As it relates to Pricekite.io, I've already moved on from this topic, and you won't see anymore blogs about it here. I'm currently deep into navigating the byzantine spaces of the cloud provider product catalogs to pull out serverless computing prices.
But, since I'm pretty sure there will never be a price spike, and since none of the dire predictions ever came true, it is worth considering why.
I have heard at least 3 reasons why we were going to run out of IP Addresses. Here are they are, and here are the reasons they haven't and won't happen:
People - with so many people in the world, and so many of them being online, we will run out of IP addresses because individuals (needing to carve out their digital homesteads) will use them up. Why did it not happen? The rise of online platforms allow people to join the online community without a traditional website and everything that comes with it. Facebook, Twitter, Pintrest, Medium, GitHub, Wix, etc. - you don't need a domain name or an IP address to be online with these services.
Businesses - Businesses, even more than people, need to be online so that people can find them and they can make money. Why did it not happen? Platforms are a part of this. Many business have Facebook pages or Google Sites and that is it, no IP address needed. Also, today you are able to create a web presence outside of a platform and you don't need an IP address to do it. Pricekite for instance has a unique domain and 2 subdomains, but because of cloud based development and neat DNS tricks it does not need an IP address.
IoT Devices - The idea here is that with billions and billions of connected devices we will run out of IP v4 addresses. Why did it not happen? IoT devices mostly don't use public IP addresses, which is as it should be. There's no reason for your refrigerator to be on the public internet (and therefore need a public IP address). It's dangerous enough having it on your home wifi with an internal address. Internal addresses are pretty much infinite, so the IoT devices aren't putting any pressure on the IP address space.
OK, that's it for my thoughts on IP Addresses. Look for more information on compute prices in the near future.
As part of my recent and ongoing interest in the price of IP Addresses, I'm putting together a site to get live reads on the prices from the 3 big cloud providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
The site is now live with live data from GCP and is called pricekite.io. The prices for AWS and Azure are current, but do not refresh live from web services. The code is on GitHub.
A few observations and thoughts from the first part of this development:
I am currently stuck on the Azure implementation because of permissions. I know the least about Azure permissions, and they turn out to be quite complicated. I have followed the tutorials, but still it doesn't work. By contrast the GCP permissions are very simple to set up and work very cleanly, while allowing you to control access quite granularly.
This appears (on the surface) to be an arifact of legacy Active Directory. Microsoft needs to support a lot of older models that they have developed over the years for large clients, and can't simply abandon the ways of the past. In Google's case they have only the security and permission model developed for GCP with no legacy headaches to worry about. Such is the price of success.
GCP Pricing Details
Under the covers of GCP's pricing platform there are some interesting things to be aware of.
All of the items (and there are many of them) have the ability to be priced at a level of billionths of a dollar, or other currency.
Items are priced by:
Units - whole units of currency. Such as the USD or other currency.
Nanos - fractional units of currency equal to 1 billionth of the unit.
Take, for instance, our friend the old, reliable IP v4 Address. In this case, for unused addresses thay are priced at:
0 units and 15,000,000 nanos per hour
This means, that each unused address costs:
$0 + 15,000,000/1,000,000,000 per hour
Or in plain English: $.015/hour or $7.2/month.
Of course the fascinating thing here is the ability to control very fine grained level of pricing. Also, there is evidence that in the future they will be charging per second for some resources. Though I don't believe they do this today.
Next I am going to dive into the AWS implementation and leave my Azure frustrations behind. I'll post another update when I get the AWS pricing working.
A few years ago I saw an article about IP v4 addresses and how IoT was causing us to run out of them quickly. At the time it seemed odd, because I knew that you could get them for nothing, or next to nothing, from every cloud provider.
If we were really running out, wouldn't you expect to pay something for them? Wouldn't supply and demand dictate that they couldn't be given away for free?
But perhaps this is really starting to happen now.
I just received an email from Google Cloud that, perhaps, There's No Such Thing as a Free IP Address Either (TNSTAAFIAE).
From the email:
First, we’re increasing the price for Google Compute Engine (GCE) VMs that use external IP addresses. Beginning January 1, 2020, a standard GCE instance using an external IP address will cost an additional $0.004/hr and a preemptible GCE instance using an external IP address will cost an additional $0.002/hr.
In addition, there are also price increases at Azure, though not in the classic resource deployment mode.
Here are the spot prices today for single static IP addresses (based on a 30 day month):
I ordered my AWS Deep Racer about 6 months ago, when it was supposed to be ready in March. At long last, I'm expecting to get it this week.
If you aren't familiar, Deepracer is Amazon's 1/18th scale robotic self-driving (toy) car. It uses reinforcement learning (a variation of machine learning) to teach the car about driving and help it to complete various courses.
Here is what the car hardware looks like:
The hardware was originally supposed to be out earlier this year, but has been somewhat delayed.
In the meantime I've been working with the simulation tool on AWS - AWS Deepracer. So far, I've managed to train a model to complete one of the easier tracks every time.
I'm pretty excited and looking forward to having the actual hardware. I'm probably not ready for the Deepracer League yet but I am having fun with it.
So far, the cost of running the AWS Robomaker simulation jobs (used for training and evaluating models) is not too expensive. I'll have to see what I spend over the coming weeks, it appears to be $10-$15/day for a few training and simulation runs a day, but that is based on a pretty small sample size.
I was very pleased with Exadel's performance in a recent Forrester Wave™.
We participated in the Midsize Agile Software Development Service Providers, Q2 2019 Wave from Forrester. We were named a Leader in the report and given the highest score in the Current Offering category.
It was really great to work with all of our Agile experts here at Exadel. We worked hard to put together our response and talk about the exciting Agile software development work that we do for our clients and ourselves.
Exadel has been doing Agile development for a number of years and it was great to get to talk about our Agile capabilities. Our Scrum Masters really know their stuff, and it was cool to get recognition for this.