noxasaxon

Learning Rust

Getting Started + Installation | Cheat Sheet

Table of Contents

1. How Do I Start Learning Rust?!
2. Ok, I Think I Know The Basics But How Do I Get Better?!
3. Rustlang Tooling
4. Helpful References Throughout Your Journey
5. The Rust Community
6. Recommended (but not free) Books & Courses

seva-ramin

#!/bin/bash

# pad base64URL encoded to base64
paddit() {
  input=$1
  l=`echo -n $input | wc -c`
  while [ `expr $l % 4` -ne 0 ]
  do
    input="${input}="
    l=`echo -n $input | wc -c`

antonyharfield

// Result is a superpowered enum that can be Success or Failure
// and the basis for a railway junction
sealed class Result<T>
data class Success<T>(val value: T): Result<T>()
data class Failure<T>(val errorMessage: String): Result<T>()

// Composition: apply a function f to Success results
infix fun <T,U> Result<T>.then(f: (T) -> Result<U>) = 
    when (this) {
        is Success -> f(this.value)

ServerlessBot

{
    "Statement": [
        {
            "Action": [
                "apigateway:*",
                "cloudformation:CancelUpdateStack",
                "cloudformation:ContinueUpdateRollback",
                "cloudformation:CreateChangeSet",
                "cloudformation:CreateStack",
                "cloudformation:CreateUploadBucket",

danidiaz

Vertical decomposition. Creating cohesive services

One of the biggest misconceptions about services is that a service is an independent deployable unit, i.e., service equals process. With this view, we are defining services according to how components are physically deployed. In our example, since it’s clear that the backend admin runs in its own process/container, we consider it to be a service.

But this definition of a service is wrong. Rather you need to define your services in terms of business capabilities. The deployment aspect of the system doesn’t have to be correlated to how the system has been divided into logical services. For example, a single service might run in different components/processes, and a single component might contain parts of multiple services. Once you start thinking of services in terms of business capabilities rather than deployment units, a whole world of options open.

What are the Admin UI

marwei

Kafka 0.11.0.0 (Confluent 3.3.0) added support to manipulate offsets for a consumer group via cli kafka-consumer-groups command.

1. List the topics to which the group is subscribed

kafka-consumer-groups --bootstrap-server <kafkahost:port> --group <group_id> --describe

Note the values under "CURRENT-OFFSET" and "LOG-END-OFFSET". "CURRENT-OFFSET" is the offset where this consumer group is currently at in each of the partitions.

2. Reset the consumer offset for a topic (preview)

ibraheem4

Installing Postgres via Brew

Pre-Reqs

Brew Package Manager

In your command-line run the following commands:

1. brew doctor
2. brew update

rspeer

theburningmonk

{
  "Comment": "How long AWS Lambda keeps idle functions around?",
  "StartAt": "FindIdleTimeout",
  "States": {
    "FindIdleTimeout": {
      "Type": "Task",
      "Resource": "arn:aws:lambda:us-east-1:{account_id}:function:when-will-i-coldstart-dev-find-idle-timeout",
      "Next": "RepeatOrNot"
    },
    "RepeatOrNot": {

ptarjan

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.