Vubon Notes - Vubon Roy's Engineering Blog on Vubon Notes

Saga Pattern: Handling Distributed Transactions in Microservices

Wed, 03 Jun 2026 00:00:00 +0000

Whenever microservices enter a system design discussion, one question always comes to my mind:

What happens when a transaction succeeds in one service but fails in another?

Let’s take a payment system as an example.

Imagine a user initiates a $100 transfer. The workflow looks like this:

Transfer Service creates the transaction ✅
Wallet Service deducts $100 from the user’s balance ✅
Bank Service sends the transfer request ❌

Now we have a problem.

No-Op Update Pattern: State-Driven Idempotent Updates

Sun, 24 May 2026 11:00:00 +0000

After exploring idempotency keys, I came across another pattern that deserves more attention: the No-Op Update Pattern.

The idea is simple, but the mindset behind it is what makes it powerful.

Instead of treating every update request as something that must trigger work, you first ask a more important question:

Does this request actually change the state?

If the answer is no, the system should do nothing and return the current state.

System Design Interview: Partial Failure & Durability

Fri, 08 May 2026 00:00:00 +0000

After talking about idempotency, I thought I’d share another good follow-up question:

“What happens if your service crashes in the middle of a request?”

Let’s say:

transfer record inserted ✅
ledger update started ❌
database connection drops
service dies

Now you have partial data.

And in payment systems, partial success is usually worse than failure.

The first answer most people give #

👉 Use database transactions (ACID).

System Design Interview: Idempotency

Mon, 04 May 2026 11:00:00 +0000

Almost every candidate faces this question during a system design interview:

How do you handle duplicate transactions?

Most people answer: Idempotency key + Cache.

To be honest — that’s a good start.

But the real lesson comes when you build an actual payment system.

Duplicates are normal behavior #

In distributed systems, duplicates are not edge cases. They are normal behavior.

Duplicates can originate from anywhere:

client double-clicks
mobile retry on timeout
API gateway retries
reverse proxies
silent network failures
third-party timeouts

So the problem is not if duplicates happen.

System Design Interview Prep — Series Introduction

Mon, 04 May 2026 10:00:00 +0000

System design interviews are tough. Not because the questions are impossible - but because they’re open-ended, and most people don’t know where to start.

After years of building distributed systems in FinTech, I’ve been on both sides of the table. I know what interviewers are actually looking for, and it’s not buzzwords. It’s trade-offs, real-world thinking, and knowing why something works, not just that it works.

So I’m putting together this series — practical write-ups on the topics that come up again and again. No fluff, just the stuff that matters.

SOLID Principles with Python Examples

Sat, 03 Jan 2026 12:00:00 +0000

Let’s deep dive into SOLID principles. SOLID is a short form. It stands for

Single Responsibility Principle

Open and Closed Principle

Lisvok Sub situation Principle

Interface Segregation Principle

Dependency Inversion Principle

This is the meaning of the SOLID. In this article, I’m going to try to explain SOLID Principles in the simplest way so that it’s easy for beginners to understand.

The SOLID principles were defined in the early 2000s by Robert C. Martin (Uncle Bob). Uncle Bob elaborated some of these and identified others already existing and said that these principles should be used to get good management of dependencies in our code.

Fan-Out Fan-In in Golang — The easy way

Thu, 01 Jan 2026 00:00:00 +0000

These days, low latency isn’t “nice to have” — it’s table stakes. So let’s talk about the Fan-Out/Fan-In pattern and why it’s my go-to for faster APIs and background work. After 6+ years building FinTech systems, I’ll share a real example that makes the concept easy to digest and hard to forget. You’ll be able to plug it into your services right away.

But before the demo, let’s hit the basics.

How to Deploy Your Hugo Blog to GitHub Pages

Wed, 31 Dec 2025 06:45:00 +0000

If you want to publish a blog without paying for hosting? GitHub Pages is your friend. In this article, I will show you how to deploy a Hugo static site to GitHub Pages. Trust me, once you get it right, it’s super smooth.

Why Hugo + GitHub Pages? #

I was looking for a simple way to publish my blog. I don’t like to deal with WordPress hosting fees, database backups, or security updates. Hugo generates static HTML files—fast, secure, and free to host on GitHub Pages. What’s not to love?

How To Work A Card Network - Payment

Thu, 02 Mar 2023 06:53:33 +0000

For a long time, I did not write a single article. Suddenly, I thought I should write something about the financial system because I have been working with financial companies for four years already. The concept may be old, but there are still a lot of people who do not know how it works!

Python: Symbol is better than function call

Sun, 15 Sep 2019 21:24:56 +0000

Benchmarking Function Calls vs. Symbols #

[The time difference is from my Core-i3 machine; it may vary on yours.]

# Example 1
from timeit import timeit

print(timeit("my_tuple = tuple([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])"))
print(timeit("my_tuple = ([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])"))

# Output
# 0.3789963669996723
# 0.1345829190004224

# Example 2
print(timeit("my_set = set([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])"))
print(timeit("my_set = {*[1, 2, 3, 4, 5, 6, 7, 8, 9, 0]}") )

# Output
# 0.6751592210002855
# 0.547103707000133

You will see a probably trivial difference—but a difference is still a difference. Think about huge datasets; the cost adds up.

Hmm Python @Property

Tue, 11 Jun 2019 23:05:03 +0000

Hmm. I am thinking what is that? let’s deep a dive with me. Before I start I want to ask some questions myself.

What is @property in Python?
When should I use the @Property function?
How to use the @property function? In this article, you will understand what exactly the Python @Property does.

What is the Property in Python? In Python property is a built-in function. Property function is helping to modify class attributes and give backward compatibility. But you should have a basic concept of Python classes and method. Because of the @property is typically used inside one.

When should I use the @Property function? Assume, You create a class that store user bank account information like a bank account number and balance. Let's create the class

class Account:
 """ A basic class that store bank account information """

 def __init__(self, bank_account: str, balance: float):
 self.bank_account = bank_account
 self.balance = balance
 self.account_information = dict(bank_account=self.bank_account, balance=self.balance)

 def __str__(self):
 return f"Bank Account: {self.bank_account} - balance: {self.balance}"


account = Account("0004-0067894712", 1000.50)
print(f"account number: {account.bank_account}")
print(f"Current balance: {account.balance}")
print(f"Account information: {account.account_information}")

# Output should look like this 
account number: 0004-0067894712
Current balance: 1000.5
Account information: {'bank_account': '0004-0067894712', 'balance': 1000.5}

Now, from this account we transfer the fund what will we get after calling the account_information attribute? Let’s transfer the balance and call the account_information attribute of the instance.

Clock Arithmetic or Modular Arithmetic

Wed, 22 May 2019 00:29:56 +0000

image credit: slideplayer

6 + 9 = 3, Is this possible ?? Sometimes, we say this is a fallacy. But in Mathematics has an area that is called Clock Arithmetic or Modular Arithmetic.

A familiar use of the clock arithmetic is in the 12-hour clock. Let’s explain the example. Here 6 means 6 o’clock and 9 means 9 hours later it will be 3:00.

While I was studying in Mathematics at that time I was thinking this is totally bullshit, I could not apply anywhere. Seriously believe me. But I am proud of myself because I have completed my graduation in mathematics.

Experiment with GIN index of PostgreSQL DB

Thu, 04 Apr 2019 14:49:16 +0000

PostgreSQL provides the index methods B-tree, hash, GiST, SP-GiST, GIN, and BRIN. Users can also define their own index methods, but that is fairly complicated. In this article, I will discuss the GIN index. GIN index is a very useful index method for a query, count, etc.

Use cases GIN index:

Full-Text search(tsvector)
Array Data Type
JSONB

What is the Gin index? From the Docs

"GIN stands for Generalized Inverted Index. GIN is designed for handling cases where the items to be indexed are composite values, and the queries to be handled by the index need to search for element values that appear within the composite items. For example, the items could be documents, and the queries could be searches for documents containing specific words."

![GIN index diagram](/images/GIN-index-1024x597.jpg)

Image credit: Cybertec Postgresql Create test data

String in Python

Thu, 28 Mar 2019 06:47:23 +0000

In computer science string is a sequence of characters and characters can be Alphabet, Numeric, Alpha-numeric. In computer science string defined by " " or ‘’. Example

variable = "Hello Python"

Here “Hello Python” is a string value and variable is a variable of Hello Python string.

Everything in Python is an object. The string has few methods. I will discuss every method in this article.

#Method 1: Capitalize

str.capitalize()

Return a copy of the string with Capitalize format. Example: