This one was painful. Yes, I have a bit of a Microsoft aversion, but I tried to keep an open mind. Read the full description of my Azure adventure. Expensive, apparently no IPv6, slow disk IO, and I couldn't figure out block storage options. Definitely not for me.
然後在測試 Azure 時的評語就更酸了：
Oh Azure! This one is going to get a bit ranty. I Spent a good 20 minutes clicking around the provisioning Web UI. To be fair, it is more geared to people needing to provision a lot of servers. Doing a single one like this is not the target audience as far as I can tell. But still, instead of presenting a couple of standard options and a way to build your own custom config, Azure gives you 92 options (depending on which region you select):
I also got super lost trying to figure out what it would cost to bring the VPS up to 500 GB of persistent storage. And then to make things even more confusing, when I started the virtual machine creation process and came to the "Choose your virtual machine size" step, I got a bunch of different options not included in the above list with most of them listed as "Not Available" including both the A4 v2 and F4 options I had so carefully located.
然後還有奇怪的 agent 在跑：
The Azure VPS also had the heaviest provisioning agent of all the ones I tested. It looks like it is doing a heartbeat once per second and doing a (non-ssl) GET request to an IIS server upstream asking it for a "GoalState". I listened and checked what the IIS server responded with. The response from the management server is in the GoalState addendum below. It is mostly self-explanatory, I think.
The most important and obvious difference between TTD and rr is that TTD is for Windows and rr is for Linux (though a few crazy people have had success debugging Windows applications in Wine under rr).
TTD supports recording of multiple threads in parallel, while rr is limited to a single core.
On the other hand, per-thread recording overhead seems to be much higher in TTD than in rr. It's hard to make a direct comparison, but a simple "start Firefox, display mozilla.org, shut down" test run on similar hardware takes about 250 seconds under TTD and 26 seconds under rr.
Amazon Web Services now offers an AWS Deep Learning AMI for Microsoft Windows Server 2012 R2 and 2016.
然後 driver 與常用的東西都包進去了：
The AMIs also include popular deep learning frameworks such as Apache MXNet, Caffe and Tensorflow, as well as packages that enable easy integration with AWS, including launch configuration tools and many popular AWS libraries and tools. The AMIs come prepackaged with Nvidia CUDA 9, cuDNN 7, and Nvidia 385.54 drivers, and contain the Anaconda platform (supports Python versions 2.7 and 3.5).
SQL Server 2017 is now available for Amazon EC2 instances running Red Hat Enterprise Linux (RHEL) 7.4 as an Amazon Machine Image (AMI) from the AWS Marketplace. With this release, you can now launch RHEL instances on-demand using SQL Server 2017 Enterprise License Included AMIs without having to bring your own license. SQL Server 2017 on RHEL 7.4 AMI is available in all public AWS regions starting today.
Also, Git wasn't designed for a codebase that was so large, either in terms of the number of files and version history for each file, or in terms of sheer size, coming in at more than 300GB. When using standard Git, working with the source repository was unacceptably slow. Common operations (such as checking which files have been modified) would take multiple minutes.