News Aggregator

Challenges of Using LLMs in Production: Constraints, Hallucinations, and Guardrails

Aggregated on: 2025-03-28 19:13:15

Large language models (LLMs) have risen in popularity after the release of Chat-GPT. These pre-trained foundation models enable rapid prototyping, and companies want to use this cool technology. However, their probabilistic nature and lack of built-in constraints often lead to challenges once they are out of prototyping mode. Let us consider an example of classifying news articles based on the content in the article to discuss the challenges one would encounter. Current LLMs have issues such as non-adherence to instructions, hallucinations, and possibly spitting out something that you don't want. This article explores these challenges with an example of classifying news articles into categories based on the content in the article and offers actionable strategies to mitigate them.

Ansible Security and Testing Tools for Automation

Aggregated on: 2025-03-28 18:13:15

Automation has become the cornerstone of modern IT operations, enabling organizations to streamline processes, reduce manual errors, and improve efficiency. However, as automation grows in complexity and scale, security risks also increase. Misconfigured infrastructure, untested playbooks, and vulnerabilities in automation workflows can expose organizations to significant threats. After my article on using SonarQube for Ansible code scanning and quality checks, this article covers additional tools and frameworks required for secured automation.

Understanding the Importance of Web Accessibility

Aggregated on: 2025-03-28 17:28:15

The process of creating websites and web apps that are usable by individuals with disabilities is known as web accessibility. This encompasses people with a range of disabilities, including: Visual: Low vision, color blindness, and blindness Auditory: Hard of hearing, deaf Cognitive: Memory problems, learning issues Motor: Paralysis, tremors, and trouble using hands An accessible web enables these individuals to view, understand, interact with, and contribute to the online environment. Here are a few examples of accessibility features:

Real-World Garbage Collection Scenarios and Solutions

Aggregated on: 2025-03-28 16:13:15

If you’re experiencing Java performance problems, where do you start looking for solutions? Is GC tuning really worthwhile? How do you analyze the GC logs to identify and fix bottlenecks? This article looks at some real-life success stories, where organizations were able to achieve dramatic performance gains simply by tweaking GC.

Why Mocking Sucks

Aggregated on: 2025-03-28 15:13:15

Developers love mocking. It’s been a go-to solution for years: Simulate external services, run tests faster, and avoid the overhead of real APIs. But here’s the truth — mocking is overused and often dangerous. It deceives you into thinking your system is stable, hiding critical failures that only appear when your code hits the real world. APIs change. Rate limits throttle you. Authentication flows break. Your tests will still pass with green colors while your app crashes in production. Overusing mocks can turn your tests into a house of cards, giving you false confidence and creating hidden technical debt that slows teams down. In complex workflows — like payments or authentication — mocks fail to capture the true behavior of interconnected services.

Security in the CI/CD Pipeline

Aggregated on: 2025-03-28 14:28:15

As development cycles speed up, integrating security into the CI/CD pipeline is essential to embed security checks early and throughout the process to prevent vulnerabilities from creeping into production. This article delves deeper into the technical details, code examples, and configurations to build a robust, secure CI/CD pipeline. A CI/CD pipeline is an automated workflow that streamlines the process of software development from code integration to deployment. It comprises two main practices:

Using Terraform Moved Block to Refactor Resources

Aggregated on: 2025-03-28 13:28:15

Terraform introduced the moved block in version 1.1.0. This block provides a straightforward way to refactor resources by explicitly mapping old resource addresses to new ones. It significantly reduces the risk of losing state or manually managing imports during renames or moves. In this article, we’ll explain what the moved block is and how to use it to streamline resource restructuring for smoother and safer Terraform updates.

Building a Scalable ML Pipeline and API in AWS

Aggregated on: 2025-03-28 12:13:15

With rapid progress in the fields of machine learning (ML) and artificial intelligence (AI), it is important to deploy the AI/ML model efficiently in production environments. This blog post discusses an end-to-end ML pipeline on AWS SageMaker that leverages serverless computing, event-trigger-based data processing, and external API integrations. The architecture downstream ensures scalability, cost efficiency, and real-time access to applications.

The Art of Postmortem

Aggregated on: 2025-03-28 11:28:15

How an individual responds to setbacks defines their character, and the same is true of companies. Authoring a postmortem is the traditional way to learn from failures. The postmortem is a core foundation of company culture. Successful tech companies have rigorous postmortem processes that have been refined meticulously over time. A company that learns from its mistakes will protect an incalculable amount of business value by preventing future outages.

Accurate Quantitative Analysis With ChatGPT and Azure AI Hub

Aggregated on: 2025-03-27 21:13:15

LLMs are not very good at quantitative analysis. For example, when I asked ChatGPT, "Which number is bigger, 9.9 or 9.11?" it incorrectly responded with 9.11. In another example, I have an Excel file containing a large amount of quantitative data. The maximum word count for a single prompt that ChatGPT can handle is around 4,000 words (approximately 16,000 characters). If I try to query this data, it may not fit within the context window.

Moving PeopleSoft ERP Data Between Databases With Data Mover Scripts

Aggregated on: 2025-03-27 20:28:15

Why Transfer or Move Data? Transferring PeopleSoft application data between databases is necessary for various business needs, including: Application upgrades User or system testing Training environment setup This article covers the essential commands and step-by-step instructions needed to perform data transfer effectively.

Using Heap Dumps to Find Memory Leaks

Aggregated on: 2025-03-27 19:13:15

A JVM (Java Virtual Machine) runs programs in Java and many other languages and provides the runtime environment, CPU, memory, and security management. At any particular moment, the running JVM has many objects, and a heap dump is a snapshot of the memory allocated to all these objects. In this post, we will discuss how to use heap dumps to find memory leaks.

Self-Healing Data Pipelines: The Next Big Thing in Data Engineering?

Aggregated on: 2025-03-27 18:13:15

I'm an enthusiastic data engineer who always looks out for various challenging problems and tries to solve them with a simple POC that everyone can relate to. Recently, I have thought about an issue that most data engineers face daily. I have set alerts on all the batch and streaming data pipelines. When the errors reach a threshold limit or if the data pipeline fails, we get failure notifications immediately in the email inbox. Everything seemed fine until I noticed one of our critical datasets could not be loaded into BigQuery. After investigating the error logs, I found several messages with "missing required data." I felt ‘lost’ seeing these frequent raw data issues from a user-inputted file.

XAI: Making ML Models Transparent for Smarter Hiring Decisions

Aggregated on: 2025-03-27 17:28:15

Recruiting is extremely tough as outsiders may disagree with you — I’ve been there, sifting through resumes, trying to spot the perfect fit for a role. I’ve noticed more companies using machine learning to screen candidates and predict job success lately. The problem? When an algorithm rejects someone, there’s often no clear reason why. That’s where explainable AI (XAI) changes the game. Think of it as a recruiter’s secret weapon — it takes the mystery out of AI decisions and turns machine learning into a real hiring partner. Let’s dive into why this matters and how to use it.

Automatic Versioning in Mobile Apps

Aggregated on: 2025-03-27 16:28:15

Picture this: Your mobile app is evolving quickly, with new features requiring changes to the local database. Your users expect seamless upgrades, and your stakeholders want new functionality delivered fast. The challenge becomes even trickier when you realize you need to update the app's database schema without disrupting existing data or forcing users into error-prone migrations. In this article, I’ll share a practical, automatic versioning approach I developed that simplifies database versioning and migration for mobile apps. This system lets developers focus on data models instead of manually scripting version changes, while making sure users’ data stays intact across updates.

Creating an Application With a Personality

Aggregated on: 2025-03-27 15:13:15

Many years ago, one of my favorite former colleagues left the company where we worked together, and he wrote a goodbye email. I've seen a few, but this was the most imaginative of them all. He wrote it in the form of a Jenkins notification email about a failed Maven build. If you read the build logs carefully, you could see that the build failed because my colleague left the company. This memory gave me the idea of what an application would say about itself if we could ask.

Optimized Metrics Generation With Metadata-Driven Dynamic SQL

Aggregated on: 2025-03-27 14:13:15

The creation of precise and adaptable metrics remains crucial for successful monitoring, auditing, and reporting in present-day data-centric settings. This article describes an optimized method to create metrics and dynamic SQL with metadata-based techniques using Oracle packages. This process combines configuration tables, dynamic SQL templates, and merge operations to create a metrics generation framework that scales well and remains easy to maintain and adjust. Background The process is built around an audit package and a set of Data Definition Language (DDL) statements that define critical tables for storing audit facts, dynamic SQL templates, and metric results.

Breaking the Context Barrier of LLMs: InfiniRetri vs RAG

Aggregated on: 2025-03-27 13:28:15

Large language models (LLMs) are reshaping the landscape of artificial intelligence, yet they face an ongoing challenge — retrieving and utilizing information beyond their training data. Two competing methods have emerged as solutions to this problem: InfiniRetri, an approach that exploits the LLM’s own attention mechanism to retrieve relevant context from within long inputs, and retrieval-augmented generation (RAG), which dynamically fetches external knowledge from structured databases before generating responses. Each of these approaches presents unique strengths, limitations, and trade-offs. While InfiniRetri aims to maximize efficiency by working within the model’s existing architecture, RAG enhances factual accuracy by integrating real-time external information. But which one is superior?

The Future of DevOps

Aggregated on: 2025-03-27 12:13:15

When I was asked to think about my technology predictions for 2025, it occurred to me how much happened from 2023 until now, where the dust is still settling and the reverberations from these seismic shifts in our ecosystem are still taking hold of our industry. The Infrastructure as Code (IaC) landscape is entering an era of transformation. The ubiquitous tools we came to know and love are being replaced with newer more open options — if we just recap all of the major milestones from then until now: Terraform is losing ground to other more open solutions after closing its license in August 2023, the fork of OpenTofu and its contribution to the Linux Foundation, and the consequent acquisition of Hashicorp by IBM, as well as the growing momentum around other IaC tooling like Crossplane, Pulumi and even ARM templates.

How to Port CV/ML Models to NPU for Faster Face Recognition

Aggregated on: 2025-03-27 11:28:15

Recently, our development team faced a new challenge: one of our partners was implementing an access control system using a single-board computer from Forlinx. To meet the existing time constraints for face recognition operations, we decided to port our models to the NPU. What we can say after porting is that the NPU is generally a reliable way to put heavy processing on an edge device. So, our partner needed to detect faces in a video stream and provide 1:1 matching (face verification). To better understand what this means, let's recall the basic face recognition pipeline diagram.

A Comprehensive Guide to Protect Data, Models, and Users in the GenAI Era

Aggregated on: 2025-03-27 10:13:15

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Generative AI: The Democratization of Intelligent Systems. Generative AI (GenAI) is transforming how organizations operate, enabling automation, content generation, and intelligent decision making at an unprecedented scale. From AI-powered chatbots to advanced code generation and creative design, GenAI is revolutionizing industries by increasing efficiency and innovation. However, alongside these advancements come significant security risks that organizations must address.

The Real-World Guide to Event-Driven Microservices

Aggregated on: 2025-03-26 21:13:14

Let's face it — if you've worked with microservices, you've probably experienced that moment of dread when your carefully designed system starts to feel like a complicated web of API calls. You know the scene: one service goes down, and suddenly your application looks like a house of cards. Sound familiar? Don't worry — you're not alone, and there's a better way forward. Breaking Free from the Synchronous Nightmare Remember the days when we thought REST APIs were the answer to everything? I certainly do. We'd build these beautiful service-to-service communications, and everything would work perfectly... until it didn't. That's when many of us discovered event-driven architecture (EDA), and it was like finding a light switch in a dark room.

Modern QA Practices to Enhance Software Reliability

Aggregated on: 2025-03-26 20:28:14

Imagine a scenario: You are working at breakneck speed to roll out a new IT product or a business-critical update, but quality control workflows lack efficiency. They are mainly manual and performed late in the development cycle. This challenges your ability to cope with pressing deadlines, innovate, and remain competitive, as manual efforts are slow, workflows lack fast and continuous feedback loops, and critical and major issues arise just before the release. Transitioning to more advanced testing practices can turn the tide and positively impact operational productivity due to early defect detention, increased test coverage, and better software stability, allowing businesses to economize, ship high-quality IT solutions faster, and elevate end-user satisfaction.

Ensuring Data Quality With Great Expectations and Databricks

Aggregated on: 2025-03-26 19:13:14

Data quality checks are critical for any production pipeline. While there are many ways to implement them, the Great Expectations library is a popular one. Great Expectations is a powerful tool for maintaining data quality by defining, managing, and validating expectations for your data. In this article, we will discuss how you can use it to ensure data quality in your data pipelines.

Avoid Cross-Shard Data Movement in Distributed Databases

Aggregated on: 2025-03-26 18:13:14

Modern applications rely on distributed databases to handle massive amounts of data and scale seamlessly across multiple nodes. While sharding helps distribute the load, it also introduces a major challenge — cross-shard joins and data movement, which can significantly impact performance. When a query requires joining tables stored on different shards, the database must move data across nodes, leading to:

Jakarta NoSQL 1.0: A Way To Bring Java and NoSQL Together

Aggregated on: 2025-03-26 17:28:14

NoSQL is no longer the exception — it's a key part of modern data architectures. With the release of Jakarta NoSQL 1.0, Java developers finally gain a standardized, extensible way to interact with NoSQL databases across document, key-value, column, and graph data models — all while staying aligned with Jakarta EE principles. This article introduces the Jakarta NoSQL 1.0 specification, which boosts productivity, simplifies mapping, and provides fluent, type-safe access to NoSQL data.

Loader Animations Using Anime.js

Aggregated on: 2025-03-26 16:28:14

Anime.js is a lightweight JavaScript animation library that allows developers to create smooth and powerful animations with ease. Why Use Anime.js? Simple and flexible syntax Supports multiple animation types (CSS properties, SVG, DOM attributes, JavaScript objects) High performance and lightweight (~17KB gzipped) Works well with other libraries and frameworks Getting Started Anime.js is a Javascript library. You can download it from the public GitHub or use the CDN URL.

A Beginner's Guide to Spark UI: Concepts and How to Use It

Aggregated on: 2025-03-26 15:28:14

If you have been working with petabytes of data, are a data engineer, or are looking to get into data engineering, I am sure you have heard about Apache Spark, a distributed data processing system. Apache Spark is a Unified computing engine, clubbed with a set of libraries for parallel data processing on compute clusters. It is not primarily designed as a storage system. Apache Spark can run locally in your system or on the cloud — using AWS EMR, AWS Glue, Google Cloud Dataproc, Databricks, etc. However you may use it, one thing before you start is to understand the basics — Spark UI, RDDs, DataFrames, Transformations/Actions, Job, Stages, Tasks.

Best Ways to Write Clean and Quality Python Code

Aggregated on: 2025-03-26 14:13:14

When considering whether to use classes in Python code, it's important to weigh the benefits and contexts where they are most appropriate. Classes are a key feature of object-oriented programming (OOP) and can provide clear advantages in terms of organization, reusability, and encapsulation. However, not every problem requires OOP. When to Use Classes Encapsulation and Abstraction Encapsulation. Classes allow you to bundle data (attributes) and methods (functions) that operate on the data into a single unit. This helps in keeping related data and behaviors together. Abstraction. Classes can hide the complex implementation details and expose only the necessary parts through public methods. Reusability Reusable components. Classes can be represented multiple times, allowing you to create reusable components that can be used in different parts of your application. Inheritance and Polymorphism Inheritance. Classes allow you to create new classes based on existing ones, reusing the code and reducing redundancy. Polymorphism. Classes enable you to define methods in such a way that they can be used interchangeably, improving flexibility and integration. Stateful Function Using Classes Using a class is a more explicit way to manage state. Use classes when the stateful function requires multiple methods.

Lakehouse: Manus? MCP? Let’s Talk About Lakehouse and AI

Aggregated on: 2025-03-26 13:13:14

Since OpenAI launched ChatGPT in late 2022, AI has become an unavoidable topic in every field. Many companies have even transformed into AI companies overnight. The data analytics domain is no exception — Databricks, Snowflake, and Elasticsearch have all redefined themselves as AI data platforms or AI-ready data analytics and search products. Setting aside the “hype”, in today’s article, we’ll explore what relationship actually exists between Lakehouse and AI. Before diving into this topic, let’s start with a simple example demonstrating the connection between data and AI.

How to Integrate Event-Driven Ansible With Kafka

Aggregated on: 2025-03-26 12:13:14

Integrating event-driven Ansible with Kafka enables seamless real-time automation by continuously monitoring Kafka topics and triggering Ansible playbooks based on specific events. This integration is particularly beneficial in IT operations, where it streamlines automated incident response, reducing reliance on manual intervention. Leveraging Kafka’s distributed architecture ensures high scalability, rapid event processing, and improved system resilience. Ultimately, this approach enhances operational efficiency by enabling proactive, intelligent automation that minimizes downtime and optimizes resource management.

Building AI-Driven Intelligent Applications: A Hands-On Development Guide for Integrating GenAI Into Your Applications

Aggregated on: 2025-03-26 11:13:14

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Generative AI: The Democratization of Intelligent Systems. In today's world of software development, we are seeing a rapid shift in how we design and build applications, mainly driven by the adoption of generative AI (GenAI) across industries. These intelligent applications can understand and respond to users' questions in a more dynamic way, which help enhance customer experiences, automate workflows, and drive innovation. Generative AI — mainly powered by large language models (LLMs) like OpenAI GPT, Meta Llama, and Anthropic Claude — has changed the game by making it easy to understand natural language text and respond with new content such as text, images, audio, and even code.

GenAI: From Prompt to Production

Aggregated on: 2025-03-25 21:58:14

The Idea A project time-tracking system should allow entry of: Clients have one or more projects consisting of one or more tasks. Tasks have timesheet entries, completed by persons entering hours working for a client. Invoices are created by adding invoice items linked to billable timesheet lines. Once the invoice is marked as ready, send the information to Kafka for invoice processing. The Prompt GenAI Logic is a web page, like many chatbots, that allows the user to enter a prompt. The more details provided, the better the result (although you can iterate to add or change the outcome using the “Iterate” button).

A Systematic Approach for Java Software Upgrades

Aggregated on: 2025-03-25 21:43:14

The amount of business logic embedded in the form of code in software systems is so huge and valuable that you don’t always need to think in terms of replacing them with entirely new systems. Rather, software systems should facilitate evolution both in terms of functionality and in terms of technological upgrades. This is truer in transactional systems, especially in domains including, but not limited to, finance, travel, transportation, logistics (TTL), and e-commerce. While much literature has been written about how to manage functional changes in software applications, technology upgrades are non-trivial, and many times, developers are left out to try and test their own intuition.

Java Reborn: Conquering Cloud-Native and Next-Gen Concurrency

Aggregated on: 2025-03-25 19:58:14

Although Java has been around for long time, the future looks exciting. Historically being the go to language for building enterprise applications, the language has grown to match the speed of development of the cloud development technology. In this article, we take a closer look as to how Java keeps on evolving with focus on cloud native designs, improving concurrency, microservices architecture, and new initiatives that promise to change the way Java is seen and used.

Recursive Feature Elimination in Practice

Aggregated on: 2025-03-25 19:13:14

The effectiveness of machine learning models often hinges on a deceptively simple question: Which features actually matter? The challenge becomes particularly evident as datasets grow larger and more complex. Modern data collection gives us access to hundreds or even thousands of features, but quantity doesn't always translate to quality. Processing all these features wastes computational resources and disrupts your model's performance. Feature selection addresses this challenge by identifying the subset of features that contribute most meaningfully to your model's predictions. While several approaches exist for tackling this problem, Recursive Feature Elimination (RFE) stands out for its systematic and interpretable approach. By iteratively removing less important features, RFE helps you build models that are both more efficient and more accurate.

Lakehouse: Starting With Apache Doris + S3 Tables

Aggregated on: 2025-03-25 17:58:14

Among the numerous AI products launched at the AWS re:Invent 2024 conference, Amazon S3 Tables might have seemed inconspicuous. However, for database professionals, the emergence of S3 Tables signifies that the era of modular data analytics has arrived. S3 Tables are a special type of S3 Bucket with built-in support for Apache Iceberg. They stand alongside the previously introduced General Purpose Bucket and Directory Bucket, collectively referred to as Table Bucket. This means you can now create a table bucket as easily as you would create a standard S3 Bucket.

Agentic AI and Generative AI: Revolutionizing Decision Making and Automation

Aggregated on: 2025-03-25 17:28:14

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Generative AI: The Democratization of Intelligent Systems. The rapid advancement of artificial intelligence (AI) creates breakthroughs that span multiple industries. Among many developments, agentic AI and generative AI stand out as two transformative powers. Although these systems work differently because they serve distinct functions, they bring substantial benefits when used together. Generative AI focuses on content creation through deep learning transformer models that learn from extensive datasets. This technology enables increased human productivity in content creation tasks as well as design, marketing activities, and software development by delivering text, images, code, and music outputs.

Make ML Models Work: A Real-World Take on Size and Imbalance

Aggregated on: 2025-03-25 16:13:14

The Initial Hurdle In NLP classification tasks, especially those involving text descriptions, it's common to encounter two significant hurdles: large model sizes and imbalanced datasets. A large model can be difficult to deploy and manage, while class imbalance can lead to poor predictive performance, particularly for minority classes. Imagine you are building a system to automatically categorize product descriptions into various product categories. The project began with a dataset of close to 40,000 records, where each record contained a short product title and a longer product description, along with its corresponding category. The initial Random Forest model, while achieving a decent accuracy of around 70%, ballooned to a whopping 11 GB size.

Mastering Async Context Manager Mocking in Python Tests

Aggregated on: 2025-03-25 15:13:14

Testing asynchronous Python code can be challenging, especially when dealing with nested context managers. In this tutorial, we’ll explore how to effectively mock nested async context managers to create clean, reliable tests for complex async code structures. The Challenge of Testing Nested Async Context Managers Modern Python codebases often use asynchronous context managers (using async with) for resource management in async functions. When these context managers are nested, testing becomes complicated. Consider a client that uses nested context managers to manage HTTP sessions and requests:

Using KRaft Kafka for Development and Kubernetes Deployment

Aggregated on: 2025-03-25 14:43:14

With KRaft for Kafka ZooKeeper is no longer needed. KRaft is a protocol to select a leader among several server instances. That makes the Kafka setup much easier. The new configuration is shown on the example of the MovieManager project.

Video Generation With Java: Leverage Nova and Amazon Bedrock

Aggregated on: 2025-03-25 13:58:14

Amazon Nova is a new generation of state-of-the-art (SOTA) foundation models (FMs) that deliver frontier intelligence and industry-leading price performance, released on December 24. It is available exclusively on Amazon Bedrock. As this model is quite new, there are not a lot of examples of its use, especially in Java. As of this writing, the official AWS docs contain only Python code examples, and there are a couple.

How to Get Word Document Form Values Using Java

Aggregated on: 2025-03-25 13:28:14

In this article, we’ll provide some background about Word DOCX forms and discuss how form values (i.e., form responses) can be programmatically extracted from completed DOCX forms in Java. We’ll discuss the specific way in which form responses are stored in the DOCX file structure and how that impacts a programmatic process aimed at retrieving them. Towards the end of this article, we’ll learn about a few different APIs we can use to build an expedited DOCX form-value retrieval workflow in Java.

The Role of Sanity Testing in Performance Engineering

Aggregated on: 2025-03-24 22:43:13

As a CTO, my role extends beyond overseeing technical solutions — I work closely with engineering teams to ensure performance testing strategies align with business goals. One of the recurring challenges I’ve observed is how sanity testing, despite being a simple step, often determines the success or failure of performance testing efforts. Many teams focus on running large-scale performance tests, ensuring their applications can handle peak loads, but neglect the essential first step — validating the test scripts and basic system functionality before executing a full-scale load test. Over the years, I’ve seen how overlooking this step can lead to wasted time, misleading results, and frustration.

Hybrid Backup Strategies: On-Premises vs Cloud for DevOps

Aggregated on: 2025-03-24 20:43:13

Where is it safer to keep your DevOps data backups — in the cloud or on-premise? For sure, when it comes to SMBs or large businesses, everything depends on their corporate, legal, or compliance requirements. Their security teams have a proper evaluation of the security issues of each of the deployment models for a backup and analyze which one suits them the most. However, while many companies opt for one of the variants, others are starting to rely more on a hybrid deployment model.

Text Clustering With Deepseek Reasoning

Aggregated on: 2025-03-24 19:13:13

In this article, we will explore the world of reasoning in LLM. DeepSeek has provided us with an excellent tool to explain our inferences and build machine learning systems that inspire more confidence and trust from end users. Machine learning models are black boxes by default and do not provide out-of-box explanations (XAI) for their decisions. We will use the DeepSeek model and try to add the explanation or reasoning aspect to our machine learning world.

Breaking AWS Lambda: Chaos Engineering for Serverless Devs

Aggregated on: 2025-03-24 18:13:13

The Day Our Serverless Dream Turned into a Nightmare It was 3 PM on a Tuesday. Our "serverless" order processing system — built on AWS Lambda and API Gateway — was humming along, handling 1,000 transactions/minute. Then, disaster struck. A sudden spike in traffic caused Lambda timeouts, API Gateway threw 5xx errors, and customers started tweeting, “Why can’t I check out?!” The post-mortem revealed the harsh truth: we’d never tested failure scenarios. Our “resilient” serverless setup had no fallbacks, retries, or plans for chaos.

How to Build a React Native Chat App for Android

Aggregated on: 2025-03-24 17:28:13

In this tutorial, we will walk you through the complete process of integrating the MirrorFly Chat SDK into your React Native app. With this React Native Chat SDK, you can create a real-time chat app within 10 minutes. Moving forward, we'll cover the following steps:

5 Life Hacks to Protect Your Project from Escaped Defects

Aggregated on: 2025-03-24 16:28:13

Every project team knows that there is nothing worse than getting a message from an annoyed customer that there is a critical bug found in production. 'How did you let this get through? Did you even test this build?!' These are common complaints that could make your team feel anxious and insecure.

Supercharging Pytest: Integration With External Tools

Aggregated on: 2025-03-24 15:43:13

Testing is a crucial aspect of software development, and while Python’s Pytest framework is powerful on its own, integrating it with external tools can significantly enhance the testing workflow. Let's explore how to supercharge Pytest implementation by combining it with various complementary tools and systems.