News Aggregator

How ARIA Snapshot Testing Solves Common Playwright Issues

Aggregated on: 2025-03-05 16:13:03

The challenges of testing various elements on a webpage, such as headings and links, noting that traditional code-based tests can become complex and brittle. I am not a huge fan of using screenshots for testing, as they can break with minor layout changes. Playwright’s ARIA Snapshots offer a powerful method to validate the accessibility tree of your web applications, ensuring that content is both accessible and correctly structured. By capturing the hierarchical representation of accessible elements, you can compare snapshots over time to detect unintended changes.

Mastering Scalability in Spring Boot

Aggregated on: 2025-03-05 15:28:03

Scalability is a fundamental concept in both technology and business that refers to the ability of a system, network, or organization to handle a growing amount of requests or ability to grow. This characteristic is crucial for maintaining performance and efficiency as need increases. In this article, we will explore the definition of scalability, its importance, types, methods to achieve it, and real-world examples.

Actuator Enhancements: Spring Framework 6.2 and Spring Boot 3.4

Aggregated on: 2025-03-05 14:28:03

In Spring Boot, an Actuator is a framework module that provides features for managing and monitoring applications. It helps developers and operations teams to gain insights into the run-time behavior of their applications and provides capabilities for health checking, metrics collection, and application management via a set of built-in and customizable endpoints. Traditional Implementation of Actuators Monitor health of the applications using endpoints like /actuator/health. Provide application metrics such as memory usage and thread count using /actuator/metrics. Endpoints like /info, /env, and /beans expose state of the application. Developers had to integrate monitoring tools manually. Example of traditional use:

Deep Learning Fraud Detection With AWS SageMaker and Glue

Aggregated on: 2025-03-05 13:13:03

Fraud detection has become a top priority for businesses across industries. With fraudulent activities growing more sophisticated, traditional rule-based approaches often fall short in addressing the constantly evolving threats. Detecting and preventing fraud — be it financial scams, identity theft, or insurance fraud — is crucial, especially when global fraud losses run into billions of dollars annually. This guide discusses how deep learning can improve fraud detection with AWS SageMaker and AWS Glue. Deep learning, a branch of machine learning, excels at uncovering complex patterns in large datasets and adapting to emerging fraud techniques. AWS SageMaker, a comprehensive machine learning platform, equips businesses with the tools to build, train, and deploy advanced deep learning models, while AWS Glue streamlines data preparation and integration with its fully managed ETL capabilities.

Ansible Event-Driven Automation for Real-Time Operations

Aggregated on: 2025-03-05 12:13:03

Event-driven automation allows the service team to execute predefined actions automatically in response to specific events within a systems landscape. This approach improves operational efficiency by minimizing manual intervention and allowing systems to adapt quickly to changing conditions. Ansible, a popular open-source automation tool, incorporates event-driven features to support such dynamic and responsive automation. Key Components of Event-Driven Ansible Event-driven Ansible automation consists of three main components:

Essential Python Libraries: Introduction to NumPy and Pandas

Aggregated on: 2025-03-04 23:13:03

In Python programming, NumPy and Pandas stand out as two of the most powerful libraries for numerical computing and data manipulation. NumPy: The Foundation of Numerical Computing NumPy (Numerical Python) provides support for multi-dimensional arrays and a wide range of mathematical functions, making it essential for scientific computing.

Database Query Service With OpenAI and PostgreSQL in .NET

Aggregated on: 2025-03-04 22:13:03

Generate SQL queries based on natural language input In this blog post, we'll explore how to build a service that interacts with a PostgreSQL database and uses OpenAI's GPT-4 model to generate SQL queries based on natural language input. This service called NorthwindServicefromDB is designed to make it easier for users to query a database without needing to write SQL themselves. We'll walk through the code step by step, explaining each component and how it fits into the overall architecture.

Feather Wand: Your AI-Powered Companion for JMeter

Aggregated on: 2025-03-04 20:28:03

Imagine having an intelligent assistant right inside JMeter, ready to help you craft, optimize, and troubleshoot your test plans with ease. That’s exactly what Feather Wand, a new JMeter plugin, brings to the table — a sprinkle of AI magic to transform your performance testing experience. Let’s dive into what makes this tool special, how it works, and why it might just become your go-to JMeter sidekick — especially for performance test engineers. The Story Behind the Name Before we get technical, a quick nod to the whimsical origin of "Feather Wand." The name comes from my kids, who were inspired by an episode of Bluey, the charming animated show. In that episode, a simple feather turns into a magical wand, making ordinary things extraordinary (and hilariously heavy).

Automated Bug Fixing: From Templates to AI Agents

Aggregated on: 2025-03-04 19:28:03

If you've spent any time in software development, you know that debugging is often the most time-consuming and frustrating part of the job. What if AI could handle those pesky bugs for you? Recent advances in automated program repair (APR) are making this increasingly realistic. Let's explore how this technology has evolved and where it's headed.

React Performance Optimization: Tricks Every Dev Should Know

Aggregated on: 2025-03-04 18:13:02

Let’s face it: we’ve all been there. You build a sleek React app, only to watch it slow to a crawl as it grows. Buttons lag, pages take forever to load, and users start bouncing. Sound familiar? I’ve been in that exact spot — debugging performance issues at 2 AM, fueled by coffee and frustration. In this guide, I’ll share battle-tested strategies to optimize React apps, sprinkled with real-world war stories and practical examples. No jargon, no fluff — just actionable advice.

Integrating Redis With Message Brokers

Aggregated on: 2025-03-04 17:43:03

Let's look at how to integrate Redis with different message brokers. In this article, we will point out the benefits of this integration. We will talk about which message brokers work well with Redis. We will also show how to set up Redis as a message broker with practical code examples, and discuss how to handle message persistence and how to monitor Redis when it is used as a message broker.

AI Agents For Automated Claims Processing

Aggregated on: 2025-03-04 16:28:02

Agent-grounded models live for quite some time. They are generally enforced as computer simulations. An AI agent is a software operation that engages with its surroundings, collects information, and utilizes that data to negotiate predefined objectives. AI agents: Are software programs that accomplish jobs autonomously or semi-autonomously Run independently to design, implement, and optimize workflows Have proper boundaries to help execute tasks properly Help in driving better decision-making and functional effectiveness Can enable personalization Help in performing tasks accurately and consistently Manage and optimize complex systems Monitor and analyze security pitfalls in real time, delivering proactive measures to prevent breaches and guarantee data protection Increase productivity by reasoning, planning, and self-checking, releasing users from certain tasks Business Case for AI Agents Usage Today, CXOs see the IT budget as an area of overspending and are continuously looking for ways to reduce costs and time [1].

Building a Weather Service With Genkit and AI

Aggregated on: 2025-03-04 15:28:02

Overview This project demonstrates how to build an AI-enhanced weather service using Genkit, TypeScript, OpenWeatherAPI, and GitHub models. The application showcases modern Node.js patterns and AI integration techniques. Prerequisites Before you begin, ensure you have the following:

AI Agents for Data Warehousing

Aggregated on: 2025-03-04 14:13:02

The term "data warehousing" was first introduced in the 1980s, referring to the practice of storing data from various sources within an organization. The collected data is then utilized for reporting, decision-making, accurate analytics, better customer insights, and handling ad hoc queries. However, traditional data warehousing techniques come with significant challenges, including high setup and maintenance costs, slow processing speeds, and scalability limitations. However, with the rise of artificial intelligence, the introduction of DW Agent AI is revolutionizing data management, making processes more automated, efficient, and scalable.

The Critical Role of CISOs in Managing IAM, Including NHIs

Aggregated on: 2025-03-04 13:13:02

Who Should Own IAM in the Enterprise? Identity and access management (IAM) started as an IT function, with the entire focus on giving human users the right access to the right systems. But today, identity has become the primary attack surface, with at least 80% of all modern breaches involving compromised or stolen identities from adversaries who exploit poor identity. This reality has moved the responsibility for risk onto the shoulders of the team tasked with protecting the organization from attacks, namely security. Which ultimately means the CISO. However, there’s a major blind spot in this conversation: non-human identities (NHIs). This is a critical oversight. We are witnessing non-human identities (NHIs) outnumber humans by a factor of at least 45-to-one in the enterprise, with some estimates as high as 100 to 1. As organizations accelerate to deliver more code and products faster than ever, the number of these machine identities, such as service accounts, APIs, and automated workloads, will continually increase this imbalance. LLMs and the rapid adoption of new coding assistants and AI productivity tools will only rapidly accelerate this trend.

Next.js Theming: CSS Variables for Adaptive Data Visualization

Aggregated on: 2025-03-04 12:13:02

Theming is not just a choice but an important feature in modern web and mobile applications, as it allows for a more personalized, seamless, and tailored user experience. Theming becomes a must-have feature for SaaS applications integrating into other applications. Traditional theming techniques often involve hardcoded styles and rigid code configurations. This creates issues in the maintenance and scaling of applications. Furthermore, complexity grows even more when an application supports multiple themes across web and mobile devices. Modern CSS frameworks come with built-in theming support, but often, the themes they provide are fixed and don’t fit the needs of enterprise applications.

Handling Dynamic Data Using Schema Evolution in Delta

Aggregated on: 2025-03-03 22:28:02

One of the biggest challenges of managing data nowadays is its constantly changing nature. We recently came across a requirement to ingest survey data and send it for sentimental analysis. The survey data is very dynamic, and even for existing surveys, new questions will be added, modified, or deleted. As the data source evolves and adapts to new changes, the challenge is how to deal with the dynamically changing data to be represented in a table format. We implemented this by leveraging the schema evolution feature in Delta tables.

Time Data Series: The Rest of the Story

Aggregated on: 2025-03-03 21:28:02

It’s been a while since I wrote about PHP Zmanim — the work I’ve done with it and the things I’ve learned while implementing it. But despite the delay, I always intended to continue the conversation. That’s what we’re doing today. In my first post, I explained how to install and get started with the PHP Zmanim library. Then, in the next post, I dug into calculating more complex times and the real power of the tool — applying the most common Rabbinic opinions for various zmanim. I’m picking up where I left off with minimal overlap, so if you need to take a minute to get back up to speed, I’ve linked to those previous posts.

How I Made My Liberty Microservices Load-Resilient

Aggregated on: 2025-03-03 20:43:02

It started with an all-too-familiar problem: As the traffic spiked, our microservices started slowing down, some even crashing under the pressure. Users experienced frustrating delays and outright bulk API request failures, and reliability took a hit. IBM Liberty gave us a solid, lightweight foundation, but we needed to do more. To keep things running smoothly, we had to fine-tune our architecture and make our services truly resilient to heavy loads.

API Management as Code: A Declarative Approach to Scaling API Operations

Aggregated on: 2025-03-03 19:13:02

In the rapidly evolving landscape of software development, Application Programming Interfaces (APIs) have emerged as the fundamental building blocks of modern applications, facilitating seamless communication and data exchange between diverse software systems. However, as organizations experience growth and their digital ecosystems expand, the manual management of hundreds or even thousands of APIs becomes increasingly arduous and unsustainable. This is where the paradigm of API Management as Code emerges as a transformative solution, offering a declarative approach to the efficient and scalable management of API artifacts. This article explores the key concepts behind API management as code, the benefits of automation, and how technologies like GitOps and the operator pattern streamline API lifecycle management.

Materialized Views in Data Stream Processing With RisingWave

Aggregated on: 2025-03-03 18:28:02

Incremental computation in data streaming means updating results as fresh data comes in, without redoing all calculations from the beginning. This method is essential for handling ever-changing information, like real-time sensor readings, social media streams, or stock market figures. In a traditional, non-entrepreneurial calculation model, we need to process the entire dataset every time we get a new piece of data. It can be incompetent and slow. In incremental calculations, only the part of the result affected by new data is updated.

Understanding the Data Culture

Aggregated on: 2025-03-03 17:28:02

A data culture is the collective behaviors and beliefs of people who value, practice, and encourage the use of data and AI to propel organizational transformation. It equips everyone in an organization with intuitive, productive insights for tackling complex business challenges. Introduction: Data Culture Creating a data culture helps you accelerate the value of analytics and AI. It transforms the quality and speed of decision-making across an organization and forms a foundation of data trust and transparency.

Modern Data Processing Libraries: Beyond Pandas

Aggregated on: 2025-03-03 16:13:02

As discussed in my previous article about data architectures emphasizing emerging trends, data processing is one of the key components in the modern data architecture. This article discusses various alternatives to Pandas library for better performance in your data architecture. Data processing and data analysis are crucial tasks in the field of data science and data engineering. As datasets grow larger and more complex, traditional tools like pandas can struggle with performance and scalability. This has led to the development of several alternative libraries, each designed to address specific challenges in data manipulation and analysis.

Zero-Trust Infinite Security: Masking's Powerful New Ally

Aggregated on: 2025-03-03 15:13:02

Escalating data breach risks and intensifying regulatory guidelines have put organizations' readiness for privacy protection into the spotlight. Until now, obscuring data sets via different methods of masking has been the anchor, but rising uncertainty around the nature of attacks requires a more proactive approach. When applied with masking, zero-trust architectures have enabled organizations to shield sensitive information through various methods, such as role-based access, identity verification, and continuous encryption. The outcome? A robust and sophisticated defense against breaches.

Docker Bake: A Modern Approach to Container Building

Aggregated on: 2025-03-03 14:28:02

The traditional way of building Docker images using the docker build command is simple and straightforward, but when working with complex applications consisting of multiple components, this process can become tedious and error-prone. This is where Docker Bake comes in — a powerful and flexible tool for organizing multi-stage and parallel image building. In this article, we'll look at the capabilities of Docker Bake, its advantages over the standard approach, and practical examples of its use for various development scenarios.

AI in Agile Product Teams

Aggregated on: 2025-03-03 13:28:02

I have been interested in how artificial intelligence as an emerging technology may shape our work since the advent of ChatGPT; see my various articles on the topic. As you may imagine, when OpenAI’s Deep Research became available to me last week, I had to test-drive it. I asked it to investigate how AI-driven approaches enable agile product teams to gain deeper customer insights and deliver more innovative solutions. The results were enlightening, and I’m excited to share both my experience with this research approach and the key insights that emerged.

Challenges of Using Nginx in a Microservices Architecture

Aggregated on: 2025-03-03 12:13:02

Microservice architecture has become the standard for modern IT projects, enabling the creation of autonomous services with independent lifecycles. In such environments, Nginx is often employed as a load balancer and reverse proxy. However, several challenges can arise when integrating Nginx into a microservices ecosystem. Below, I outline these issues and discuss potential solutions.

Doris Lakehouse Integration: A New Approach to Data Analysis

Aggregated on: 2025-02-28 20:43:00

In the wave of big data, the data volume of enterprises is growing explosively, and the requirements for data processing and analysis are becoming increasingly complex. Traditional databases, data warehouses, and data lakes operate separately, resulting in a significant reduction in data utilization efficiency. At this time, the concept of lakehouse integration emerged, like a timely rain, bringing new possibilities for enterprise data management. Today, let's talk about lakehouse integration based on Doris and see how it solves the problems of data management and enables enterprises to play with big data!

Exploring IoT's Top WebRTC Use Cases

Aggregated on: 2025-02-28 19:28:00

Around the world, 127 new devices are connected to the Internet every second. That translates to 329 million new devices hooked up to the Internet of Things (IoT) every month. The IoT landscape is expanding by the day, and, consequently, novel ways of running an IoT network are also evolving. An emerging area of interest is developing new ways of sharing data between IoT devices, like transmitting a video feed from a surveillance camera to a phone. One well-known way to transmit data is with Web Real-Time Communication (WebRTC), a technology that enables web applications and physical devices to capture and stream media, as well as to exchange data between browsers and devices without requiring an intermediary. For developers creating a primarily audio- or video-based application, WebRTC is one of the best options available.

Exploring Embeddings API With Java and Spring AI

Aggregated on: 2025-02-28 18:43:00

Hi community! This is my second article in a series of introductions to Spring AI. You may find the first one, where I explained how to generate images using Spring AI and OpenAI DALL-E 3 models, here. Today, we will create simple applications using embeddings API and Spring AI.

XAI for Fraud Detection Models

Aggregated on: 2025-02-28 17:28:00

One would question, why should I worry about what is happening behind the scenes as long as my model is able to deliver high-precision results for me? In this article, we dive deep into the aspect of reasoning and try to answer the question above. More importantly, we will understand how it can help us to build greater insights into evolving fraud patterns.

Grafana Loki Fundamentals and Architecture

Aggregated on: 2025-02-28 16:13:00

Grafana Loki is a horizontally scalable, highly available log aggregation system. It is designed for simplicity and cost-efficiency. Created by Grafana Labs in 2018, Loki has rapidly emerged as a compelling alternative to traditional logging systems, particularly for cloud-native and Kubernetes environments. Loki can provide a comprehensive log journey. We can select the right log streams and then filter to focus on the relevant logs. We can then parse structured log data to be formatted for our customized analysis needs. Logs can also be transformed appropriately for presentation, for example, or further pipeline processing.

Key Use Cases of the Event-Driven Ansible Webhook Module

Aggregated on: 2025-02-28 15:28:00

The ansible.eda.webhook plugin is a powerful Event-Driven Ansible (EDA) tool that listens for incoming HTTP webhook requests and triggers automated workflows based on predefined conditions. It’s highly versatile and can be applied across various industries and IT operations. Key Use Cases Automated Incident Response A major use case for ansible.eda.webhook is in automated incident response. When monitoring tools like Prometheus, Nagios, or Datadog spot issues or failures, they can send webhook alerts to Ansible, which then automatically runs playbooks to troubleshoot and fix the problem. This could involve restarting services, scaling up infrastructure, or rolling back recent deployments.

Thread-Safety Pitfalls in XML Processing

Aggregated on: 2025-02-28 13:28:00

Do you think the method children() below is thread-safe? Java children() { NodeList nodes = this.node.getChildNodes(); int length = nodes.getLength(); return Stream.iterate(0, idx -> idx + 1) .limit(length) .map(nodes::item) .map(SafeXml::new); } }" data-lang="text/x-java"> import java.util.stream.Stream; import org.w3c.dom.Node; import org.w3c.dom.NodeList; public final class SafeXml { private final Node node; SafeXml(final Node node) { this.node = node.cloneNode(true); } public Stream<SafeXml> children() { NodeList nodes = this.node.getChildNodes(); int length = nodes.getLength(); return Stream.iterate(0, idx -> idx + 1) .limit(length) .map(nodes::item) .map(SafeXml::new); } } Of course, since I’m asking this question, the answer is no. For those who haven’t had the pleasure of working with XML in Java (yes, it’s still alive), the org.w3c.dom package is not thread-safe. There are no guarantees, even for just reading data from an XML document in a multi-threaded environment.

Loss Functions: The Key to Improving AI Predictions

Aggregated on: 2025-02-28 12:43:00

How Good Is an AI Model at Forecasting? We can put an actual number on it. In machine learning, a loss function tracks the degree of error in the output from an AI model by quantifying the difference or the loss between a predicted value and the actual value. If the model’s predictions are accurate, the difference between these two numbers — the loss — is small. If the predictions are inaccurate, the loss is larger. For example, a colleague built an AI model to forecast how many views his videos would receive on YouTube. The model was fed YouTube titles and forecasted the number of views the video would receive in its first week. When comparing the model’s forecasts to the actual number of views, the predictions were not very accurate. The model predicted that the cold brew video would bomb and that the pour-over guide video would be a hit, but this wasn’t the case. This is a hard problem to solve, and loss functions can help improve the model.

The Tree of DevEx: Branching Out and Growing the Developer Experience

Aggregated on: 2025-02-28 02:28:00

Editor's Note: The following is an infographic written for and published in DZone's 2025 Trend Report, Developer Experience: The Coalescence of Developer Productivity, Process Satisfaction, and Platform Engineering. Engineering teams are recognizing the importance of developer experience (DevEx) and going beyond DevOps tooling to improve workflows, invest in infrastructure, and advocate for developers' needs. By prioritizing things such as internal developer platforms, process automation, platform engineering, and feedback loops, organizations can remove friction from development workflows, and developers gain more control over their systems, teams, and processes.

Modern ETL Architecture: dbt on Snowflake With Airflow

Aggregated on: 2025-02-28 02:28:00

The modern discipline of data engineering considers ETL (extract, transform, load) one of the processes that must be done to manage and transform data effectively. This article explains how to create an ETL pipeline that can scale and uses dbt (Data Build Tool) for transformation, Snowflake as a data warehouse, and Apache Airflow for orchestration. The article will propose the architecture of the pipeline, provide the folder structure, and describe the deployment strategy that will help optimize data flows. In the end, you will have a clear roadmap on how to implement a scalable ETL solution with these powerful tools.

Psychological Safety as a Competitive Edge

Aggregated on: 2025-02-27 22:28:00

Psychological safety isn’t about fluffy “niceness” — it is the foundation of agile teams that innovate, adapt, and deliver. When teams fearlessly debate ideas, admit mistakes, challenge norms, and find ways to make progress, they can outperform most competitors. Yet, many organizations knowingly or unknowingly sabotage psychological safety — a short-sighted and dangerous attitude in a time when knowledge is no longer the moat it used to be. Read on to learn how to keep your competitive edge.

Top Methods to Improve ETL Performance Using SSIS

Aggregated on: 2025-02-27 21:58:00

Extract, transform, and load (ETL) is the backbone of many data warehouses. In the data warehouse world, data is managed through the ETL process, which consists of three steps: extract—pulling or acquiring data from sources, transform—converting data into the required format, and load—pushing data to the destination, typically a data warehouse or data mart. SQL Server Integration Services (SSIS) is an ETL tool widely used for developing and managing enterprise data warehouses. Given that data warehouses handle large volumes of data, performance optimization is a key challenge for architects and DBAs.

How to Set Up Redis Properties Programmatically

Aggregated on: 2025-02-27 21:28:00

Redis is a high-performance NoSQL database that is usually used as an in-memory caching solution. However, it is very useful as the primary datastore solution. In this article, we will see how to set up Redis properties programmatically on the example of a Spring application. In many use cases, objects stored in Redis may be valid only for a certain amount of time.

STRIDE: A Guide to Threat Modeling and Secure Implementation

Aggregated on: 2025-02-27 20:43:00

Threat modeling is often perceived as an intimidating exercise reserved for security experts. However, this perception is misleading. Threat modeling is designed to help envision a system or application from an attacker's perspective. Developers can also adopt this approach to design secure systems from the ground up. This article uses real-world implementation patterns to explore a practical threat model for a cloud monitoring system. What Is Threat Modeling? Shostack (2014) states that threat modeling is "a structured approach to identifying, evaluating, and mitigating risks to system security." Simply put, it requires developers and architects to visualize a system from an attacker’s perspective. Entry points, exit points, and system boundaries are evaluated to understand how they could be compromised. An effective threat model blends architectural precision with detective-like analysis. Threat modeling is not a one-time task but an ongoing process that evolves as systems change and new threats emerge.

Micronaut vs Spring Boot: A Detailed Comparison

Aggregated on: 2025-02-27 17:43:00

Micronaut and Spring Boot are popular frameworks for developing microservices in Java. They offer robust features for REST API, but their approach towards dependency injection, start-up time, and memory usage differ. This article presents a detailed comparison between both frameworks on various parameters such as implementation, performance metrics, and usefulness of each framework. The Micronaut Framework Overview This is a recently developed framework aimed to develop faster microservices and serverless services. Its main feature of compile-time dependency injection results in faster startup times and less memory usage. It has built-in support for cloud environments and serverless deployments and can be integrated with GraalVM. This makes the Micronaut framework suitable for applications where resource utilization is paramount.

Handling Embedded Data in NoSQL With Java

Aggregated on: 2025-02-27 17:28:00

NoSQL databases differ from relational databases by allowing more complex structures without requiring traditional relationships such as one-to-many or one-to-one. Instead, NoSQL databases leverage flexible types, such as arrays or subdocuments, to store related data efficiently within a single document. This flexibility enables developers to design models that suit their application's querying and performance needs. Jakarta NoSQL is a Java framework that simplifies interactions with NoSQL databases, including MongoDB. It provides annotations that determine how data is mapped and stored, allowing developers to control whether embedded objects are grouped or stored in a flat manner.

The Outbox Pattern: Reliable Messaging in Distributed Systems

Aggregated on: 2025-02-27 15:43:00

The Outbox Pattern is a design pattern in distributed systems that is used to ensure reliable event publishing and state consistency between different services or databases. It is primarily used in scenarios like when a system is required to update a database and publish events atomically. In distributed systems, there are often challenges in maintaining consistency during the process of writing to a database and sending messages. For example, consider a payment processing system where you are required to update the transaction status in the database and send an event to another service about the status that got updated (e.g., payment confirmation event). If either the database update fails or the message fails publishing fails, inconsistencies can arise in the current system or another system that failed to consume the event, potentially leading to business losses.

Efficient Multimodal Data Processing: A Technical Deep Dive

Aggregated on: 2025-02-27 14:28:00

Multimodal data processing is the evolving need of the latest data platforms powering applications like recommendation systems, autonomous vehicles, and medical diagnostics. Handling multimodal data spanning text, images, videos, and sensor inputs requires resilient architecture to manage the diversity of formats and scale. In this article, I will walk through a comprehensive end-to-end architecture for efficient multimodal data processing while striking a balance in scalability, latency, and accuracy by leveraging GPU-accelerated pipelines, advanced neural networks, and hybrid storage platforms.

Cloud-Driven Analytics Solution Strategy in Healthcare

Aggregated on: 2025-02-27 13:13:00

This paper examines the revolutionary possibilities of combining Apache Spark for real-time streaming analytics with cloud-based technologies, particularly AWS and Databricks. Using identity and access management (IAM) and encryption techniques, utilizing Databricks' Lakehouse architecture with Unity Catalog improves data governance and security. This approach tackles issues, including traditional data processing systems' latency, fragmented data pipelines, and compliance issues. Scalable, high-performance analytics pipelines are made possible by AWS's reliable infrastructure and Apache Spark's distributed computing. HIPAA and other strict healthcare compliance regulations are met by the Unity Catalog, which guarantees safe, unified data access.

Networking in DevOps: Your Beginner Guide

Aggregated on: 2025-02-27 12:43:00

Hey there! I’m Rocky, the face behind CodeLivly, where I share all things tech, code, and innovation. Today, I want to talk about something super important for anyone diving into the world of DevOps: networking. Networking might sound a bit dry or overly technical at first, but it's actually the backbone of everything DevOps stands for: collaboration, automation, and efficiency. Be it deploying an app in the cloud, automating a pipeline, or troubleshooting an issue in production, knowing how networks operate can make or break your workflow.

Banking Fraud Prevention With DeepSeek AI and AI Explainability

Aggregated on: 2025-02-26 23:12:59

Fraud detection in banking has significantly advanced with artificial intelligence (AI) and machine learning (ML). However, a persistent challenge is the explainability of fraud decisions — how do we justify why a particular transaction was flagged as fraudulent? This article explores how DeepSeek AI enhances fraud prevention through:

Identity and Access Management Solution to Safeguard LLMs

Aggregated on: 2025-02-26 22:12:59

In the era of artificial intelligence, the use of large language models (LLMs) is increasing rapidly. These models offer amazing opportunities but also introduce new privacy and security challenges. One of the essential security measures to address these challenges involves securing access to the LLMs so that only authorized individuals have access to data and permissions to perform any action. This can be achieved using identity and access management (IAM). Identity and access management act as a security guard for critical data and systems. This approach operates just like a physical security guard who controls who can enter a building and who has access to security camera footage. When entering a building, security guards can ask for your identity, where you live, etc. They can also keep an eye on your activity around or inside the building if they see something suspicious. Similarly, identity and access management ensure that only authorized individuals can enter and access large language models. IAM also keeps a log of user activities to identify suspicious behavior.

How to Scale Elasticsearch to Solve Your Scalability Issues

Aggregated on: 2025-02-26 20:42:59

With the evolution of modern applications serving increasing needs for real-time data processing and retrieval, scalability does, too. One such open-source, distributed search and analytics engine is Elasticsearch, which is very efficient at handling data in large sets and high-velocity queries. However, the process for effectively scaling Elasticsearch can be nuanced, since one needs a proper understanding of the architecture behind it and of performance tradeoffs. While Elasticsearch’s distributed nature lets it scale horizontally, that also introduces more complexities in how data is spread and queries served. One of the theoretical challenges associated with scaling Elasticsearch is its inherently distributed nature. In most practical scenarios, reads on a standalone node will always outperform reads in a sharded cluster. This is because, in a sharded cluster, data ownership is spread across multiple nodes. That means every query may have to shoot multiple requests to different nodes, aggregate the results back at the coordinating node, and return the result. This extra network overhead will easily result in increased latency compared to a single-node architecture where data access is straightforward.