Oleksandr Andrushchenko

Oleksandr Andrushchenko

@oleksandr-andrushchenko

Software Engineer & Solution Architect

User info

Address: Missoula, MT 59808, USA
Followers: 4 | Following: 0 | Posts count: 9
Joined: Nov 03, 2025

About

Senior Software Engineer with 15+ years of experience building and optimizing scalable applications across healthcare, fintech, e-commerce, media, and logistics. Skilled in Python, JavaScript/TypeScript, PHP, cloud architecture (AWS Certified Solutions Architect & Developer), and database design (RDBMS, NoSQL). Delivered 30+ projects, improving performance, scalability, and reliability. Experienced in architectural decision-making and driving projects from concept to deployment.

Latest published posts

Scalability for Dummies — Part 1: Clones

Simple, practical guide to the first and often-most-used approach to scaling: making copies of what works. No PhD required — just common sense, a few engineering patterns, and awareness of the pitfalls.By Your Friendly Engineer · Part 1 in a short series on practicalscalability. Acloneis simply anot
Nov 24, 2025 0 0 scalability
Scalability for Dummies — Part 1: Clones

Software System Design Topics

Overview:A compact guide to the main topics you’ll encounter when designing modern software systems — principles, patterns, trade-offs, and practical concerns for reliable, scalable, and maintainable systems.Audience:engineers, technical leads, and architects looking for a structured checklist and a
Nov 21, 2025 0 0 software-system-design
Software System Design Topics

CAP Theorem in System Design

TheCAP theoremis one of the most fundamental principles in distributed system design. It defines the trade-offs between three key properties —Consistency,Availability, andPartition tolerance— and explains why it’s impossible to achieve all three simultaneously in a distributed data system. Formally
CAP Theorem in System Design

Consistency in System Design

Consistency is one of the foundational concerns when designing distributed systems. It answers the question:when a client reads data, how fresh or correct should that data be compared to the most recent write?Different applications have different tolerances for stale or conflicting data. This articl
Consistency in System Design

Availability in System Design — Principles, Patterns, and Practical Guidance

What availability means, how it's measured, architectural patterns that improve it, practical trade-offs, and how to validate an availability target. Availabilityis the probability that a system performs its required function at a given point in time. Practically, it answers the question:“Is the ser
Nov 11, 2025 3 0 availability
Availability in System Design — Principles, Patterns, and Practical Guidance

Scalability, Availability & Stability Patterns

Modern software systems must handle rapid growth, unpredictable load, and unexpected failures — all without compromising user experience. Three key pillars define such systems:scalability,availability, andstability. Each comes with its own design patterns and trade-offs that engineers use to build r

Cache in Software System Design — A Practical Guide

Caching is the process of temporarily storing frequently accessed data in a faster storage layer to reduce latency, save computation, and improve system scalability. Instead of recomputing or refetching data from a slower source like a database or API, a cache serves it quickly from memory or nearby
Nov 08, 2025 2 0 cache
Cache in Software System Design — A Practical Guide

Scalability in Software System Design — A Practical Guide

Scalability is the ability of a system to handle increased load — such as more users, data, or requests — without unacceptable performance degradation. It can be achieved in two main ways: It also includes operational, cost, and development scalability — how the system, budget, and team scale with g
Nov 08, 2025 3 0 scalability
Scalability in Software System Design — A Practical Guide

Understanding Caching in Scalable Systems

Caches can exist on the client (OS or browser), on the server, or in a dedicated cache layer. Content delivery networks (CDNs) act as distributed caches to improve performance and availability. Reverse proxies and caching servers like Varnish can serve static and dynamic content directly. Web server
Understanding Caching in Scalable Systems

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