Automation & Agents
Generative AI for Incident Workflows: Evidence Before Action
How generative AI can assist log review, incident drafting and alert triage without replacing monitoring rules or incident ownership.
Read article
INSIGHTS
Technical insights for
modern engineering teams.
Architecture patterns, technical deep-dives and practical lessons across AI, data, cloud and platform engineering.
Platform Engineering
Security Testing in DevOps: Controls Across the Delivery Pipeline
Security testing and release controls that help DevOps teams identify vulnerabilities, protect secrets and track remediation.
Read article
Enterprise Architecture
DevOps, MLOps and LLMOps: Shared Foundations, Different Risks
How DevOps, MLOps and LLMOps overlap, and where data, evaluation, release management and security requirements differ.
Read article
Data Architecture
Jenkins for DataOps: Pipeline Controls and Operating Trade-offs
Using Jenkins to coordinate DataOps checks and jobs, while accounting for credentials, maintenance, failure handling and operating cost.
Read article
Technology Strategy
Quantum Readiness: Workload Evaluation and Cryptographic Inventory
Separate quantum workload experiments from cryptographic inventory and supported migration planning.
Read article
Technology Strategy
LinkedIn Content: Six Practical Considerations
Six practical content considerations for LinkedIn, without unsupported claims about algorithm changes or guaranteed reach.
Read article
AI & GenAI
AI, Machine Learning and Deep Learning: Architectural Distinctions
The relationship between artificial intelligence, machine learning and deep learning, with clear definitions and practical distinctions.
Read article
MLOps & LLMOps
Monitoring and Feedback in MLOps: Signals, Labels and Release Decisions
Monitoring service health, data drift and prediction quality, then using reviewed feedback to guide controlled model updates.
Read article
Data Architecture
DataOps: Contracts, Tests and Recoverable Pipelines
DataOps practices for repeatable data delivery, quality checks and operational ownership, and how they differ from MLOps.
Read article