goTempM

goTempM is a full stack Golang microservices sample application built on top of the Micro platform. Note that the original goTemp, which is built directly on the go-Micro framework, is still available and can be found in the goTemp repo. It is worth noting that Micro itself uses go-Micro as its underlying framework.

In it current incarnation (this is wip), this mono-repo uses the following stack as backend:

• Golang as its main implementation technology
• Micro as the microservices platform running our services
• gRPC for inter-service real time communication
• NATS for Pub/Sub event driven communication
• multicast DNS for service registration and discovery
• PostgreSql for transactional data storage
• TimescaleDB time series DB used for historical audit data storage
• ArangoDBis a multi-model database used for master data storage
• Redis is used to cache data and reduce number of data requests to other services
• Vault for credentials management when running in Kubernetes

In terms of the web front end, the stack is as follows:

• Javascript as its main implementation technology
• Svelte is used as the compilation engine (via rollup)
• Sapper is the javascript framework
• Sveltestrap provides the css framework and is based on bootstrap
• Font Awesome to display icons in the application

As far as observability, the application uses:

• Prometheus scrapes metrics from the microservices, databases and broker
• Grafana provides graphic visualization of application metrics

Finally, for orchestration, the stack is as follows:

• Docker for creating application images
• Docker-compose to run the application
• Minikube to run the application in Kubernetes

Below is a diagram that displays the overall setup of the application:

In a nutshell. the application functionality is as follows in the backend:

• The frontend connects to the different services through the Micro API gateway
• For each service the frontend provides:
  • Search page
  • Detail page
• Additionally, the frontend provides:
  • Landing page
  • Login page
  • Register page
• Each service performs the basic CRUD operations to their underlying databases
• All services authenticate via the user service
• All completed CUD operations are forwarded to the NATS broker which in turn forwards the message to the auditing service. This service saves the data into TimescaleDB.
• Each service has a client which can be used to test all basic CRUD functionality

Starting the application

Note: At this time, starting multiple services in a row (which the startup scripts do) sometimes causes an error to be thrown. The details of the issue are described in issue 8. As such, portions of the startup scripts may have to be re-run manually to bring the application up fully.

Before running the application the first time:

• Clone the repository
• cd into gotempM/web/sapper
• Run the following command to generate the javascript dependencies.

    npm install

Running with the Micro Docker image

Prerequisites

Software

• Docker must be installed and running

Running the app

To start the application:

• Ensure that Docker is installed and running. Then, execute the following command from a terminal in the goTempM root folder:

   make microup

Depending on whether you have run the application before, docker may have to download all the dependent images (Micro, PostgreSql, TimescaleDB, Nodejs, etc). This may take a while depending on your internet connection speed. Once everything has been downloaded and started, you should see a message in the terminal indicating that the application is listening at localhost:3000. At that point, yo can open your browser and navigate to:

    http://localhost:3000

Additionally, observability tooling can be accessed at the addresses below

    Prometheus:  http://localhost:9090
    Grafana:     http://localhost:3001

To stop the application:

    make microdown

Running on Kubernetes (Minikube) using the Micro Helm chart

Prerequisites

Software

• Ensure Micro is installed on the host
• Docker must be installed and running
• Ensure that Minikube is installed and running
• Similarly, ensure that Helm is installed on the host.
• Install the Micro Helm Chart

Ingress

The application front end connects with the API gateway using via a K8s ingress resource. As such, the ingress addon must be enabled in Minikube. To enabled it, run:

    minikube addons enable ingress

Check the ingress is working using the command below. The command's results should include an entry for the ingress.

    kubectl get pods -n kube-system

Building and pushing images (optional)

Out of the box, the Kubernetes manifest will pull existing Bolbeck goTemp images for the front end and some of the DBs from Docker Hub. You are welcome to change the Kubernetes manifests in the ./cicd/K8s folder to pull your own images. To build your own image of the front end and push it to docker hub run the command below for each of the services:

    make hubpushcontext SERVICE=web FOLDER=web

where serviceName is the name of the service for which the image should be built folderName is the folder that contains the docker file used to build the service image

Note that Micro will automagically create and deploy the containers for the different services

Running

Enable Port forwarding:

    kubectl port-forward svc/proxy -n micro 8081:443

Note that the application itself does not need this port forwarding, this is only needed so that we can send commands to Micro and start the app.

Start application by running:

    make microk8sup

Once the application is deployed, check the address and host assigned to the ingress:

    kubectl get ingress -n micro

Note that it takes a couple of minutes for K8s to assign the IP to the ingress. As such wait for that happens before moving ahead.

If this is the first time running the app in Minikube: Grab the address & the host from the result of the command above, and add it to your /etc/hosts file:

    <ipAddress> gotempm.tst

Finally, access app:

     minikube service web -n micro

Vault integration

The microservices can be integrated with Vault when running in K8s to manage their credentials. To enable this integration, please first refer to the README in the ./vault directory to setup Vault and all the microservices secrets. Once that is configured, and the application is running, just execute :

    make vkubpatchdeploy

Once that completes, the microservices' credentials to the different dependencies (DBs, brokers,etc ...) can be managed in Vault.

Observability

Observability tools access while the application is running in K8s (with or without Vault):

• Prometheus: minikube service prometheus
• Grafana: minikube service grafana

Stopping the application

to stop the application, execute:

    make microK8sdown

Note: The port forwarding to Micro should also be stopped. Also, if the Vault Integration is enabled, and the VAULT UI is enabled, then the associated port-forwarding should be stopped as well.

Running with Micro locally

Prerequisites

Software

• Ensure Micro is installed
• Docker must be installed and running

Running

Start the micro server:

    micro server

Wait for the server to be up and ensure that you can access localhost:8080 before continuing to next step. Start the application:

    make microlocalup

Access the application in your browser at:

    http://localhost:3000

To stop the application, run:

    make microlocaldown

Repo organization

The project is organized in a way that each folder represents either a service, a database or a shared library package. Currently, we have the following:

• arangodb: Volumes mounted to the ArangoDB container as well as data initialization scripts
• audit: Audit service to collect and store historical audit information
• cicd : Holds files related to CI/CD and orchestration
• customer: Customer master data service
• diagramforDocs: Diagrams used in the readme documents
• globalCache : Enables Micro to use Redis as a cache store which can then be used in our services
• globalErrors: Generic errors shared package
• globalMonitoring: Generic monitoring utilities shared package
• globalProtos: Generic protobuf message definitions shared across packages
• globalUtils: Generic utilities shared package
• grafana: Grafana configuration and custom dashboard definitions
• micro : Hosts the custom Dockerfile that is used to run Micro.
• nats: NATS dockerfile and configuration
• postgres: Volumes mounted to the PostgreSQL DB container as well as data initialization scripts
• product: Product master data service
• promotion: Promotion service to track product discounts (this was the first service built)
• prometheus: Prometheus configuration and exporters
• redis: Volumes mounted on the redis container as well as config files (if any)
• timescaleDB: Volumes mounted to the Timescale DB container as well as data initialization scripts
• user: User and authentication service
• Vault: Scripts & policies needed to run the app in K8s with Vault
• web: application web frontend

Additionally, we have the following files in the root directory as well:

• .dockerignore: Files to be ignored when building service images
• .gitignore: Files to be ignored by git
• docker-compose: File controls the building of the different services and their dependencies
• go.mod and go.sum: Go modules control
• main.go: Not used for services yet
• Makefile: shortcuts to common actions
• Readme.md: Well... this file...

Services

We use Micro as the main GO microservices platform. Using Micro simplifies many of the tasks associated with building microservices including (but not limited to):

• Service discovery
• gRPC for inter service communication
• Built in async messaging (in our case used to set up pub/sub messages to NATS )
• Built-in data storage interface (in our case used to interact with Redis)
• API gateway:
  • Request routing
  • Load balancing
  • Automatic conversion of frontend JSON payloads to backend gRPC messages

Organization

Each one of the services has a similar structure:

• client: Contains a client service that calls the server service to perform multiple operations
• proto: Proto buffer messages and services definitions. Empty if service does not handle real time inter-service communication.
• server: Service that performs a number of actions like interacting with the DB
• Dockerfile: Build the image for the server service
• DockerfileCLI: Build the image of the client service
• docker-compose.env: Environment variable required to run the service when running the service with docker-compose
• docker-compose-cli.env: Environment variable required to run the client when running the client with docker-compose

Running individual services

Starting the service

The services must be started using Micro run. Since we are using the Dockerized version of Micro, we can start a service as follows:

If Micro is not already running:

make microserveup

This will start Micro as well as all the DBs used by goTempM. Get into the Micro container, if not in it already:

docker exec -it microservercont bash

Start the service:

make micro<serviceName>

where can be usersrv, auditsrv, customersrv, productsrv or promotionsrv.

Testing the service

Note: all the commands below must be run within the Micro container

To run some data through a service once it is started, we can run the service client:

micro run --name <serviceClientName> <serviceFolder>/client

where can be usercli, auditcli, customercli, productcli or promotioncli. For example, we could start the user client as follows:

micro run --name usercli user/client

This will bring up run the client service which will attempt to create,update and delete a user. The results will be printed to the log. To see the logs, run:

micro logs -f <serviceOrClientName>

The server user service will update the DB as necessary and send the updated information to the broker (NATS) so that the audit service may eventually store it in the time series DB. The audit service can be started using:

make microauditsrv

Databases Initialization

The project initializes each of the DBs and seeds them with tables and data. Data changes made at run time are automatically persisted using mounted volumes when running via docker-compose. See the folders for each DB for details as well as the docker-compose file.

Web front end

Our web front end is built with Svelte and Sapper which have some interesting benefits:

• Server-side initial rendering of our pages
• File based routing
• Smaller code base than other Javascript frameworks. Does more with less.
• Svelte translates the code to vanilla javascript. Thus, smaller application footprint than most frameworks
• Emphasis on component re-usability

Organization

The web application lives in the ./web folder. Since Sapper and Svelte generate multiple files and folders, we will just discuss the relevant folders below:

• sapper: The main folder containing the web app
  • src: This is where the bulk of the application resides
    • components: Contains re-usable Svelte components
    • globalUtils: Shared javascript utilities
    • routes: application routes to the different pages
    • client.js: This is a required file. It is used to start Sapper.
    • server.js: Used to configure the app with items like middleware and compression
    • template.html: Main page that contains our application. We added Bootstrap and Font Awesome CDN references in this page.
  • static: Holds static items
• Dockerfile: Used to build the docker image for the web app

Routes

All of our main routes are pretty standard in terms of organization. We will use the customer route (./web/sapper/src/routes/customer) as an example:

• index.svelte: Main customers search page that serves at localhost:3000/customer
• _searchGridSlot: Component holds the template for the search grid to be display in hte search page (index.svelte)
• new.svelte: Page to be displayed when user want to create a new customer. Displayed at localhost:3000/customer/new .
• [slug].svelte: Page to view and modify existing customers. Displayed at localhost:3000/customer/[customerid]
• _detail.svelte: Holds the gui and bulk of the logic for adding or editing customers. It is called by new.svelte and [slug].svelte .

There are three routes that do not share the structure above as they have very little functionality and thus are server by a single index.svelte component: root, register and login.

Kubernetes

The application configuration in K8s can be seen in the diagram below. Note that the diagram shows just one of the different microservices and its associated database. The configuration for all other microservices, beyond the shared ingress and API Gateway, is similar to the one depicted in the diagram. Note that Micro builds and spins out the service pods.

Notes:

• When running the application with Vault, the microservices secrets will be superseded by the secrets stored in Vault.
• The microservices, ArangoDB and NATS have Prometheus metric scrape endpoints built-in. On the other hand, Redis, PostgresDB and TimescaleDB use adapter containers to expose the data to Prometheus.
• To keep the diagram simple, the K8s services for the database, Vault, Prometheus and Grafana are not displayed in the diagram.
• Since Micro automatically manages the K8s objects for the microservices, exposing the metrics ports to Prometheus is done by patching the Micro created K8s services via service patches. The patches can be found under cicd/K8s/microservicesPatch

Organization

The K8s files live in the ./cicd/K8s folder, and is organized as follows:

• dbsAndBroker: Contains the manifests for all the databases and for the broker.
• Ingress: Manifest to create the ingress resource that allows the frontend, and the back end to communicate
• microservicesPatch: contains the manifests to open the ports required to scrape metrics from the microservices
• monitoring: holds the manifests to deploy monitoring resources (Prometheus, Grafana)
• Vault: Manifests to create the service accounts and patches to integrate the application with Vault
• web: Manifest for the web front end.

Note that within each of the folders, most related manifests are organized using a prefix. For example, all the front end related services start with the 'web' prefix.

Additional information:

Additional information can be found in the individual folders either in a readme.md or a doc.go file. Additionally, the Makefile contains many command samples that can be used for development.