mimol91

package main

import (
	"encoding/json"
	"testing"
)

type foo struct {
	ID            string  `json:"_id"`
	Index         int     `json:"index"`

mimol91

JPG:
$ brew install jpegoptim
$ find . -name "*.jpg" -exec jpegoptim -m80 -o -p --strip-all {} \;

- PNG:
$ brew install optipng
$ find . -name "*.png" -exec optipng -o7 {} \;

mimol91

When Istio Meets Jaeger - An Example of End-to-end Distributed Tracing

Kubernetes is great! It helps many engineering teams to realize the dream of SOA (Service Oriented Architecture). For the longest time, we build our applications around the concept of monolith mindset, which is essentially having a large computational instance running all services provided in an application. Things like account management, billing, report generation are all running from a shared resource. This worked pretty well until SOA came along and promised us a much brighter future. By breaking down applications to smaller components, and having them to talk to each other using REST or gRPC. We hope expect things will only get better from there but only to realize a new set of challenges awaits. How about cross services communication? How about observability between microservices such as logging or tracing? This post demonstrates how to set up OpenTracing inside a Kubernetes cluster that enables end-to-end tracing between serv

mimol91

const I = x => x;
const K = x => y => x;
const A = f => x => f(x);
const T = x => f => f(x);
const W = f => x => f(x)(x);
const C = f => y => x => f(x)(y);
const B = f => g => x => f(g(x));
const S = f => g => x => f(x)(g(x));
const P = f => g => x => y => f(g(x))(g(y));
const Y = f => (g => g(g))(g => f(x => g(g)(x)));

mimol91

version: 2
jobs:
  build:
    working_directory: /go/src/github.com/your_company/your_app
    docker:
      - image: circleci/golang:1.10.0
    environment:
      - GOCACHE: "/tmp/go/cache"
      - DEP_VERSION: 0.4.1
    steps: