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Showing posts from April, 2025

The Journey of a Web Request: Unraveling Multi-Tier Architecture and Cloud Security

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Introduction: Imagine you have a company with a website, say XYZ.com , where you sell grocery items online. When a client (let’s call them Client A) tries to access your website using a web browser, they type the website address (URL). The Domain Name System (DNS) resolves this webpage name (like www.xyz.com ) into an IP address. Once the IP address is obtained, the browser sends an HTTP request to the serve. Now, what exactly is a server? Every webpage you see is essentially a static file provided by a server to your web browser. A server is nothing but a computer that is ready to serve you with the files or anything it is configured to server. For example, even something as simple as searching for www.xyz.com triggers an HTTP request to the server. The server then responds by sending back the requested webpage, typically the homepage, to the browser. While this process may seem straightforward, a lot of complex operations happen behind the scen es every time you see such simpl...

Unlocking Change Data Capture in ADF: New Feature Explained

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 Change Data Capture(CDC) In Azure Data Factory Introduction This blog post introduces an exciting new feature in Azure Data Factory (ADF) — Change Data Capture (CDC) — a long-awaited capability that significantly enhances real-time data integration scenarios. While ADF has previously supported CDC through Data Flows , this newly introduced UI-based CDC feature brings a more streamlined and user-friendly experience. However, it's important to note that there are key differences between the two implementations: CDC in Data Flows follows a pattern of performing a full initial load , followed by incremental updates , allowing users to establish a historical baseline before applying changes. In contrast, the CDC feature in the ADF UI is designed specifically for incremental loads only , and it offers near real-time synchronization by pushing changes directly to the sink as they occur. Additionally, with Data Flows, changes are applied based on checkpoint-based pipeline ...