In various chapters in the book we make references to demos and lectures that can be found on-line. Much of this is located in a Github site we keep for the book. Below are links to a few of these
- Chapter 6 (Containers) references is simple Dockerfile for building a trivial web site. The source code for that demo is linked here.
- In the Kinesis Array of Things example in the book there is a data file you need and a program that will send the events to Kinesis. This is illustrated in Notebook 18. The folder with more code and the data is Kinesis-spark-Aot.
- Chapter 7 (Scaling deployments) contains an MPI C program that sends a token down a line: You can find this program and a related ring version in the Github site at aws-hpc-cluster, along with a simple C program that show how to invoke a python program.
- The demonstration of the small microservice document classifier demo used the EC2 Container Service is also in the Github repo in directory aws-ml-container. This goes along with Notebooks 10 and 11.
- Chapter 7 (Scaling deployments) presents a Kubernetes example that uses a Celery program. There is no notebook for this example, but the basic components for the solution are in Github in file gcloud-container.
The slides for the 2017 IEEE Cloud Engineering Workshop are linked here.
- Tutorial Introduction (ppt) (pdf)
- Storage (ppt) (pdf)
- Virtual machines and containers (ppt) (pdf)
- Scaling, clusters and microservices (ppt) (pdf)
We have put together a container based on jupyter/all-spark-notebook with additional installed SDKs for Azure and AWS. The notebook is accurate as of 3/28/2017. However there is a self-signed certificate so you will need to accept security exceptions to run it. To invoke it with Docker do:
docker run -it -p 8888:8888 dbgannon/tutorial
and go to https://ip-of-host:8888 and login with password “tutorial”.