Introduction: LLM applications are notoriously difficult to debug. Unlike traditional software where errors are obvious, LLM issues manifest as subtle quality degradation, unexpected costs, or slow responses. Proper observability is essential for production LLM systems. This guide covers monitoring strategies: tracking latency, tokens, and costs; implementing distributed tracing for complex chains; structured logging for debugging; […]
Read more →DevSecOps: Integrating Security into DevOps – Part 7
Continuing from my previous blog, let’s explore some more advanced topics related to DevSecOps implementation. Automated Vulnerability Management Automated vulnerability management is a key practice in DevSecOps. It involves using automated tools to identify, prioritize, and remediate vulnerabilities in an organization’s systems and applications. Automated vulnerability management includes the following activities: Shift-Left Testing Shift-left testing […]
Read more →LLM Security Best Practices: Protecting AI Applications from Attacks
Introduction: LLM applications face unique security challenges. Prompt injection attacks can hijack model behavior, sensitive data can leak through responses, and malicious outputs can harm users. Traditional security measures don’t fully address these risks—you need LLM-specific defenses. This guide covers practical security strategies: validating and sanitizing inputs, detecting prompt injection attempts, filtering sensitive information from […]
Read more →Building the Modern Data Stack: How Spark, Kafka, and dbt Transformed Data Engineering
The data engineering landscape has undergone a fundamental transformation over the past decade. What once required massive Hadoop clusters has evolved into a sophisticated ecosystem of specialized tools: Kafka for ingestion, Spark for processing, and dbt for transformation. Modern Data Stack Architecture The Paradigm Shift: Monolithic → Modular The old approach centered around monolithic platforms […]
Read more →Vertex AI Masterclass: Building Production ML Pipelines on Google Cloud
Vertex AI represents Google Cloud’s unified machine learning platform, bringing together AutoML, custom training, model deployment, and MLOps capabilities under a single, cohesive experience. This comprehensive guide explores Vertex AI’s enterprise capabilities, from managed training pipelines and feature stores to model monitoring and A/B testing. After building production ML systems across multiple cloud platforms, I’ve […]
Read more →DevSecOps: Integrating Security into DevOps – Part 8
Continuing from our previous blog, let’s explore some more advanced topics related to DevSecOps implementation. Continuous Compliance Continuous compliance is a practice that involves integrating compliance requirements into the software development lifecycle. By doing so, organizations can ensure that their software complies with regulatory requirements and internal security policies. Continuous compliance includes the following activities: […]
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