Backend Systems
Architecture trade-offs, reliability, scale, and incident response for production services.
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Deep-dive articles on System Design, Java, Kafka, Redis, AI/ML, and AWS — from an Engineering Manager with 10+ years building distributed systems at scale.
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Follow a practical track and build momentum from fundamentals to production trade-offs.
Java Production
Spring Boot readiness, JVM behavior, connection pools, and performance tuning.
Data & Caching
Database performance, cache invalidation, indexing, and production data access patterns.
Kafka & Events
Consumer lag, reliable publishing, exactly-once trade-offs, and event-driven systems.
AI Engineering
RAG, embeddings, feature stores, agents, and production AI infrastructure.
Latest Articles
Fresh practical guides and deep dives worth your time
Kubernetes for AI Inference: GPUs, Autoscaling, Queues, and Cost Control
Kubernetes can run AI inference workloads well, but only if you treat GPU capacity as a scarce production resource instead of "just another Deployment." GPU nodes are expensive, images are large, cold starts are painful,…
Apr 8, 202612 min read
#kubernetes#gpu#ai infrastructure
LLM Evaluation at Scale: LLM-as-Judge, RAGAS, and Building Automated Eval Pipelines
Evaluating LLMs is the unsolved problem at the center of every production AI system. You can't ship a prompt change, a retrieval improvement, or a model upgrade without knowing whether it actually got better — or just be…
Apr 8, 202611 min read
#llm evaluation#ragas#llm-as-judge
LLM Inference Optimization: Quantization, KV Cache, and High-Throughput Serving
The Real Cost of Running LLMs A 70B-parameter model in fp16 requires roughly 140 GB of GPU VRAM just for weights. That means two 80 GB accelerator cards before you serve a single token. Add KV cache for concurrent users …
Apr 8, 202614 min read
#llm#inference#quantization
LLM Observability in Production: Traces, Evals, Cost, Latency, and Failure Modes
LLM systems fail differently from normal backend systems. A normal service usually fails with a timeout, an exception, or a bad status code. An LLM application can return a fluent answer that is wrong, unsupported by ret…
Apr 8, 202611 min read
#llm#observability#evals
About Me
Who I Am
I'm a Technical Lead / Architect at Redwood Software, with over 10 years of backend engineering across fintech, enterprise SaaS, and early-stage startups.
I've worked at Paytm, ServiceNow, Threado AI, Paysafe, Accion Labs, and TCS — building systems that process payments at scale, integrating enterprise platforms, and leading teams through complex data migrations and architectural transitions.
CodeSprintPro is where I share what I've learned from building production systems — the real patterns, the real trade-offs, and the decisions that only make sense once you've seen a system fail at 2am.
Technical Stack
Languages & Frameworks
JavaSpring BootSpring CloudSpring Security
Data & Messaging
KafkaRedisMySQLPostgreSQLElasticsearchPresto
Infrastructure & Observability
AWSDockerPrometheusGrafanaDatadogNew Relic
Architecture
MicroservicesSystem DesignDistributed SystemsREST APIs
10+
Years of experience
7
Companies across fintech, SaaS & startups
94
Technical articles published
Work Highlights
Selected projects from 10 years of building backend systems across payments, enterprise SaaS, and startups.
Paytm2023 – 2025
Staff Software Engineer / Senior Technical Lead
PSP Device Binding Migration & Merchant Invoicing
- →Led migration of 20 GB+ of user PSP binding data with zero downtime — served millions of active Paytm users
- →Built and shipped new device binding APIs for the mobile platform, improving security and reducing unauthorized access
- →Replaced heavy code-based merchant file processing with Presto-powered SQL pipelines, cutting invoicing turnaround and eliminating per-config code changes
- →Led deployment team through critical production rollouts; used shell scripting to resolve live device binding incidents
JavaSpring BootKafkaRedisMySQLPrestoPrometheusGrafana
ServiceNow2019 – 2022
Independent Contributor II & III
Azure, Jira & DevOps Integrations — Marketplace Apps
- →Architected and shipped Azure and Jira integration apps now available in the ServiceNow Store
- →Contributed to the ServiceNow Agile Development 2.0 family plugin, used by enterprise customers globally
- →Led security remediation across the product using Fortify static analysis — identified and resolved critical vulnerabilities
JavaServiceNowAzureJiraREST APIsFortifyJenkinsDocker
Paysafe Group2018 – 2019
Platform Engineer
Real-Time Transaction Analytics Platform
- →Built a merchant analytics platform that processed payment transactions in parallel using MapR Stream
- →Enriched raw transaction data and surfaced insights into merchant dashboards via Elasticsearch and Druid
- →Designed Spring Boot / Spring Cloud REST APIs powering the analytics front-end
Spring BootSpring CloudMapR StreamElasticsearchDruid
Writing & Community
CodeSprintPro
94 in-depth articles on Kafka, Redis, System Design, Java 21, AWS, and distributed systems — the site you're reading right now.
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Medium
Earlier writing on Java, Spring Boot, and system architecture. 100K+ views across published articles.
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Stack Overflow
Active contributor with answers focused on Java, Spring Boot, and database optimization.
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Get In Touch
Feel free to reach out for collaborations, opportunities, or just a friendly chat about technology and software development.