Embedding Space Analysis: Visualizing and Understanding Vector Representations

Introduction: Understanding embedding spaces is crucial for building effective semantic search, RAG systems, and recommendation engines. Embeddings map text, images, or other data into high-dimensional vector spaces where similar items cluster together. But how do you know if your embeddings are working well? How do you debug retrieval failures or understand why certain queries return […]

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Guardrails and Safety Filters: Protecting LLM Applications from Harmful Content

Introduction: LLMs can generate harmful, biased, or inappropriate content. They can be manipulated through prompt injection, jailbreaks, and adversarial inputs. Production applications need guardrails—safety mechanisms that validate inputs, moderate content, and filter outputs before they reach users. This guide covers practical guardrail implementations: input validation to catch malicious prompts, content moderation using classifiers and LLM-based […]

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Testing LLM Applications: Unit Tests, Integration Tests, and Evaluation

Introduction: Testing LLM applications presents unique challenges compared to traditional software. Outputs are non-deterministic, quality is subjective, and the same input can produce different but equally valid responses. This guide covers practical testing strategies: unit testing with mocked LLM responses, integration testing with real API calls, evaluation frameworks for quality assessment, and regression testing to […]

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Securing Cloud Applications with Google Cloud Armor: Enterprise WAF and DDoS Protection

Google Cloud Armor provides enterprise-grade DDoS protection and web application firewall (WAF) capabilities that integrate with Cloud Load Balancing. Cloud Armor Defense Architecture WAF Rule Execution Flow Terraform Configuration resource “google_compute_security_policy” “armor_policy” { name = “cloud-armor-policy” description = “Enterprise Cloud Armor security policy” rule { action = “deny(403)” priority = 100 match { expr { […]

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