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AKArvan Kumaraiwitharvan.hashnode.dev23h ago · 8 min read

80% Right Is the Dangerous Number

I Asked an LLM to Port My AWS Terraform to Google Cloud. Here's What It Got Confidently Wrong. Migrating a real-time analytics stack from EC2 to Compute Engine — and a working test for when to trust g

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JOJoseph Oluwadarajosephdara.hashnode.dev1d ago · 20 min read

From Cloud Run Experiment to Terraform-Managed Platform: Productionizing My Blockchain Indexer on Google Cloud

How I rebuilt the Stablecoin Whale Monitor around a continuous Cloud Run Worker Pool, Terraform, least-privilege CI/CD, and observability that reflects what users can actually experience. The first ve

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SRSailesh Ravichandrandata-engineering-sailesh.hashnode.dev1d ago · 10 min read

Fixing the Past Without Breaking the Present: How Enterprises Backfill Historical Data

A plain English look at a real problem every large company eventually hits and how to solve it safely. Table of Contents The Problem in One Sentence Why You Can't Just "Start Over" Five Situations

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MBMadhav Bhasinblog.madhav.dev3d ago · 5 min read

FastAPI Background Tasks vs Pub/Sub vs Cloud Tasks: When to Use What

The queue had been growing for six days before anyone noticed. A Cloud Tasks queue processing cart abandonment reminders had started backing up after a handler deployment introduced a subtle bug — an

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SRSailesh Ravichandrandata-engineering-sailesh.hashnode.dev3d ago · 11 min read

Deduplication and Late-Arriving Data Handling

How we stopped rewriting the entire lake every night and started scoping dedup work to exactly the partitions that changed Domain: Data Engineering Stack: Azure Databricks, Delta Lake (MERGE + Z-Orde

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SRSailesh Ravichandrandata-engineering-sailesh.hashnode.dev4d ago · 13 min read

Centralized Enterprise Data Quality Framework

Difficulty: Expert Category: Data Engineering Architecture Pattern: Metadata Driven Data Quality Platform Target Audience: Principal Data Engineers, Data Engineers, Enterprise Architects Executive S

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SRSailesh Ravichandrandata-engineering-sailesh.hashnode.dev4d ago · 10 min read

Agentic Root Cause Analysis for Lakehouse Pipeline Failures

Category: Data Engineering · Platform Engineering · AIOps Pattern: AI-Augmented Operations (AIOps), Risk-Gated Automation Cloud: Azure + Databricks Scale: Enterprise (thousands of pipelines/day) 1.

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KSKamran Shaghaghicloudironguard.hashnode.dev4d ago · 8 min read

Cloud Iron Guard: Building Production-Grade Defense-in-Depth on GKE with Terraform, gVisor, and OPA Gatekeeper

When designing production infrastructure on Google Kubernetes Engine (GKE), relying on a single security control—like basic IAM or default network policies—is a recipe for disaster. True cloud resilie

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MMikeymikey-og.hashnode.devJul 31 · 10 min read

How I Designed and Built a Secure Two-Tier Architecture on Google Cloud Platform

A hands-on cloud engineering project demonstrating secure networking, high availability, load balancing, object storage, and infrastructure design using Google Cloud Platform. Introduction Imagine

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MBMadhav Bhasinblog.madhav.devJul 29 · 5 min read

I Migrated a Product from AWS to GCP — Here's What I'd Do Differently

Last year we moved a production platform off AWS and onto GCP. Full migration — compute, database, storage, CDN, CI/CD, the works. The product was live, clients were active, and we had no meaningful d

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#gcp

Explore Hashnode

Trending tags this week

80% Right Is the Dangerous Number

From Cloud Run Experiment to Terraform-Managed Platform: Productionizing My Blockchain Indexer on Google Cloud

Fixing the Past Without Breaking the Present: How Enterprises Backfill Historical Data

FastAPI Background Tasks vs Pub/Sub vs Cloud Tasks: When to Use What

Deduplication and Late-Arriving Data Handling

Centralized Enterprise Data Quality Framework

Agentic Root Cause Analysis for Lakehouse Pipeline Failures

Cloud Iron Guard: Building Production-Grade Defense-in-Depth on GKE with Terraform, gVisor, and OPA Gatekeeper

How I Designed and Built a Secure Two-Tier Architecture on Google Cloud Platform

I Migrated a Product from AWS to GCP — Here's What I'd Do Differently