This article explores the diverse infrastructure options and tools that are available for deploying and optimizing AI agents and large language models (LLMs).
September 22, 2025
by Vidyasagar (Sarath Chandra) Machupalli FBCS
CORE
Client-server synchronous communication via REST, focusing on the client while presenting two distinct implementations with RestTemplate and RestClient.
The difference between reactive and proactive monitoring comes down to tracking the right network metrics and catching issues before they impact users.
Learning and choosing the correct cloud-to-device communication method to send a message to the device using the Azure IoT Hub to build an effective IoT system.
A detailed performance analysis between Amazon OpenSearch's specialized OM2 and general-purpose M7g instances to help you optimize performance and cost.
AI coding is quietly building a “shadow SDLC” inside your organization, spinning up code, dependencies, configs, but requires solid best practices to prevent disaster.
Delta blobs that are 5–10x smaller let serving layers patch serialized data without schemas, enabling substantial network savings while trading most CPU overhead.
The new agent mode in VS Code appears to be a disruption at first glance. Let's dive a bit deeper from an architect's perspective — from architecture to build.
Build an application for natural-language questions that an LLM converts to a Cypher query, runs against the database, and returns the query and the results.