Here is short info about post: Modern Containerized Microservice Control Protocol (MCP) servers empower organizations to build robust, portable, and scalable microservice ecosystems. Pairing MCP servers with Docker amplifies their effectiveness—ensuring consistent environments, reproducible builds, and scalable deployments. As teams increasingly rely on containerization, understanding best practices for creating Dockerized MCP servers becomes essential for reliability, maintainability, and long-term success. This article explores best practices for building Dockerized MCP servers—from structuring images and managing dependencies to optimizing performance and improving operational workflows. It includes coding examples, ... The Best Practices for Building Dockerized MCP Servers

Here is short info about post: Modern identity and access governance (IAG) programs often struggle with application onboarding. Many enterprise applications lack native APIs, SCIM endpoints, or modern provisioning connectors. Some are legacy systems, some are proprietary, and some simply do not justify the cost or effort of building direct integrations. Yet, organizations still need governance controls—certifications, birthright provisioning, least-privilege access modeling, and access request workflows. A powerful and widely applicable strategy is to achieve access governance without building direct application connectors, by instead using: Existing ... How To Achieve Access Governance Without Direct Application Connectors By Leveraging Existing LDAP Integration and Groups as Entitlements

Here is short info about post: Artificial intelligence agents have rapidly evolved from experimental prototypes to production-ready components that drive automation, decision-making, and high-value enterprise workloads. Whether it’s orchestrating tasks, integrating with APIs, or reasoning over business logic, modern AI agents deliver predictable, repeatable outcomes that scale. Microsoft’s Semantic Kernel (SK) is one of the most powerful frameworks for building AI agents in .NET, Python, or Java. It provides a robust orchestration layer for Large Language Models (LLMs), enabling developers to unify memory, planning, connectors, functions, ... How To Build a Simple, Production-Ready AI Agent Using Semantic Kernel

Here is short info about post: Testing POST requests is one of the most essential capabilities when working with backend services and APIs. In most modern applications, POST endpoints enable creating new resources, submitting forms, authenticating users, uploading data, or triggering workflows. For QA engineers, developers, and automation testers, validating the integrity and reliability of these POST operations is crucial for ensuring software quality. One of the most popular open-source libraries for API automation in Java is REST Assured. It offers a fluent, readable syntax that ... How To Test POST Requests With REST Assured Java For API Testing

Here is short info about post: Delivering responsive digital experiences is no longer merely a matter of technical polish—it is a competitive advantage. Users have become increasingly intolerant of waiting for screens to load, content to generate, or computations to complete. They expect immediate feedback, even when the system is performing expensive tasks in the background. One effective strategy for meeting these expectations is to first return a fast and lightweight response, and then silently upgrade that response with a richer, more complete version once heavier ... How To First Deliver A Fast And Lightweight Response, And Later Upgrade It To A Slower And Richer One To Create The Illusion Of Zero Latency

Here is short info about post: Building multimodal AI agents is becoming one of the most important skills for modern developers. As applications shift from text-only interactions to real-world, perception-capable systems, frameworks like Google’s AI Device Kit (ADK) provide a powerful foundation. With ADK, you can build agents that communicate using text, speech, images, audio, gesture inputs, and custom sensors—effectively bridging the gap between machine reasoning and physical-world interaction. This article walks through what Google ADK is, how it works, how to build multimodal agents with ... How To Build Multimodal Agents Using Google ADK

Here is short info about post: Retrieval-Augmented Generation (RAG) has emerged as one of the most practical and powerful architectures for enabling large language models (LLMs) to use custom domain knowledge. Traditional LLMs are trained on general-purpose corpora and cannot access your private data unless you provide it at inference time. RAG solves this problem by allowing the model to “look up” relevant documents from an external knowledge base and use them as context for generating accurate responses. But while many cloud-based tools support RAG, there ... How To Build a Private and Offline RAG System With Ollama and FAISS

Here is short info about post: Amazon DocumentDB has long been a powerful, scalable, and fully managed document database service for teams building applications compatible with MongoDB workloads. But as more organizations adopt Kubernetes as their core platform, the need to deploy, manage, and scale DocumentDB-like environments directly inside Kubernetes has grown. The new open-source DocumentDB Operator now makes this possible. It introduces a Kubernetes-native way to run DocumentDB-compatible workloads by leveraging Custom Resource Definitions (CRDs), declarative configuration, and the reconciliation patterns common in modern Operators. ... How To Deploy, Manage, And Scale DocumentDB On Kubernetes With The New Open-Source DocumentDB Operator

Here is short info about post: Working with PostgreSQL’s advanced JSON and JSONB column types has become increasingly common in modern software development. These flexible data structures enable applications to implement semi-structured or schema-light storage patterns without fully committing to a NoSQL database. Meanwhile, Java applications often need a clean, type-safe, and low-boilerplate way to map these JSON fields to domain objects. This is where asentinel-orm comes in. asentinel-orm is a lightweight Object-Relational Mapping (ORM) tool designed to simplify the interaction between Java objects and relational ... How to Map PostgreSQL JSON Data Types in Java

Here is short info about post: The Java Stream API, introduced in Java 8, revolutionized how developers manipulate collections and sequences of data. By providing a fluent and declarative style, Streams make it easier to process data in a functional style — filtering, mapping, reducing, and transforming data into desired outputs. However, while Streams come with a rich set of built-in intermediate operations (like map(), filter(), and flatMap()), they also allow for deeper customization through Collectors. Although Collectors are primarily associated with terminal operations — such ... How Java Stream Collectors Allow Developers to Define Custom Intermediate Operations

Here is short info about post: In today’s fast-moving software industry, measuring developer productivity has become a key challenge for engineering managers, CTOs, and team leads. With complex codebases, distributed teams, and constantly evolving technologies, the traditional metrics that once worked for evaluating developer performance often fail to capture the full picture today. This article explores the old and new practices for measuring developer productivity — what they get right, what they miss, and how modern teams can achieve a better balance between quantitative and qualitative ... How To Measure Developer Productivity: Old And New Practices

Here is short info about post: Kubernetes has become the backbone of cloud-native infrastructure. It orchestrates containers at scale, automates deployments, and ensures high availability. However, when failures occur—due to misconfigurations, resource exhaustion, or security policy violations—troubleshooting can be complex and time-consuming. To tackle this challenge, AI-driven automation can be introduced into the Kubernetes control loop. This article walks you through how to build an AI-driven Kubernetes Operator that automatically: Detects failures in the cluster Uses a Large Language Model (LLM) to generate remediation steps Validates ... How To Create An AI-Driven Kubernetes Operator That Analyzes Failures, Generates Fixes Using LLMs, Validates Them Using OPA, And Securely Deploys Changes Via GitOps