Viewing Sizing Recommendations for Instances
cloud.google.com
cloud.google.com
Last I checked there was no advice on instance size. I've seen one or two, nothing meaningful.
There are lots of advice for reserving instances though, and they are extremely poor. Listening to them would be a good way for us to waste $10k/month :D
Checks the Amazon Elastic Compute Cloud (Amazon EC2) instances that were running at any time during the last 14 days and alerts you if the daily CPU utilization was 10% or less and network I/O was 5 MB or less on 4 or more days.
As far as why this may benefit google: while a customer will pay the same regardless, that means there are less resources in GCPs overall pool of potential machines that others can use. And to support the overall capacity of all their customers, Google needs more machines to handle them all. I'm guessing Google would rather have most of their machines active, as building out less racks/datacenters is probably better for the bottom-line overall.
Google started with a dominant search platform. They don't have that luxury with Cloud.
Google used to have a near monopoly on solving hard CS problems, with an army of very very very smart CS grads. They could produce software that no other company could.
These days, many other companies have invested in growing their army of top tier CS devs, and so they are able to make software equally as impressive.
Slight oversimplification, but Google's had basically S3/GCS and Hadoop since early 2000s, and basically Docker + Kubernetes for the past 10. This translates into real-world edge.
For example, how many big data tools have any one of the 15 characteristics of BigQuery that I described at [0]? Or how many companies have inter-data center networking that gives you a Petabit of bisectional bandwidth, described at [1], or how many cloud providers have live migration, custom VMs, or insane RAM-like local SSD? Or how many PaaS offerings can sustain a behemoth like Snapchat? Or a NoSQL that scales to 56 million qps with just a handful of engineers [2] ??
Edit: To add more color. In days past, Google would release papers (GFS, MapReduce, Bigtable, etc). With Google Cloud Platform we can just externalize these services (with a bit of customer-friendly bits like isolation, pricing, etc). Bigtable, BigQuery (Dremel), PubSub to name a few.
(clearly biased, since I work at Google)
[0]https://medium.com/p/6654841fa2dc
[1]https://cloudplatform.googleblog.com/2015/06/A-Look-Inside-G...
[2]https://cloudplatform.googleblog.com/2016/03/financial-servi...
Except... Customer service for cloud platforms is terrible. Not only is there an image problem. The fact that there is almost a blog post about Google Cloud Service screwing over a customer and just flat not communicating happens every 2-3 months.
Best, Terrance
However, having used Big Query extensively at my startup, getting external data into it via Google Cloud Storage was a royal pain in my balls.
My broader point, is that Google was able to disrupt the Ad industry because it dominated web search by way of having a large number of exceptionally brilliant engineers. In 2016, that is no longer true--many other big (and small) players have invested in hiring their own equally brilliant engineers.
From my experience, most issues with loading data stem from just data parsing, or trying to make batch load behave like stream load (we have an api for that too).
And, one of the things I mention in my article, unlike any other database, batch ingest into BigQuery is entirely free, as in not competing with query capacity one bit.
More annoying that loading data into S3 for RedShift?
Heh. "We've established enough foothold to compete with EC2 therefore we're preparing to pull an App Engine
I work for Google Cloud.