Gemini CLI and Gemini Code Assist are AI tools that can support work across the SDLC. Used thoughtfully, they help with requirements capture, code and test generation, refactoring, CI/CD hooks, and operational workflows. This guide outlines where they fit, how to integrate them with existing processes, and what to validate during pilots before wider rollout. Before the use-cases deep-dive, let’s have a glance at both of these. Continue reading “Gemini CLI and Gemini Code Assist: Comprehensive SDLC Use Cases and Implementation Guide”
Building a Scalable And Cost-Efficient BigQuery Platform: Architecture, Practices & Lessons
As data platforms evolve from proof-of-concept pipelines to business-critical systems, scaling BigQuery requires more than writing efficient SQL. Without the right architectural choices, governance, and monitoring, organizations often face unpredictable costs, query slowdowns, and operational instability.
This blog outlines a set of platform-level engineering decisions and best practices adopted to run BigQuery at scale—focused on performance, cost optimization, security and observability. Each practice is backed by real-world implementation examples. Continue reading “Building a Scalable And Cost-Efficient BigQuery Platform: Architecture, Practices & Lessons”
Logs to Unclog: The Complete Guide to Logging
Introduction to Logging
What Are Logs?
Logs are chronological records of events that occur within software applications, operating systems, and network devices. They serve as the digital equivalent of a ship’s logbook, documenting what happened, when it happened, and often providing context about why it happened.
Why Logging Matters
In today’s distributed systems and microservices architectures, logging is not just helpful — it’s essential. Here’s why:
- Debugging: Logs provide crucial information for identifying and fixing bugs
- Monitoring: They enable real-time monitoring of system health and performance
- Security: Logs help detect security incidents and unauthorized access
- Compliance: Many regulations require comprehensive logging for audit trails
- Performance Analysis: They help identify bottlenecks and optimization opportunities
- Business Intelligence: Application logs can provide insights into user behavior and business metrics
Continue reading “Logs to Unclog: The Complete Guide to Logging”
MCP: The Model Context Protocol Powering the Next Wave of AI Workflows
As enterprises and developers adopt LLMs (Large Language Models) at scale, the challenge is no longer just about “which model to use” — but how to use the right model with the right data context, securely and efficiently.
This is where Model Context Protocol (MCP) comes in. Continue reading “MCP: The Model Context Protocol Powering the Next Wave of AI Workflows”
LLM-Powered ETL: How GenAI is Automating Data Transformations
We’ve made huge strides in collecting data. Businesses today generate terabytes from apps, sensors, transactions, and user behavior. But the moment you want to do something with that data (feed it into dashboards, power models, trigger business logic), you run straight into the mess of transformation.
You’ve probably seen this first-hand. Engineers spend weeks writing brittle transformation code. Every schema update breaks pipelines. Documentation is missing. Business logic is locked away in obscure ETL scripts no one wants to touch. This is the silent tax on your data operations: not gathering data, but shaping it. Continue reading “LLM-Powered ETL: How GenAI is Automating Data Transformations”