iinvest-backend

README

iinvest backend: Cloud-Native Microservice application

This project contains a microservice based application. The application is a web-based social networking application called " The iinvest platform" providing a privacy focused social network aiming to facilitate dialogue regarding financial literacy. Additionally, the platform provides users with the ability to utilize various data sources to both educate themselves in order to become more financially adept and make better investment decisions.

** This application demonstrates the use of technologies like Kubernetes/GKE, Stackdriver, gRPC, and OpenCensus** This application works on Kubernetes cluster (such as a local one), as well as Google Kubernetes Engine.

Service Architecture

Service	Language	Description
apigateway	Go	Exposes an HTTP server to serve the website. Does not require signup/login and generates session IDs for all users automatically.

Features

• Kubernetes/GKE: The app is designed to run on Kubernetes (both locally on "Docker for Desktop", as well as on the cloud with GKE).

• gRPC: Microservices use a high volume of gRPC calls to communicate to each other.

• Istio: Application works on Istio service mesh.

• OpenCensus Tracing: Most services are instrumented using OpenCensus trace interceptors for gRPC/HTTP.

• Stackdriver APM: Many services are instrumented with Profiling, Tracing and Debugging. In addition to these, using Istio enables features like Request/Response Metrics and Context Graph out of the box. When it is running out of Google Cloud, this code path remains inactive.

• Skaffold: Application is deployed to Kubernetes with a single command using Skaffold.

• Synthetic Load Generation: The application comes with a background job that creates realistic usage patterns on the website using Locust load generator.

  Installation

We offer three installation methods:

1. Running locally with “Docker for Desktop” (~20 minutes) You will build and deploy microservices images to a single-node Kubernetes cluster running on your development machine.

2. Running on Google Kubernetes Engine (GKE)” (~30 minutes) You will build, upload and deploy the container images to a Kubernetes cluster on Google Cloud.

3. Using pre-built container images: (~10 minutes, you will still need to follow one of the steps above up until skaffold run command). With this option, you will use pre-built container images that are available publicly, instead of building them yourself, which takes a long time).

Option 1: Running locally with “Docker for Desktop”

💡 Recommended if you're planning to develop the application or giving it a try on your local cluster.

1. Install tools to run a Kubernetes cluster locally:

   • kubectl (can be installed via gcloud components install kubectl)
   • Docker for Desktop (Mac/Windows): It provides Kubernetes support as noted here.
   • skaffold (ensure version ≥v0.20)

2. Launch “Docker for Desktop”. Go to Preferences:

   • choose “Enable Kubernetes”,
   • set CPUs to at least 3, and Memory to at least 6.0 GiB
   • on the "Disk" tab, set at least 32 GB disk space

3. Run kubectl get nodes to verify you're connected to “Kubernetes on Docker”.

4. Run skaffold run (first time will be slow, it can take ~20 minutes). This will build and deploy the application. If you need to rebuild the images automatically as you refactor the code, run skaffold dev command.

5. Run kubectl get pods to verify the Pods are ready and running. The application frontend should be available at http://localhost:80 on your machine.

Option 2: Running on Google Kubernetes Engine (GKE)

💡 Recommended if you're using Google Cloud Platform and want to try it on a realistic cluster.

1. Install tools specified in the previous section (Docker, kubectl, skaffold)

2. Create a Google Kubernetes Engine cluster and make sure kubectl is pointing to the cluster.

   gcloud services enable container.googleapis.com
   

   gcloud container clusters create demo --enable-autoupgrade \
       --enable-autoscaling --min-nodes=3 --max-nodes=10 --num-nodes=5 --zone=us-central1-a
   

   kubectl get nodes
   

3. Enable Google Container Registry (GCR) on your GCP project and configure the docker CLI to authenticate to GCR:

   gcloud services enable containerregistry.googleapis.com
   

   gcloud auth configure-docker -q
   

4. In the root of this repository, run skaffold run --default-repo=gcr.io/[PROJECT_ID], where [PROJECT_ID] is your GCP project ID.

   This command:

   • builds the container images
   • pushes them to GCR
   • applies the ./kubernetes-manifests deploying the application to Kubernetes.

   Troubleshooting: If you get "No space left on device" error on Google Cloud Shell, you can build the images on Google Cloud Build: Enable the Cloud Build API, then run skaffold run -p gcb --default-repo=gcr.io/[PROJECT_ID] instead.

5. Find the IP address of your application, then visit the application on your browser to confirm installation.

   kubectl get service frontend-external
   

   Troubleshooting: A Kubernetes bug (will be fixed in 1.12) combined with a Skaffold bug causes load balancer to not to work even after getting an IP address. If you are seeing this, run kubectl get service frontend-external -o=yaml | kubectl apply -f- to trigger load balancer reconfiguration.

Option 3: Using Pre-Built Container Images

💡 Recommended if you want to deploy the app faster in fewer steps to an existing cluster.

NOTE: If you need to create a Kubernetes cluster locally or on the cloud, follow "Option 1" or "Option 2" until you reach the skaffold run step.

This option offers you pre-built public container images that are easy to deploy by deploying the release manifest directly to an existing cluster.

Prerequisite: a running Kubernetes cluster (either local or on cloud).

1. Clone this repository, and go to the repository directory

2. Run kubectl apply -f ./release/kubernetes-manifests.yaml to deploy the app.

3. Run kubectl get pods to see pods are in a Ready state.

4. Find the IP address of your application, then visit the application on your browser to confirm installation.

   kubectl get service/frontend-external
   

(Optional) Deploying on a Istio-installed GKE cluster

Note: you followed GKE deployment steps above, run skaffold delete first to delete what's deployed.

1. Create a GKE cluster (described in "Option 2").

2. Use Istio on GKE add-on to install Istio to your existing GKE cluster.

   gcloud beta container clusters update demo \
       --zone=us-central1-a \
       --update-addons=Istio=ENABLED \
       --istio-config=auth=MTLS_PERMISSIVE
   

   NOTE: If you need to enable MTLS_STRICT mode, you will need to update several manifest files:

   • kubernetes-manifests/frontend.yaml: delete "livenessProbe" and "readinessProbe" fields.
   • kubernetes-manifests/loadgenerator.yaml: delete "initContainers" field.

3. (Optional) Enable Stackdriver Tracing/Logging with Istio Stackdriver Adapter by following this guide.

4. Install the automatic sidecar injection (annotate the default namespace with the label):

   kubectl label namespace default istio-injection=enabled
   

5. Apply the manifests in ./istio-manifests directory. (This is required only once.)

   kubectl apply -f ./istio-manifests
   

6. Deploy the application with skaffold run --default-repo=gcr.io/[PROJECT_ID].

7. Run kubectl get pods to see pods are in a healthy and ready state.

8. Find the IP address of your Istio gateway Ingress or Service, and visit the application.

   INGRESS_HOST="$(kubectl -n istio-system get service istio-ingressgateway \
      -o jsonpath='{.status.loadBalancer.ingress[0].ip}')"
   echo "$INGRESS_HOST"
   

   curl -v "http://$INGRESS_HOST"
   

Cleanup

If you've deployed the application with skaffold run command, you can run skaffold delete to clean up the deployed resources.

If you've deployed the application with kubectl apply -f [...], you can run kubectl delete -f [...] with the same argument to clean up the deployed resources.

Conferences featuring Hipster Shop

• Google Cloud Next'18 London – Keynote showing Stackdriver Incident Response Management
• Google Cloud Next'18 SF
  • Day 1 Keynote showing GKE On-Prem
  • Day 3 – Keynote showing Stackdriver APM (Tracing, Code Search, Profiler, Google Cloud Build)
  • Introduction to Service Management with Istio
• KubeCon EU 2019 - Reinventing Networking: A Deep Dive into Istio's Multicluster Gateways - Steve Dake, Independent

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