Visualizing Rate Limiting Algorithms
An interactive exploration of fixed windows, sliding windows, and token buckets with animated visualizations.
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Software Engineer • Backend & Distributed Systems
Building scalable microservices and event-driven architectures for banking & supply chain finance. Passionate about LLMs, systems thinking, and engineering excellence.
data class Engineer(
val name: String,
val role: String,
val experience: Int,
val skills: List<String>
)
fun main() {
val rakshak = Engineer(
name = "Rakshak D S",
role = "SWE",
experience = 5,
skills = listOf(
"Kotlin", "Go",
"Microservices",
"Event-Driven"
)
)
}I'm a backend engineer with 5+ years of experience building production systems for banking and supply-chain financing. I work on microservices, event-driven architectures, and financial integrations that power real-world transactions.
Currently at Vayana Network, I'm involved in technical leadership—contributing to architecture decisions, implementation, and coordination across engineering, product, and operations teams.
Beyond work, I'm deeply curious about Large Language Models, systems thinking, and prompt engineering. I love understanding how complex systems behave at scale.
Thoughts on distributed systems, backend engineering, and software craft.
An interactive exploration of fixed windows, sliding windows, and token buckets with animated visualizations.
Real-world patterns and pitfalls from building event-driven systems at scale in fintech.
From skeptic to enthusiast—exploring practical applications of large language models.
Exploring the capabilities and limitations of LLMs, from GPT to open-source alternatives. Fascinated by emergent behaviors and reasoning capabilities.
Understanding complex adaptive systems, feedback loops, and how individual components create emergent system-level behaviors.
Crafting effective prompts to unlock AI capabilities. Interested in chain-of-thought reasoning, few-shot learning, and instruction tuning.
Building intuition for ML systems—from classical algorithms to deep learning. Focus on practical applications in production systems.
Designing systems that handle growth gracefully. From horizontal scaling to distributed consensus and eventual consistency.
Finding bottlenecks and making systems faster. Profiling, caching strategies, and efficient algorithms.
When I'm not coding, you'll find me exploring virtual worlds.
I'm always interested in hearing about new opportunities, interesting projects, or just having a conversation about distributed systems and AI.
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