Architectural variation of hwx-pricing-engine using a grid of compute workers running on K8s.

It comprises of the following two components:

• compute-engine
• compute-manager

A simple client-server application written in Go. eodservice simulates the client that submits valuation requests to a grid of remote compute engine (server) instances - valengine. The valengine responds to requests by doing static pricing compute using QuantLib library through a Java wrapper library - computelib. The application uses the Kite micro-services framework for RPC.

eodservice breaks job submissions into batches with a max size of 100 (pricing requests) and the computelib prices them in parallel.

The compute-engine's docker image builds on top of a pre-baked image of the computelib.

FROM amolthacker/mockcompute-base
LABEL maintainer="[email protected]"

# Paths
ENV COMPUTE_BASE /hwx-pe/compute/

# Copy lib and scripts
RUN mkdir -p $COMPUTE_BASE
ADD . $COMPUTE_BASE
RUN chmod +x $COMPUTE_BASE/compute.sh
RUN cp $COMPUTE_BASE/compute.sh /usr/local/bin/.
RUN cp $COMPUTE_BASE/mockvalengine-0.1.0.jar /usr/local/lib/.

# Start Engine
ENTRYPOINT go run $COMPUTE_BASE/valengine.go

# Ports : 6000 (RPC) | 8000 (HTTP-Health)
EXPOSE 6000 8000

A web based management user interface for the compute-engine that facilitates following operational tasks:

• Submission of valuation jobs to the compute engine
• Scaling of compute
• Aggregated compute engine log stream

The backend is written in Go and frontend with AngularJS

The demo below will:

• First go through deployment specifics
• Submit a bunch of compute jobs
• Watch the pods auto-scale out
• See the subsequent job submissions get balanced across the scaled-out compute engine grid
• See the compute engine grid scale back in after a period of reduced activity

Demo - https://youtu.be/OFkEZKlHIbg

The application uses following Go libraries:

• Kite micro-service framework
• Go client for K8s
• Configuration definition support

• Start minikube

$ minikube start

• Provisiong infrastructure

  $ cd acs
  $ az group deployment create -n hwx-pe-k8s-grid-create -g k8s-pe-grid --template-file az-deploy.json --parameters @az-deploy.parameters.json
  

• Point kubectl to this K8s cluster

  $ az acs kubernetes get-credentials --ssh-key-file ~/.ssh/az --resource-group=k8s-pe-grid --name=containerservice-k8s-pe-grid
  

• Start the proxy

  $ nohup kubectl proxy 2>&1 < /dev/null &
  

• Deploy the K8s cluster

  $ kubectl apply -f k8s/
  

• Deploy compute-manager

  Clone the repo and add utils under src/compute-manager/scripts/linux to PATH
  

• Update the config/env.toml file to use the setup environment properties for compute-engine and Kubernetes

• Run the web server

$ cd ${path-to-compute-manager} 
$ go run ComputeManager.go

• Start the SSH tunnel

  Update SSH config as under scripts/ssh-config
  $ ./scripts/hwxadmin-tunnel.sh start
  

• Access the compute-manager Web UI

  http://localhost:8090/login
  

• Stop the SSH tunnel

  $ ./scripts/hwxadmin-tunnel.sh stop
  

• Destroy the K8s cluster

  $ kubectl delete -f k8s/
  

• Stop minikube

  $ minikube stop
  

• Teardown the AZ infrastructure

  $ cd acs
  $ az group deployment create -n hwx-pe-k8s-grid-create -g k8s-pe-grid --template-file az-teardown.json