1 min read
Monitoring AI Applications with Azure Monitor and Application Insights
Configure alerts for latency spikes, error rate increases, and token usage anomalies to catch issues before they impact users.
Blog
Thoughts on data engineering, cloud architecture, and technology. 2205 articles and counting.
Showing 24 of 2205 posts — page 11 of 92
1 min read
Building AI Agents with AutoGen and Azure OpenAI
AutoGen enables building sophisticated AI systems that can decompose complex tasks and collaborate to find solutions.
1 min read
Azure Functions with AI: Building Serverless AI Applications
Configure appropriate timeout settings for AI operations and implement retry logic for transient failures. Consider using premium plans for…
1 min read
Responsible AI: Implementing Fairness and Transparency in ML Models
Create comprehensive model documentation including intended use cases, limitations, fairness assessments, and performance across demographic groups to…
1 min read
Azure Machine Learning Pipelines: Orchestrating ML Workflows
Configure pipelines to run on schedules or in response to data changes, enabling fully automated ML operations with minimal manual intervention.
1 min read
Implementing RAG with LangChain and Azure OpenAI
Experiment with chunk sizes, overlap, and retrieval strategies. Hybrid search combining semantic and keyword matching often provides the best results for…
1 min read
Azure AI Document Intelligence: Automated Document Processing at Scale
For high-volume scenarios, implement batch processing with proper error handling and retry logic to ensure reliable document processing at scale.
1 min read
Semantic Kernel: Building AI Orchestration with .NET
Semantic Kernel provides a clean abstraction for building AI-powered features while maintaining flexibility to switch between different LLM providers.
1 min read
Fine-Tuning Azure OpenAI Models: When and How to Customize
Fine-tuning is appropriate when you need consistent formatting, domain-specific language understanding, or reduced prompt lengths. However, it requires…
1 min read
Azure Cosmos DB for AI Applications: Vector Search and Change Feed Patterns
Use Change Feed to trigger embedding generation and synchronization with other AI services automatically when documents are created or updated.
1 min read
Prompt Engineering Patterns for Enterprise Applications
Include examples in prompts to guide model behavior for domain-specific tasks. This is especially effective for classification and formatting tasks where…
1 min read
Azure AI Search: Implementing Hybrid Search with Vectors and Keywords
Hybrid search significantly improves retrieval quality for RAG applications by leveraging both semantic understanding and exact keyword matching.
1 min read
Edge AI Deployment: Running ML Models on Azure IoT Edge
Configure the edge deployment with appropriate resource limits and restart policies for reliable operation in edge environments with limited connectivity.
1 min read
Model Evaluation Techniques: Beyond Accuracy Metrics
Always connect model metrics to business outcomes. A model with lower accuracy but better performance on high-value segments may deliver more business value…
1 min read
Real-Time Streaming Analytics with Azure Stream Analytics and Event Hubs
Enrich streaming data with reference data lookups for context-aware processing and alerting in real-time scenarios.
1 min read
Data Governance with Microsoft Purview: Implementing Data Lineage Tracking
Purview captures lineage automatically from supported sources and allows custom lineage submission via APIs. The lineage graph shows how data flows from…
1 min read
Building Multi-Modal AI Applications with GPT-4 Vision and Audio
Multi-modal requests consume more tokens and have higher latency. Use the detail parameter wisely: "low" for quick analysis, "high" for detailed extraction…
1 min read
AI Safety Guardrails: Implementing Content Filtering in Azure OpenAI
Maintain comprehensive logs of all content filtering decisions for compliance and incident investigation. Every blocked request should be logged with…
1 min read
Microsoft Fabric Capacity Planning: Right-Sizing Your Data Platform
For development and test environments, implement auto-pause policies to reduce costs during inactive periods. Monitor utilization patterns and adjust…
1 min read
Azure Machine Learning Managed Endpoints: Advanced Deployment Patterns
Configure autoscaling rules that balance responsiveness with cost for production deployments while maintaining service level objectives.
1 min read
Preparing for Microsoft Ignite 2025: Key Azure AI Announcements to Watch
The Azure AI platform has been evolving rapidly, and Ignite typically showcases significant platform updates. This year, expect announcements around…
1 min read
September 2025 Recap: Key Takeaways for Enterprise AI
The most successful AI implementations share common architectural patterns. Hybrid search combining vector and keyword retrieval consistently outperforms…
1 min read
Retrieval-Augmented Generation: Chunking Strategies for Better Results
The best chunking strategy depends on your document types. Technical documentation benefits from header-aware chunking. Conversational content works well…
1 min read
Prompt Injection Defense: Securing LLM Applications
Prompt injection occurs when user input is interpreted as instructions rather than data. Attackers can attempt to override system prompts, extract…