it for the traffic it was about to receive. I tried to pre-scale for this project 3 different times, in coordination with support and without them. I could not do it. Very frustrating.
I think these are all signs of extreme growth, and a strange organization of engineering units inside of AWS. However, as OP descried.. we are much to heavily invested in AWS to consider an infrastructure shift at this point
This paper seems to focus on old Apple hardware (the newest I can find is the iPhone 5s). I wonder what the results would be on Apple's newest hardware (6 and above).
This seems like a non-issue to me. If you're using an IaaS provider you should be treating the network as volatile from the get-go. This is the reason AWS has things like auto-scaling groups. You should be designing for failure in "the cloud"