Microsoft AZ-700: Engineering Reliable Hybrid Connectivity
A logistics company keeps its warehouse systems on-premises while moving customer analytics and internal applications to Azure. Its initial site-to-site VPN carries…
Read articleCLOUD & ARTIFICIAL INTELLIGENCE
Cloud & AI
Understand cloud architecture, Amazon AWS, Microsoft Azure, Google Cloud and emerging AI applications.
Cloud computing is a set of engineering decisions, not just a list of products to memorize. Choosing an architecture means understanding resilience, identity, networks, costs and the operational trade-offs behind managed services. Artificial intelligence makes those decisions more consequential: evaluation, context, reliability and security matter at least as much as model choice.
For candidates, Amazon AWS provides a broad set of certification tracks, including AWS Solutions Architect – Associate (SAA-C03). Microsoft Azure Administrator (AZ-104) emphasizes operational responsibilities, while Azure AI Fundamentals (AI-901) focuses on implementing AI solutions with Microsoft Foundry. Explore the concepts first, then examine the qualification that actually matches the work you intend to do.
CURATED FROM THE EDITORIAL LIBRARY
Explore the articles
Carefully selected articles on the technologies, roles and concepts that shape this subject.
Microsoft AZ-700: Building a Hub-and-Spoke Network That Scales
An enterprise migrates three business applications into Azure and gives each one a virtual network. The applications work individually, but the company…
Read articleGenerative AI Cost Controls on AWS: Budget for Useful Answers
A legal research assistant becomes popular internally. Usage doubles, but the monthly bill grows fourfold. The engineering team blames the foundation model’s…
Read articleAWS Direct Connect Resilience: When Two Links Are Still One Failure
A bank buys two private connections to AWS and considers its hybrid network resilient. Both circuits, however, enter the same building, traverse…
Read articleAWS Control Tower Landing Zones: Design Before Account Sprawl
A growing software company begins with one AWS account and a handful of engineers. Two years later, it has dozens of accounts,…
Read articleAmazon Bedrock Model Evaluation: Test the Task, Not the Demo
A model can excel at writing a polished product description and perform poorly at extracting safety conditions from a maintenance manual. It…
Read articleBedrock Knowledge Bases: Building RAG That Can Be Trusted
Retrieval-augmented generation can make an assistant more useful by supplying relevant organization-specific information to a model at question time. It can also…
Read articleAmazon Bedrock Guardrails in Production: Where Protection Begins and Ends
A team builds a retrieval assistant for a healthcare benefits organization. Its demonstration answers policy questions fluently, and stakeholders assume adding a…
Read articleMicrosoft AB-731: Responsible AI Governance in Practice
A business may approve an AI writing assistant for routine work and discover months later that teams are submitting confidential contracts, patient…
Read articleMicrosoft AI-200: Integrating AI APIs Reliably
Calling an API is easy to demonstrate and surprisingly easy to misuse in a real application. A backend might invoke a hosted…
Read articleMicrosoft AI-200: Event-Driven AI That Can Recover
A document classifier usually works during a demonstration. A user uploads a file, a function runs, and the result appears. In production,…
Read articleMicrosoft AI-200: Identities, Secrets and Trust Boundaries
A production AI service often touches more data than the person asking a question realizes. It may fetch internal documents, query a…
Read articleFURTHER EXPLORATION
Other perspectives
Explore related disciplines across the editorial library.
Understand the subject. Connect it with a meaningful next step.
All Insights