In the first post, I discussed about the overhead that you have to pay for when working with Microservices. This time, I’m going to talk about another problem with Microservices. It is the problem of the distributed systems that you have to face with from the very beginning.


You have to deal with the problem of Distributed systems very early

Handling Data Inconsistency

A distributed system with a lot of small services followed by difference data storages means that there are no constraints between those data storages. In a traditional SQL database, this can be solved easily by adding foreign keys between tables and perform a cascading update/delete whenever you want to modify the data. Ensuring that constraint in a Microservices design is really challenging.

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It has been nearly 2 years since I started working at Agency Revolution, a team working on a software platform that utilizes Microservices architecture to build a highly scalable system for Automation Marketing. It comes with both pros and cons when building a Microservices system from scratch and I’m not for nor against Microservices. There are many articles and books on the Internet talking about the advantages of Microservices so I’m not going to write another post about the benefits of using Microservices. This post is just a summary of my experience and the difficulties after 2 years working with it as well as how we deal with those issues to get the most value of Microservices.


First, let me introduce a bit about the tech stack that we are using. We have been running our application on our private server for about 2 years before migrating to Google Cloud Platform. There are 3 types of service in the system. They are

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This post is the second part of the first post here. This post focuses on how to utilize RethinkDB Secondary Index in different use cases efficiently.


Some rules when using RethinkDB Indexes

RethinkDB Indexes, similar to Indexes in other database, are the trade-off between read and write performance. Therefore, the basic rules for RethinkDB Indexes are similar to other database.

  • Don’t create index if not necessary.
  • Don’t create index if the data set is small enough so that you can use the filter query.
  • Indexes require memory to process, be careful with tables that have a lot of indexes.
  • Indexes can slow down write operations significantly.
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It has been more than one year since my last post. But yeah, I’m still here, not going anywhere. This time, I write about the database that I have been working over the last one year at Agency Revolution, RethinkDB.


At Agency Revolution, we make heavy use of RethinkDB. Nearly everything is stored in RethinkDB. Probably at the time you are reading this blog post, that will not be true anymore and we have been utilizing other databases as well. However, as it’s still one of our main data storage, we used to have a lot of performance issues related to storing and retrieving data (and we still have until now). This blog post is to summarize how we use RethinkDB indexes to solve those problems as well as some use cases for different kind of indexes in RethinkDB.

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Why I need a Log trace

There are many logging libraries for Clojure and Ring out there which support basic logging per each request that Ring server handles. However, all of them produce multiple log entries per request, one when the request starts and one when the request ends. Also, they cannot log the steps happen inside the handler function’s execution. For example, with Ring-logger, the default setup logs:

  • an :info-level message when a request begins;
  • an :info level message when a response is generated without any server errors (i.e. its HTTP status is < 500);
  • an :error level message when a response’s HTTP status is >= 500;
  • an :error level message with a stack trace when an exception is thrown during response generation

If there are multiple requests that process at the same time, the log entries in the log file could be something like this

  • Starting request 1
  • Starting request 2
  • End request 2
  • End request 1

That’s hard for me unite all the logs into one place and search the all the related log information whenever debugging one specific request. There is also no way for me to track the flow of execution steps inside the handler function of that request. Although I can simply do (timbre/info "Start some database queries"), the problem than come back to the previous one

  • Starting request 1
  • Starting request 2
  • Start a query for request 1
  • Start a query for request 2
  • Write file for request 2
  • Write file for request 1
  • End request 2
  • End request 1

Hmmm. Something like this would be much better

  • [1] Starting request {id}
    [2] Start query to database
    [3] Found one record
    [4] Processing data
    [5] Finished request {id} in 20ms
  • [1] Starting request {id}
    [2] Start query to database
    [3] Exception: database down
    [4] Finish request {id} in 10ms

What I want is one single log entry per request with the trace of its steps so I can easily find out how the code works as well as where it can break, where it doesn’t function normally.

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Why React in place of D3?

So, I’m migrating my web app to full client-side rendering using React recently. The reason is that I mixed both server-side rendering and client-side render too much. At first, all the pages use server rendering (something like jinja2 template). However, as a consequence of the increase in interaction with user on the web app, I started to add more and more js code, which leads to the logic duplication in both backend and frontend. I decided to move all the rendering to React.js and that makes my life much easier dealing with all the DOM manipulation and two-way binding.

The only thing I need to deal with is the diagram that I implemented using D3.js before. I have been researching on the internet for a good solution and I was very closed to follow one of those tutorials, which suggests hooking D3.js rendering in React’s componentDidMount event (actually, most of the tutorials suggest that). Suddenly, one of my frontend friend recommended me throwing away D3.js for all those tasks. He said that React.js is very good at DOM manipulation stuff, why I have to mixed D3 inside that to lose all the flexibility of two-way binding, virtual DOM update,… Yeah, that sounds logical and I decided to give it a try, threw away all my old code and started in a fresh new React way. Of course, I didn’t D3.js completely, I still use it because of its supporting functions for calculating the diagram position and coordination.

Implement the Tree diagram in React.js

Okay, the first thing I need to do is to convert this old piece of code from D3 to React. The requirement is to draw a family tree like this. In contrast to my imagination, rendering the tree diagram using React is an amazingly effortless task.

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This post is written entirely on iOS on my iPhone and iPad, from many places, at several times, in different situations.

  • So… You don’t blog very regularly recently.
  • Hmm, I don’t have enough time!
  • Too busy on work?
  • Nope, just enjoying the fun of the youth that I have missed for years :D


During that, I waste a lot of time without actually doing any useful thing, mostly in waiting time, e.g waiting to my gf to be ready (oh the girl! 😅), waiting for my friends to come for a coffee or any other kind of waiting. I started to think about blogging on the go. However, the only thing that I have in thoses cases is my smart phone, an iOS powered one. And dealing with all those jekyll and git stuffs on a smartphone is really a big challenge.

Let’s make the impossible become real.

First obstacle: Git, of course

Coming from the terminal and Emacs world, I have never imagined how I would use git without them. But now I do :D

Working copy by Anders Borum is a quite good choice. You have the option to pay $14.99 in order to unlock the push feature. Actually, you have to pay. Who can use git without push feature :LOL:

For me, this’s quite adequate. All the steps to clone and push from Github are set up automatically, just input your credential and done. It just took me few minutes to get used to the UI. There are Git2Go at the same price, but I feel satisfied with this so I will leave Git2Go for the next chance.

working copy

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Conkeror is not a browser for everyone. It lacks many features that are waiting for the users to implement :D One of the issue you may find annoying when dealing with modern websites is the permission management. In other browsers, when the web page want to access current location information or request for camera recording, the browsers will pop up a small prompt to ask the user for allowance. However, in Conkeror, there is no such thing. This is how to make that possible

Currently, there are 4 kinds of permissions available, there are

  • audio-capture
  • video-capture
  • geolocation
  • desktop-notification

They are managed by the XPCOM nsIPermissionManager service. You need to access that through nsIComponentManager like this

const permissionManager = Components.classes[";1"]

Next, we need a function for prompting the user for which permission to enable or disable. This function will prompt for user to select which permission that they want to modify from the permissionsList

// List of web api permission
var permissionsList = [
{desc: "Audio Capture", value: "audio-capture"},
{desc: "Video Capture", value: "video-capture"},
{desc: "Geo Location", value: "geolocation"},
{desc: "Desktop Notification", value: "desktop-notification"}

// read permission from minibuffer
var readPermission = function(I) {
$prompt = "Select permission:",
$completer = new all_word_completer(
$completions = permissionsList,
$get_string = function(x) {return x.value;},
$get_description = function(x) {return x.desc;}
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Early Return in Clojure
  •  03 January 2016
  •  misc 

It’s better that you break your function into smaller ones, each does one simple purpose. Clojure is functional, isn’t it?

I’m just kidding. Sometimes it’s really hard to write such that code. Consider this example, I have a function for validating whether a string is a valid date time string. If it’s nil or blank, just skip it, otherwise, try parsing it to see if it’s okay.

(defn validate-date-time [date-time]
  (if (nil? date-time) true
      (if (blank? date-time) true
          (try (f/parse formatter date-time)
               (catch Exception e false)))))

Nested, nested and nested. If this is still simple and easy to see for you, try this one, need to check if the date time is between 1970 and 2030

(defn- validate-date-time [date-time]
(if (nil? date-time) true
(if (blank? date-time) true
(let [date-time (f/parse formatter date-time)]
(if (nil? date-time) false
(if (before-1970? date-time) false
(if (after-2030? date-time) false


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Recently, I have been working with projects using docker on Mac OS using docker machine. However, docker machine currently does not support fixed ip address for the machine so that everytime the virtual machine boots up, it is assigned with a new ip address. That makes accessing the docker containers running inside the machine a bit annoying since I have to use docker-machine ip command everytime to retrieve the ip of that machine and connect using the ip like

One simple solution for this is to define a fixed host name with the ip in the hosts file. This little shell scripts utilizes sed and tee to dynamically update the host name and ip of the docker machine everytime you boot up that vitual machine.

#! /usr/bin/env sh

# remove the old ip in hosts file
sudo sed -i "/\b\(hostname\)\b/d" /etc/hosts

# insert the new ip
echo "$(docker-machine ip machine-name) hostname" | sudo tee -a /etc/hosts

# set env variables
eval "$(docker-machine env machine-name)" OR $(docker-machine env machine-name)

You will need to replace hostname with the server name you want to assign to that docker machine and replace machine-name with the name of the docker machine.

This script will first find and remove the old entry that containing hostname in the hosts file. Next, it will append a new entry to the hosts file by evaluating the docker-machine ip command to get the new ip. Finally, updates all the environment variables for the current session for the docker and docker-compose to work properly. Keep in mind that you need to run this script using source for the docker-machine env command to take effect for the current shell.

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