News Aggregator

From Fragmentation to Focus: A Data-First, Team-First Framework for Platform-Driven Organizations

Aggregated on: 2025-05-02 22:43:34

Success in today's complex, engineering-led enterprise organizations, where autonomy and scalability are paramount, hinges on more than adopting the latest tools or methodologies. The real challenge lies in aligning decentralized teams with shared goals while embedding governance without stifling innovation, creating a framework where teams can innovate freely, stay aligned, and ensure data is no longer treated as a second-class citizen. While CI/CD revolutionized software development, it overlooked the unique challenges of managing and governing data at scale. Data pipelines, quality, and compliance often remain fragmented, manual, or inconsistent, creating bottlenecks and risks. Enter Continuous Governance (CG): the evolution that puts data on equal footing with software, embedding compliance, quality, and automation directly into workflows without stifling creativity.

How Large Tech Companies Architect Resilient Systems for Millions of Users

Aggregated on: 2025-05-02 21:28:34

When you are serving millions of users, resilience cannot be something you add later. It has to be part of the design from the very beginning. Otherwise, with the way user expectations keep climbing and how global traffic patterns shift, your system simply won’t keep up. What I want to walk you through today is how top companies think about resilience at scale. We will go through the strategies that work in the real world — not just theory — and look at how availability, cost, observability, scaling, and system design all come together.

Microsoft Azure Synapse Analytics: Scaling Hurdles and Limitations

Aggregated on: 2025-05-02 20:28:34

Azure Synapse Analytics is a strong tool for processing large amounts of data. It does have some scaling challenges that can slow things down as your data grows. There are also a few built-in restrictions that could limit what you’re able to do and affect both performance and overall functionality. So, while Synapse is powerful, it’s important to be aware of these potential roadblocks as you plan your projects. Data Distribution and Skew Data skew remains a significant performance bottleneck in Synapse Analytics. Poor distribution key selection can lead to:

Rethinking Recruitment: A Journey Through Hiring Practices

Aggregated on: 2025-05-02 19:28:34

Introduction It is hard to ignore that hiring processes are becoming increasingly lengthy and intricate. What troubles me is the apparent lack of genuine innovation in this space. While candidates are required to invest more effort and energy into these processes, I find it difficult to see the proportional increase in value or impact for companies. In this article, I aim to share my thoughts, personal experiences, and some strategies that have worked for me. Last year, I participated in several hiring processes that felt remarkably familiar. As I navigated through the steps, it became evident that the approach, structure, and overall experience closely mirrored what I encountered four years ago.

Rust and WebAssembly: Unlocking High-Performance Web Apps

Aggregated on: 2025-05-02 18:13:34

Information technology continues to transform at an accelerated pace because modern businesses seek faster, high-performance applications. JavaScript-based development solutions from the past tend to fall behind when performing complex computations, which produce performance issues along with ineffective execution. Fast, efficient web applications emerge through a synergistic relationship between Rust and Wasm technology. WebAssembly offers developers a novel technology to achieve native-level execution speed in web applications alongside standard web platform benefits.

Breaking Bottlenecks: Applying the Theory of Constraints to Software Development

Aggregated on: 2025-05-02 17:13:34

Introduction The Theory of Constraints (TOC) is a problem-solving and continuous improvement methodology first introduced by Dr. Eliyahu M. Goldratt in his book The Goal. Although TOC originally gained popularity in manufacturing and supply chain management, its application soon became far broader: at its core, TOC asserts that any system has at least one limiting factor—or “bottleneck”—that determines its overall efficiency. By identifying and eliminating this constraint, an organization can significantly boost productivity in virtually any process. In my view, despite TOC’s roots in managing physical goods and delivery chains, its fundamental principles easily carry over into software development. Whether the “bottleneck” lies in code review, testing, or deployment, each stage of the software development lifecycle can become a constraint for the entire process. From my experience, finding and removing these constraints often marks the difference between slow releases and a fast, efficient workflow.

Docker Base Images Demystified: A Practical Guide

Aggregated on: 2025-05-02 16:13:34

What Is a Docker Base Image? A Docker base image is the foundational layer from which containers are built. Think of it as the “starting point” for your application’s environment. It’s a minimal, preconfigured template containing an operating system, runtime tools, libraries, and dependencies. When you write a Dockerfile, the FROM command defines this base image, setting the stage for all subsequent layers. For example, you might start with a lightweight Linux distribution like Alpine, a language-specific image like Python or Node.js, or even an empty "scratch" image for ultimate customization. These base images abstract away the underlying infrastructure, ensuring consistency across development, testing, and production environments. Choosing the right base image is critical, as it directly impacts your container’s security, size, performance, and maintainability. Whether optimizing for speed or ensuring compatibility, your base image shapes everything that follows.

AI-Assisted Coding for iOS Development: How Tools like CursorAI Are Redefining the Developer Workflow

Aggregated on: 2025-05-02 15:28:34

The landscape of iOS engineering has seen a remarkable transformation since its inception, evolving from days of Interface Builder to AI enhanced development workflows. Programmers from all backgrounds are reporting an increase in productivity through AI assistance. We are seeing a fundamental shift in how iOS applications are conceptualized and built. However, this rise in AI assisted development brings both opportunities and challenges that every iOS developer needs to understand. The Evolution of iOS Development iOS engineering has come a long way, just like the arch of software engineering in general. Back in the day, iOS engineers used Interface Builder and XIB files, which were like XML files for creating static views.

Optimize Deployment Pipelines for Speed, Security and Seamless Automation

Aggregated on: 2025-05-02 14:28:34

A developer's work doesn't stop once the code is written. The real action begins when it’s deployment day. The process—managing multiple environments, testing new features, or ensuring seamless uptime during releases—must be fast, secure, and efficient. Can you imagine a world where deployment is smooth, automated, and risk-free—where strategies scale, adapt, and are successful every single time?

Unlocking AI Coding Assistants Part 4: Generate Spring Boot Application

Aggregated on: 2025-05-02 13:28:34

In this final installment of our Unlocking AI Assistants series, we will create a Spring Boot application from scratch using an AI coding assistant. The goal is not to just merely create a working application, but to create production-grade code. Enjoy! Introduction Some tasks are executed with the help of an AI coding assistant. The responses are evaluated and different techniques are applied, which can be used to improve the responses when necessary.

Comparing SaaS vs. PaaS for Kafka and Flink Data Streaming

Aggregated on: 2025-05-02 12:43:34

The cloud revolution has transformed how businesses deploy, scale, and manage data streaming solutions. While Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS) cloud models are often used interchangeably in marketing, their distinctions have significant implications for operational efficiency, cost, and scalability. In the context of data streaming around Apache Kafka and Flink, understanding these differences and recognizing common misconceptions—such as the overuse of the term “serverless”—can help you make an informed decision. Additionally, the emergence of Bring Your Own Cloud (BYOC) offers yet another option, providing organizations with enhanced control and flexibility in their cloud environments. The Data Streaming Landscape: Kafka, Flink, Cloud, and More The Data Streaming Landscape 2025 highlights how data streaming has evolved into a key software category, moving from niche adoption to a fundamental part of modern data architecture.

My LLM Journey as a Software Engineer Exploring a New Domain

Aggregated on: 2025-05-01 22:13:33

Over the holidays when I had some time off, I pondered the thought of how to make some passive income. In this day and age of AI and all the hype, I had been thinking that the world is my oyster. With the threat of AI taking over the world, especially in my day to day as a software engineer, I should start bucking up my ideas and get involved.

Evolution of Cloud Services for MCP/A2A Protocols in AI Agents

Aggregated on: 2025-05-01 21:13:33

The rapid evolution of artificial intelligence (AI) is reshaping cloud service architectures, necessitating new frameworks to support the growing complexity and autonomy of AI agents. The MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols are enhancing how AI agents interact with cloud services. MCP introduces a modular client-server architecture that allows AI models to connect seamlessly to various services without the need for custom integrations. Concurrently, the A2A protocol facilitates direct communication between AI agents, enabling them to collaborate effectively across different platforms and frameworks. As organizations increasingly adopt AI-driven solutions, the integration of MCP and A2A protocols into cloud service architectures is becoming imperative. These protocols not only streamline the development and deployment of AI agents but also pave the way for more dynamic, flexible, and scalable cloud ecosystems.

Internal Developer Portals: Modern DevOps's Missing Piece

Aggregated on: 2025-05-01 20:13:33

You have experienced the following scenario as a developer in 2025: you are prepared to test an API or introduce a new microservice, but you are initially stalled. You require authorization to construct a container, database access, or guidance on which CI/CD pipeline to employ. You go through old documents, ping a few Slack channels, and maybe, just possibly, you'll be unblocked before lunch. It's not a tool problem. This issue stems from the lack of experience among developers. To bridge the gap, internal developer portals (IDPs) are taking over.

Zero Trust for AWS NLBs: Why It Matters and How to Do It

Aggregated on: 2025-05-01 19:28:33

Introduction to AWS Network Load Balancer AWS has several critical services that drive the internet. If you have ever built any application on top of AWS and need a high throughput or volume of traffic, the chances are that you’ve leaned on an AWS Network Load Balancer at some point in the discussion. AWS NLB is nothing but a Layer 4 load balancer, and consistency helps with low-latency forwarding of massive amounts of TCP, UDP, and even TLS traffic. NLBs, being operational at Layer 4 of the OSI model, support a host of features. You get features like static IPs, support for long-lived connections out of the box, and can be configured to our requirements. In my projects, I’ve used NLBs for use cases ranging from being the front end for low-latency database requests to hosting an entire backend of an application. NLB helps in all these use cases by giving us a consistent latency, and it holds up its end every time. There are alternatives for NLBs like the AWS Application Load Balancers, but they operate at a higher level of the OSI model and are not always the choice for developers looking for a high-throughput, no-nonsense load balancer.

How Platform Engineering Is Impacting Infrastructure Automation

Aggregated on: 2025-05-01 18:28:33

Platform engineering is all about building reusable tools, workflows, and infrastructure that empower development teams to move faster without compromising on reliability or security. It’s a shift from ad hoc support to treating internal platforms like products, complete with roadmaps, user feedback, and clear ownership. Paired with infrastructure automation, which handles tasks like provisioning environments, scaling systems, and enforcing configurations, these disciplines help reduce toil and eliminate the bottlenecks that come with manual operations.

Integrating Security as Code: A Necessity for DevSecOps

Aggregated on: 2025-05-01 17:28:33

Security practices in DevOps have evolved from being a minor concern to one of the main focus points, which resulted in the DevSecOps movement. It’s about “shifting security to the left” in the software development lifecycle — so the security measures are a fundamental component. Traditionally, security management was moved to the final stages of developing software, and it has proven its ineffectiveness in dealing with the challenges of modern software projects. This is where Security as Code (SaC) comes in. It is a way to integrate security into every phase of development, from start to deployment, so that security and development teams can work together effectively and successfully.

GDPR Compliance With .NET: Securing Data the Right Way

Aggregated on: 2025-05-01 16:13:33

When developers hear the term GDPR, the initial reaction often involves stress and uncertainty, especially around how it might slow down development or degrade application performance. But here’s the truth: GDPR isn’t just another regulation to check off your list. It's a framework that can help build trust, protect user rights, and improve your application’s overall data hygiene.

Selenium Pagination Tutorial: How to Handle Page Navigation

Aggregated on: 2025-05-01 15:43:33

As websites are becoming an integral part of the business, they must have a good UI that provides the best user experience and loads the content quickly. Websites can be categorized into two types based on the categorisation of their content: paginated and infinite-scrolling websites. The paginated website divides the content of the website into different pages, allowing the user to access all the available content on the different pages of the website one by one seamlessly.

The 4 R’s of Pipeline Reliability: Designing Data Systems That Last

Aggregated on: 2025-05-01 14:28:33

As AI and machine learning applications continue to proliferate, the data pipelines that power them have become more mission-critical than ever. As retrieval-augmented generation (RAG) applications and real-time AI systems are becoming the norm, any glitch in a data pipeline can lead to stale insights, suboptimal model performance, and inflated infrastructure costs. Working in this domain has taught me that even minor lapses in pipeline reliability can escalate into major outages. To combat this, I rely on a framework I call the 4 R’s of pipeline reliability: robust architecture, resumability, recoverability, and redundancy. Here’s how each element contributes to building data systems that truly last.

Subtitles: The Good, the Bad, and the Resource-Heavy

Aggregated on: 2025-05-01 13:28:33

Stack: HTML + CSS + TypeScript + Next.js (React) Goal: Build a universal expandable subtitle with an embedded "Show more" button and gradient background.

Unlocking AI Coding Assistants Part 3: Generating Diagrams, Open API Specs, And Test Data

Aggregated on: 2025-05-01 12:13:33

While large language models (LLMs) offer valuable savings, automation, and time management, knowing and understanding their limitations—especially in defining relationships—and how to guide their output effectively can make a big difference. Let's dive into how you can make the most of LMMs in your every day development tasks. Enjoy! Introduction Part 3 of our Unlocking AI Assistants series explores how LLMs can support developers by generating UML diagrams, OpenAI specs, new features, and test data. You can find the first two articles below:

Create Your Own AI-Powered Virtual Tutor: An Easy Tutorial

Aggregated on: 2025-04-30 21:28:33

It is a very powerful world with AI being a thing. Now, you can have a tutor who never gets tired, who doesn’t roll their eyes at your dumb questions (we all have them, I do, admit it), and who is available 24/7 — no scheduling problems, no coffee breaks, just straight knowledge on demand. That’s the magic of AI-based tutors. But before we start dreaming about how AI could replace your least favorite professors, let’s discuss how to build one in fact. As someone who has tinkered with AI models for countless hours (and broken them here and there), I have been somewhat obsessed with the notion of an AI tutor. In this guide, I’m going to take you through the main components needed to build one for yourself, from Natural Language Processing (NLP) to knowledge graphs and adaptive learning models. No, this is not a plug-and-play recipe, though it will provide you with a strong road map for your path.

Google Cloud Document AI Basics

Aggregated on: 2025-04-30 20:13:33

Google Cloud’s Document AI (Doc AI) helps organizations automate the processing, extraction, and classification of massive amounts of documents. Doc AI has a lot of capabilities and use cases, and here are a few ways it can help organizations. They’re tailored towards the public sector since that’s the customers I help; however, these use cases also apply to private companies.

Docker Model Runner: Streamlining AI Deployment for Developers

Aggregated on: 2025-04-30 19:13:33

Development teams working in the fast-evolving AI development environment must tackle efficient model deployment as their primary operational challenge. Docker Model Runner represents a transformative containerization solution that drives changes in how developers create, deploy, and expand their applications that use AI technology. This article will cover how this technology bridges the gap between data science testing phases and the deployment of ready-to-use AI systems.

A Guide to Container Runtimes

Aggregated on: 2025-04-30 18:13:33

Kubernetes, also known as K8S, is an open-source container orchestration system that is used for automating the deployment, scaling, and management of containerized workloads. Containers are at the heart of the Kubernetes ecosystem and are the building blocks of the services built and managed by K8S. Understanding how containers are run is key to optimizing your Kubernetes environment.

Fixing Common Oracle Database Problems

Aggregated on: 2025-04-30 17:13:33

Lots of businesses use Oracle databases to keep their important stuff. These databases mostly work fine, but yeah, sometimes they run into issues. Anyone who's worked with Oracle knows the feeling when things go wrong. Don't worry, though — these problems happen to everyone. Most fixes are actually pretty easy once you know what you are doing. I'll show you the usual Oracle headaches and how to fix them.

Setting Up Data Pipelines With Snowflake Dynamic Tables

Aggregated on: 2025-04-30 16:13:33

This guide walks through the steps to set up a data pipeline specifically for near-real-time or event-driven data architectures and continuously evolving needs. This guide covers each step, from setup to data ingestion, to the different layers of the data platform, and deployment and monitoring, to help manage large-scale applications effectively. Prerequisites Expertise in basic and complex SQL for scripting Experience with maintaining data pipelines and orchestration Access to a Snowflake for deployment Knowledge of ETL frameworks for efficient design Introduction Data pipeline workloads are an integral part of today’s world, and maintaining these workloads needs massive effort, and it's cumbersome. A solution is provided within Snowflake, which is called dynamic tables.

Develop a Reverse Proxy With Caching in Go

Aggregated on: 2025-04-30 15:13:33

Reverse proxies act as a crucial intermediary layer in modern web infrastructure, sitting between clients and servers and offering additional functionality such as load balancing, SSL termination, and caching. In this article, we are going to construct a reverse proxy with HTTP response caching using Go’s standard library. The Basic Structure As a first step, we will declare our core data structures. We need:

Java’s Next Act: Native Speed for a Cloud-Native World

Aggregated on: 2025-04-30 14:43:33

Once the unshakable king of enterprise development, Java is now facing its most important existential moment since its creation. It’s not that Java has failed; it’s that the world around it has changed. And Java, with its traditional runtime model and heavyweight architecture, hasn’t always kept up. In a cloud-native world where agility, speed, and efficiency matter more than ever, traditional Java stacks often struggle. They’re too slow to start, too heavy on memory, and too rigid for the ephemeral, elastic environments of today’s infrastructure.

Building Scalable and Resilient Data Pipelines With Apache Airflow

Aggregated on: 2025-04-30 13:13:33

I have seen articles discussing Apache Airflow and its many capabilities. It's crucial to understand production-quality data pipelines meant to "handle" terabytes of daily data generated by the enterprise's software-as-a-service (SaaS) applications. The article takes you beyond the basic introductory stuff and on to more advanced techniques and best practices for developing scalable, fault-tolerant, and observable Airflow workflows. Administration for an enterprise in a modern SaaS context is very challenging. It comes with a myriad of challenges in terms of monitoring, administration, and understanding the usage of applications across the organization. It involves the management of increasing amounts of unstructured data with a high tendency for real-time visibility under user activity, resource utilization, and compliance requirements. From this data, organizations need clear insights into usage within their applications to enable them to manage their human resources efficiently and optimally while being effective and compliant. Therefore, they need a powerful Admin Insights pipeline capable of:

Scaling Mobile App Performance: How We Cut Screen Load Time From 8s to 2s

Aggregated on: 2025-04-30 12:13:32

User experience is king in the crowd-sourced world of mobile app development, especially in the case of speed. If your app takes too long to load, those same users will bypass your app in favour of a speedy, seamless offering. When we realized that our app was taking a frustrating 8 seconds to load some screens, this was a hard reality for us to accept. With the competition being fierce and users becoming more and more impatient, we knew something had to change. Read this article as we detail our path from an 8-second screen load time to under 2 seconds, all with a combined multi-sided attack on mobile optimization.

Why We Still Struggle With Manual Test Execution in 2025

Aggregated on: 2025-04-30 11:13:32

Manual Execution Seems To Be 'Forgotten' The SDLC evolves quickly, as does each stage of the cycle. The testing phase is nowadays evolving based on AI-powered test case generation, automation tools, and CI/CD. However, manual test execution is still unavoidable in most QA teams. The role of a manual QA engineer is still relevant. Manual testing is still indispensable. And at the same time, manual testing is one of the most error-prone and cognitively draining activities. So... why is that?

The Modern Data Stack Is Overrated — Here’s What Works

Aggregated on: 2025-04-29 21:28:32

Once upon a time, getting insights from your data meant running a cron job, dumping a CSV, and tossing it into a dashboard. It was rough, but it worked. Then came the wave — the “Modern Data Stack.” Suddenly, you weren’t doing data unless you had:

Scaling InfluxDB for High-Volume Reporting With Continuous Queries (CQs)

Aggregated on: 2025-04-29 20:28:32

The Bottleneck Our systems are constantly generating high-volume transactional events. In our case, these events are funneled through Kafka and ingested into InfluxDB. Each event includes details such as timestamps, categories, and other metadata. Initially, this architecture supported our analytical needs well. We used InfluxDB to store these metrics and performed queries to generate category-wise transaction reports. Our typical reporting queries looked like this:

Understanding Java Signals

Aggregated on: 2025-04-29 19:28:32

To tee off this presentation, consider a TodosList that contains Todo items. You wish to be able to react to the following events. In any Todoitem, when: The title is changed The completion status is toggled In the TodosList, when: A new item is added An existing item is removed Diving In Here is a basic representation of the respective domain classes:

On-Call That Doesn’t Suck: A Guide for Data Engineers

Aggregated on: 2025-04-29 18:28:32

In large-scale data platforms, reliability doesn’t end with the pipeline's DAG finishing successfully. It ends when the data consumers, whether dashboards, ML models, or downstream pipelines, can trust the data. But ensuring this is harder than it sounds. Poorly designed alerts can turn on-call into a reactive firefight, masking the signal with noise and reducing operator effectiveness. This article presents five engineering principles for scalable, actionable, and low-fatigue data quality monitoring systems, derived from real-world learnings.

Unlocking AI Coding Assistants Part 2: Generating Code

Aggregated on: 2025-04-29 17:28:32

AI coding assistants can help you build working code faster, eliminate manual repetition, and even propose solutions you might not have considered. In this blog, we'll explore how AI tools can become a powerful coding ally, saving you time, boosting creativity, and making your work smoother and more efficient. Enjoy! Introduction This article is the second in the series, with emphasis on generating code. The first part can be read here: "Unlocking AI Coding Assistants Part 1: Real-World Use Cases."

Build an MCP Server Using Go to Connect AI Agents With Databases

Aggregated on: 2025-04-29 16:28:32

Like many of you, I have been playing around with Model Context Protocol (MCP). To dive in, I built a sample MCP server implementation for Azure Cosmos DB with Go. It uses the Go SDK, and mcp-go as the MCP Go implementation.

Debugging Core Dump Files on Linux - A Detailed Guide

Aggregated on: 2025-04-29 15:43:32

Core dumps play a key roll role in debugging programs that exit abnormally. They preserve a state of a program at failure, and with them, programmers can view and identify causes of failures. In this article, a walkthrough is taken through a step-by-step exercise of enabling, creating, and checking out core dumps in Linux and touches on high-end tools and techniques for debugging sophisticated failures, and enables quick diagnoses and resolution. 1. Enabling Core Dumps in Linux Check and Set ulimit Check for current value for core dumps:

The Transformative Power of Artificial Intelligence in Cloud Security

Aggregated on: 2025-04-29 14:13:32

Cloud computing has reshaped how businesses operate, offering unmatched scalability, flexibility, and cost-efficiency. However, as organizations continue to shift critical operations to the cloud, they face escalating cybersecurity challenges. Traditional security systems often struggle to protect complex, interconnected cloud environments from increasingly sophisticated cyberattacks. Artificial Intelligence (AI) has emerged as the ultimate game-changer in cloud security. By enabling real-time threat detection, predictive analytics, and automated responses, AI is addressing challenges that older systems cannot handle. A report from Cybersecurity Ventures highlights that by 2028, spending on AI in cybersecurity is expected to exceed $60 billion, underscoring its growing importance. This article explores the evolving role of AI in cloud security, the benefits it brings, and the challenges it helps organizations overcome. This article explores how AI is reshaping cloud security, supported by graphs that provide insights into data trends and AI’s impact.

The Role of Artificial Intelligence in Climate Change Mitigation

Aggregated on: 2025-04-29 13:13:32

Climate change is among the most demanding global challenges we have. Governments and organizations worldwide are trying to figure out ways to tackle it. Amidst all this, several branches of technology, especially artificial intelligence, are emerging as major contributors to climate change mitigation and adaptation. Understanding the role of AI in climate change mitigation has opened doors to impactful projects. It has also highlighted a number of opportunities for developers to leverage the wonders of technology for a sustainable future. As we approach a new year, the contribution of AI towards mitigating climate change is expected to grow significantly. We owe this growth to huge improvements in computational power, data availability, and algorithmic efficiency. Let me guide you through all the ways developers can use AI effectively to tackle the challenges climate change brings.

How To Replicate Oracle Data to BigQuery With Google Cloud Datastream

Aggregated on: 2025-04-29 12:43:32

This technical guide outlines the steps to set up data replication using Google Cloud Datastream. Specifically, it details the process of setting up data replication from an Oracle 19c database hosted on a Google Compute Engine virtual machine into Google BigQuery. The tutorial covers all necessary steps, including prerequisites—enabling APIs and configuring firewalls, setting up the Oracle source environment, establishing secure networking, creating connection profiles for both Oracle and BigQuery in Datastream, preparing the Oracle database for Change Data Capture (CDC), and finally, creating and validating the Datastream replication job. Prerequisites Before proceeding, ensure the following Google Cloud APIs are enabled within your project. This is done through the Google Cloud Console under APIs & Services

Filtering Messages With Azure Content Safety and Spring AI

Aggregated on: 2025-04-28 21:43:32

As AI-powered applications like chatbots and virtual assistants become increasingly integrated into our daily lives, ensuring that they interact with users in a safe, respectful, and responsible manner is more important than ever. Unchecked user input or AI-generated content can lead to the spread of harmful language, including hate speech, sexually explicit content, or content promoting violence or self-harm. This can negatively affect the user experience and may also lead to legal or ethical problems.

Why I Started Using Dependency Injection in Python

Aggregated on: 2025-04-28 20:28:32

When I first started building real-world projects in Python, I was excited just to get things working. I had classes calling other classes, services spun up inside constructors, and everything somehow held together. But deep down, I knew something was off.

Building Data Pipelines With Jira API

Aggregated on: 2025-04-28 19:43:32

I’ve spent years building data pipelines and connecting project management to technical workflows. Disconnected systems lead to manual errors and delays, problems that Jira’s API helps solve. This tool lets code interact directly with project boards, automating tasks such as creating tickets when data checks fail or updating statuses after ETL.

Doris: Unifying SQL Dialects for a Seamless Data Query Ecosystem

Aggregated on: 2025-04-28 19:13:32

In the field of big data, different database systems often use different SQL dialects. This is similar to people from different regions speaking different languages, which brings great trouble to data analysts and developers. When an enterprise needs to integrate multiple data sources for analysis, it may have to spend a great deal of time and effort switching between different SQL syntaxes. However, Apache Doris breaks this barrier with its powerful SQL dialect compatibility and builds a unified data query ecosystem for users.

Mastering Shift-Left: The Ultimate Guide to Input Validation in Jenkins Pipelines

Aggregated on: 2025-04-28 18:43:32

Successful software development hinges on maintaining a balance between speed and quality. To stay ahead, many organizations are progressively adopting a shift-left approach. Rather than waiting until the end to catch bugs, this strategy emphasizes conducting quality checks and testing much earlier in the development process. One crucial aspect of this approach is input validation—ensuring that the configurations used in builds are correct right from the start. In this tutorial, we’ll walk through how to create a custom input validation framework for Jenkins pipeline. We’ll cover how to validate different input configurations such as JSON files, YAML files, and environment variables. With this system, shift-left framework can catch potential issues early and avoid delays in build and deployment process.

Contextual AI Integration for Agile Product Teams

Aggregated on: 2025-04-28 17:28:32

TL; DR: Not Onboarding But Integration Stop treating AI as a team member to “onboard.” Instead, give it just enough context for specific tasks, connect it to your existing artifacts, and create clear boundaries through team agreements. This lightweight, modular approach of contextual AI integration delivers immediate value without unrealistic expectations, letting AI enhance your team’s capabilities without pretending it’s human. Contextual AI Integration for Agile Product Teams Imagine this scenario: An empowered product team implements an AI assistant to help with feature prioritization and customer insights. Six weeks later, the Product Owner finds its ranking suggestions use irrelevant criteria, product designers notice it ignores established design patterns, and developers see it making technically sound suggestions that are misaligned with their architecture. Despite everyone using the same AI tool, it doesn’t understand how the product team actually works.

Building a Simple To-Do App With Model Context Protocol (MCP)

Aggregated on: 2025-04-28 16:13:32

What Is MCP? The Model Context Protocol (MCP) is an open protocol that standardizes how applications, tools, and AI models provide and access context. Think of MCP as the “USB-C port for AI applications”—just as USB-C lets you connect all sorts of devices with a single standard, MCP lets you connect AI models, desktop apps, and tools to a wide variety of data sources and capabilities in a consistent way. MCP is especially useful for building agents and complex workflows on top of large language models (LLMs), making it easy to integrate your own data and tools into AI-powered environments.