The core for asynchronous programming are the objects Task and Task<T>. Both of them are compatible with the keywords async and await.

First of all we need to identify if the code’s I/O-bound or CPU-bound.

• the code’s limited for external operations and waits for something a lot of time. Examples of this are DDBB calls, or a server’s response. In this case we have to use async/await to free the thread while we wait
• the code does a CPU-intensive operation. Then we move the work to another thread using Task.Run() so we don’t block the main thread.

async code vs parallel code

(!) Asynchronous code is not the same as parallel code (!)

• In async code you are trying to make your threads do as little work as possible. This will keep your app responsibe, capable to serve many requests at once and scale well.
• In parallel code you do the opposite. You use and keep a hold on a thread to do CPU-intensive calculations

async code

The importante of async programming is that you choose when to wait on a task. This way, you can start other tasks concurrently

In async code, one single thread can start the next task concurrently before the previous one completes.
(!) async code doesn’t cause additional threads to be created because an async method doesn’t run on its own thread. (!) It runs on the current synchronization context and uses time on the thread only when the method is active.

parallel code

For parallelism you need multiple threads where each thread executes a task, and all of those tasks are executed at the same time

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We can set pre-request scripts (run before the request) & tests (after execution) at several levels:

• Collection
• Folder
• Request

Snippets

Inside pre-request Script and Tests we have a SNIPPETS column with templates we may use for our code.

Get / Set variables

console.log("Hello world");

// work with local vars
let urlVar = pm.variables.get("protocol");
console.log("value for protocol: " + urlVar);

pm.variables.set("protocol", "http");
console.log(pm.variables.get("protocol"));  

// work with global vars
let globalVar = pm.globals.get("env");
console.log(globalVar);

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To test postman I use https://reqres.in. You can use it to learn how to write Postman tests.

Collections

Collections have metadata which you can set up. This includes:

• Authorization so you don’t need to set it for every single request.
• Variables, for variables only for this collection (so you don’t use environment vars).
• Collection tests.

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Hay un problema al intentar correr una imagen tuya propia en local con minikube. Minikube tiene su propio repositorio de imagenes y si no encuentra una imagen alli, la intenta descargar siempre del repositorio.

Solución

Set imagePullPolicy: IfNotPresent

Run the following command:

eval $(minikube docker-env)
# build again the image
# try to run it again

Reference(s)

https://medium.com/bb-tutorials-and-thoughts/how-to-use-own-local-doker-images-with-minikube-2c1ed0b0968

Config

Azure

log-in into a tenant

az login --tenant 7f2c3a6b-e849-4d6f-b65d-1c0ef8b0f41c

configure local kubectl .kube config file

az aks get-credentials --resource-group my-aks --name aksname --admin

(the –admin part is optional but useful)

Contexts & Namespaces

see all configured contexts

kubectl config get-contexts

configure a context with a default namespace

kubectl config set-context <context_here> --namespace=<namespace_here>
# example
kubectl config set-context my-aks-context --namespace=aks-dev

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Data generated and used by Docker containers does not persist after restarts. We use Docker volumes to manage data to solve this issue. We use it to persist data in a container or share data between containers.

Volumes are the preferred mechanism for persisting data generated and user by Docker containers. Volumes are easier to back up or migrate.

Volumes are often a better choice than persisting data in a container’s writable layer, because a volume does not increase the size of the containers using it. The volume’s contents exist outside the lifecycle of a given container.

We have 3 volume types:

Anonymous volumes

Helpful to persist data temporarily. If we restart our container data is still visible. It doesn’t persist when we remove the container. Not accessible by other containers. They’re created inside /var/lib/docker/volume.

Example file:

version: '3.8'  
services:  
  db:  
    image: mysql  
    restart: always  
    environment:  
      MYSQL_ROOT_PASSWORD: root  
      MYSQL_DATABASE: test_db  
    ports:  
      - "3306:3306"  
    volumes:  
      - /var/lib/mysql

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Steps to go from a docker-compose file, to build an Image out of the file, upload it to DockerHub, and run it with Kubernetes (minikube).

Set up

Install Kompose

# linux
curl -L https://github.com/kubernetes/kompose/releases/download/v1.22.0/kompose-linux-amd64 -o kompose
chmod +x kompose
sudo mv ./kompose /usr/local/bin/kompose

Clone App and Host It into DockerHub

Clone the files, go to the directory where your Dockerfile is and run:

# mariocodes is my DockerHub username
# kubernetes-custom-java-maven-app is the name of the repo I created at DockerHub
docker build -f Dockerfile -t mariocodes/kubernetes-custom-java-maven-app .

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(Oficial Doc)

Technology to quickly set up a Kubernetes cluster locally to learn how to use Kubernetes.

Installation

How to install on a fresh Ubuntu installation:

Install prerrequisites and kubectl

sudo apt-get update && sudo apt-get install -y apt-transport-https curl

curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -

echo "deb https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee -a /etc/apt/sources.list.d/kubernetes.list

sudo apt-get update
sudo apt-get install -y kubectl

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STATUS CrashLoopBackOff

CrashLoopBackOff and no log appears. This happens as the container has no command to run so it start up and then immediately exits.

Give your image a command.

more here

apiVersion: v1
kind: Pod
metadata:
  name: twocontainers
spec:
  containers:
  - name: container1
    image: python:3.6-alpine
	command: ['sh', '-c', 'echo cont1 > index.html && python -m http.server 8082']
  - name: container2
    image: python:3.6-alpine
	command: ['sh', '-c', 'echo cont1 > index.html && python -m http.server 8083']

Relational

SQL

SQL Cheat Sheet
SQL Triggers & Stored Procedures
SQL Views & Materialized views
SQL UNION ALL

PgSQL Functions

PgSQL Functions (Stored Procedure)

MySQL

MySQL Administration
MySQL User Privileges

No-relational

Mongo

MongoDB

ElasticSearch

ElasticSearch

i18n is just a nomenclature for Internationalization. i18n involves, among other things, the ability to display translated content. It prepares a digital product for localization by for example, separate the content into strings so they are ready to be translated and delivered.

The same goes for L10n. This is a nomenclature for Localization. L10n involves translating content, adapting graphics and finalizing the producto for each regional market.

Reference(s)

https://www.oneskyapp.com/blog/i18n-need-to-know-internationalization/