News Aggregator

Deduplication of Videos Using Fingerprints, CLIP Embeddings

Aggregated on: 2025-02-21 18:12:44

Video deduplication is a crucial process for managing large-scale video inventory, where duplicates consume storage, increase processing costs, and affect data quality negatively. This article explores a robust architecture for deduplication using video segmentation, frame embedding extraction, and clustering techniques. It also highlights key methodologies like video hashing, CLIP embeddings, and temporal alignment for effective deduplication.

Microservices vs Monoliths: Picking the Right Architecture

Aggregated on: 2025-02-21 17:12:44

You’re building a new application, and suddenly, you’re stuck in an endless debate: microservices or monolith? It’s the software equivalent of choosing between a Swiss Army knife and a specialized toolkit. Both get the job done, but the wrong choice could mean wasted time, budget, or technical debt. Having guided teams through both architectures for over a decade, here’s my no-BS take on the tradeoffs — and how to avoid regrets. Performance: It’s Not Just About Speed Let’s cut through the hype. Yes, microservices can scale effortlessly — in theory. Imagine an e-commerce app where the payment service autoscales during Black Friday traffic while the product catalog stays idle. That’s the dream. But here’s the kicker: those independently deployed services chat constantly over APIs. Every interaction introduces latency, and suddenly, your “scalable” system is bottlenecked by network calls. I’ve seen teams waste months optimizing service mesh configurations just to shave off milliseconds.

Terraform State File: Key Challenges and Solutions

Aggregated on: 2025-02-21 16:42:44

Introduction of Terraform State File The Terraform state file serves as a crucial bridge between the declarative configuration in the Terraform code and the resources deployed in the infrastructure. It maintains a detailed record of all the resources managed by Terraform, including their attributes, dependencies, and metadata. This information enables Terraform to perform intelligent operations such as incremental updates and resource tracking across multiple executions. When Terraform runs, it compares the desired state defined in the configuration files to the current state recorded in the state file. This comparison allows Terraform to determine which changes must be applied to align the infrastructure with the desired configuration.

Step-by-Step Reasoning Can Fix Madman Logic in Vision AI

Aggregated on: 2025-02-21 15:42:44

Vision AI models have a flaw. When shown a medical scan, they might correctly diagnose a condition while citing anatomically impossible reasons. Or they might solve a geometry problem with the right answer but skip essential theorems and rely on made-up ones instead. These models reach correct conclusions through reasoning that makes no sense. The Gap in Visual Reasoning Models This hints at a deeper problem. Current models don’t really think through visual problems — they pattern-match their way to answers. The LlamaV-o1 team discovered this by doing something simple: they forced their model to show its work. The results revealed that most visual reasoning errors don’t come from failing to see what’s in an image. They come from skipping key logical steps between seeing and concluding.

Building a Simple RAG Application With Java and Quarkus

Aggregated on: 2025-02-21 14:42:44

Introduction to RAG and Quarkus Retrieval-augmented generation (RAG) is a technique that enhances AI-generated responses by retrieving relevant information from a knowledge source. In this tutorial, we’ll build a simple RAG-powered application using Java and Quarkus (a Kubernetes-native Java framework). Perfect for Java beginners! Why Quarkus? Quarkus provides multiple LangChain4j extensions to simplify AI application development, especially RAG implementation by providing an Easy RAG module for building end-to-end RAG pipelines. Easy RAG acts as a bridge, connecting the retrieval components (like your document source) with the LLM interaction within the LangChain4j framework.

Why Platform Engineering Is Essential to DevEx: Understand the Relationship Between Platform Engineering and the Developer Experience

Aggregated on: 2025-02-21 12:27:43

Editor's Note: The following is an article written for and published in DZone's 2025 Trend Report, Developer Experience: The Coalescence of Developer Productivity, Process Satisfaction, and Platform Engineering. Software engineering continues to be an exciting journey, where use cases not only feed creativity but also allow the underlying intellectual property to thrive. The biggest challenge is to make sure engineers maintain a focus on what allows their solutions to be differentiators in the market. That's where concepts like developer experience (DevEx) and platform engineering come into play.

Solving Interface Challenges With the BFF Pattern

Aggregated on: 2025-02-20 23:57:43

Modern software applications often need to support multiple frontend UI like Web, Android, IOS, TV, and VR, each with unique requirements. Traditionally, developers have dependent on a single backend to serve all clients. However, the complexity of serving different frontends needs using a monolithic backend can result in performance bottlenecks, complicated APIs, and unnecessary data interactions. The Backend for Frontend (BFF) architecture helps answer these challenges by creating a dedicated back-end service for each frontend type. Each BFF is dedicated to a specific UI kind, improving performance, UX, and overall system stability and maintainability.

Bitwise Operators in Go

Aggregated on: 2025-02-20 22:57:43

In low-level programming, it is common to work at the bit level. This was true in earlier days of computing and is even relevant today. Most popular languages keep provisions for bit-level operations, not only as a legacy but also as a frequently used feature in their arsenal. Direct bit-level operations are used in cryptography, system-level programming, image processing, etc. In this Golang programming tutorial, we will go into the details of bitwise operators and how to work with them in Go. Golang Bitwise Operators Go provides the following bitwise operators:

Implementing SOLID Principles in Android Development

Aggregated on: 2025-02-20 21:57:43

Writing software is an act of creation, and Android development is no exception. It’s about more than just making something work. It’s about designing applications that can grow, adapt, and remain manageable over time. As an Android developer who has faced countless architectural challenges, I’ve discovered that adhering to the SOLID principles can transform even the most tangled codebases into clean systems. These are not abstract principles, but result-oriented and reproducible ways to write robust, scalable, and maintainable code.

AI Agents: Future of Automation or Overhyped Buzzword?

Aggregated on: 2025-02-20 21:12:43

In a world obsessed with artificial intelligence, there's a new player in town — AI agents. But before you roll your eyes and think, "Great, another tech term to pretend I understand at meetings," let’s break it down. What the Heck Are AI Agents? Imagine you have a really smart assistant — not just one that tells you the weather or suggests a new Netflix show — but one that thinks, plans, and acts without you having to spell everything out. That’s what AI agents are all about. Unlike simple chatbots or automation scripts that follow rigid, predefined paths, AI agents are designed to be autonomous. They don’t just react; they perceive, decide, and take action based on goals.

Kata Containers: From Kubernetes Pods to Secure VMs

Aggregated on: 2025-02-20 19:42:43

Introduction to Kata Containers Kata Containers is an open-source project designed to deliver a secure container runtime environment by utilizing the virtualization layer provided by the server instance. Unlike traditional containers, Kata containers run within lightweight virtual machines (VMs) created using virtualization capabilities. This approach ensures robust isolation between the host operating system (OS) and the containers, making them a powerful choice for scenarios demanding heightened security. The Core Difference: Kata vs. Conventional Containers Conventional containers are software packages that share the host OS kernel for isolated execution. They achieve isolation using Linux technologies such as network namespaces and c-groups.

Convert Stored Procedures and Functions From SQL Server to PostgreSQL

Aggregated on: 2025-02-20 18:42:43

Stored procedures and functions are implementing the business logic of the database. When migrating the SQL Server database to PostgreSQL, you will need to convert stored procedures and functions properly, paying attention to parameter handling, rowset retrieval, and other specific syntax constructions. SQL Server uses a dialect of SQL called Transact-SQL (or T-SQL) for stored procedures and functions, while PostgreSQL uses Procedural Language/PostgreSQL (or PL/pgSQL) for the same. These languages have significantly different syntax and capabilities, so stored procedures and functions must be carefully analyzed and converted.

Scaling Image Deduplication: Finding Needles in a Haystack

Aggregated on: 2025-02-20 17:27:43

In the current AI generation, where organizations deal with a vast inventory of images, identifying duplicates can be a daunting task. Distributed deduplication at scale is essential for optimizing storage, reducing redundancy, and maintaining data integrity. This article provides insight into the architectural design and practical implementation for deduplicating 100 million images efficiently using state-of-the-art tools and approaches. Challenges in Image Deduplication Scale Processing millions or even billions of images demands:

How Open Source Can Elevate Your Career as a Software Engineer

Aggregated on: 2025-02-20 16:57:43

Advancing in a software engineering career can be a daunting challenge. Many engineers find themselves stuck, unsure of what steps to take to move from a mid-level role to senior positions such as staff, principal, or distinguished engineer. While technical knowledge is essential, the real differentiators are the skills that allow engineers to build scalable, maintainable, and collaborative software solutions. Open source provides an ideal platform for mastering these crucial skills. It forces engineers to write clean, maintainable code, work within distributed teams, document effectively, and apply industry best practices that lead to software longevity. Some of the most successful open-source projects have been maintained for decades, demonstrating principles that can be used in any professional setting.

An Introduction to Object Mutation in JavaScript

Aggregated on: 2025-02-20 15:57:43

In programming, object mutation implies that an object's state or data is mutated after creation. In other words, the operation that changes the attributes of an object in JavaScript is known as object mutation. Object mutation alters an object's values directly, making it challenging, particularly in applications where multiple operations may try to read from or write to an object simultaneously. This article presents a discussion on object mutation in JavaScript with relevant code examples wherever necessary.

How to Enable Sybil Resistance in Your dApps on Avalanche

Aggregated on: 2025-02-19 22:42:43

If there’s one thing Web3 devs can agree on, it’s that Sybils suck. Bots and fake accounts are ruining airdrops, gaming economies, DAOs, and DeFi incentives. Everyone’s trying to fight them, but the solutions are either too centralized and non-private (KYC) or too easy to game (staking-based anti-Sybil tricks). That’s where Biomapper comes in handy — an on-chain tool that links one EVM account to one human for verifying that users are real, unique humans without KYC or exposing personal data.

How to Use Terraform Import Block for Importing Resources

Aggregated on: 2025-02-19 20:12:43

With Terraform 1.5 and later, you can use the import block to manage the import of resources directly in your configuration. This feature simplifies the process of importing existing infrastructure into Terraform state, eliminating the need for a separate CLI terraform import command. In this article, we explain the import block and how to use it to import different resources.

Yes! I Can Finally Run My .NET Application on Heroku!

Aggregated on: 2025-02-19 19:27:43

Heroku now officially supports .NET! .NET developers now have access to the officially supported buildpack for .NET, which means you can now deploy your .NET apps onto Heroku with just one command: git push heroku main.

Data Pattern Automation With AI and Machine Learning

Aggregated on: 2025-02-19 18:27:43

In the age of information that we live in today, every company faces challenges using data to its full potential. One technique for removing those hurdles is pattern recognition, a method by which automated processes are applied. With the amazing progress of AI, new methods of identifying relationships that were previously unobtainable, as well as identifying trends and establishing data-driven strategies, have emerged. In this article, we describe the methods and tools necessary for automated pattern recognition and how, combined with AI, they can help unlock business process automation and improve the data management workflow within companies.

The Impact of Edge Computing on Mobile App Development

Aggregated on: 2025-02-19 17:42:43

Edge computing has revolutionized how people use mobile apps and how those offerings function. It has also increased opportunities for application development professionals. How does edge computing support their work and broaden their ability to meet consumers’ needs? 1. Enhanced Privacy Since edge computing enables data processing closer to its source, user information travels shorter distances and may not leave a person’s device. Those advantages significantly reduce the chances of malicious parties compromising it. Using edge computing to strengthen cybersecurity is an excellent way to build people’s trust and position app developers at the forefront of proactive measures to protect user details.

Build Scalable GenAI Applications in the Cloud: From Data Preparation to Deployment

Aggregated on: 2025-02-19 16:12:43

The cloud has proven to be a main enabler for large AI deployments because it provides AI-native APIs for rapid prototyping, elastic computing, and storage to address scaling problems. This article covers how to build and scale GenAI applications in the cloud. The Importance of the Cloud in GenAI The cloud is critical for contemporary GenAI applications because it can accommodate vast processing power, data storage, and distributed processes necessary for AI models. Traditional deployments often need more flexibility and performance to adapt to changing business requirements.

Observability and DevTool Platforms for AI Agents

Aggregated on: 2025-02-19 15:12:43

In the past years, AI agents have been everywhere across industries, autonomously and independently operating over extended periods using various tools to accomplish complex tasks. With the advent of numerous frameworks for building these AI agents, observability and DevTool platforms for AI agents have become essential in artificial intelligence. These platforms provide developers with powerful tools to monitor, debug, and optimize AI agents, ensuring their reliability, efficiency, and scalability. Let's explore the key features of these platforms and examine some code examples to illustrate their practical applications.

Agentic Workflows for Unlocking User Engagement Insights

Aggregated on: 2025-02-19 14:27:43

What Are Agentic Workflows? Agentic workflows are systems or processes where we define the goal and the role and provide some context around both of them, and the AI agents determine the steps to fulfill the goal. They differ slightly from AI automation, where we define the goal and role and provide the steps to accomplish the goal. Advantages of Agentic Workflows There are a lot of advantages to using agentic workflows. Here are a few that are showcased in our article today.

Streamline Microservices Development With Dapr and Amazon EKS

Aggregated on: 2025-02-19 13:42:43

Microservices and containers are revolutionizing how modern applications are built, deployed, and managed in the cloud. However, developing and operating microservices can introduce significant complexity, often requiring developers to spend valuable time on cross-cutting concerns like service discovery, state management, and observability. Dapr, or Distributed Application Runtime, is an open-source runtime for building microservices on cloud and edge environments. It provides platform-agnostic building blocks like service discovery, state management, pub/sub messaging, and observability out of the box. Dapr moved to the graduated maturity level of CNCF (Cloud Native Computing Foundation) and is currently used by many enterprises.

[Comic] The Recursive Prerequisite

Aggregated on: 2025-02-19 12:27:43

The New Developer Interview Tactic Interviewing for a new job in software development? Be aware of the recent uptick in interview questions about Quicksort. Hiring managers and recruiters really are taking "divide-and-conquer" to the next level.

Building Intelligent Microservices With Go and AWS AI Services

Aggregated on: 2025-02-18 22:42:42

Coupling Go's lightweight programming capabilities with AWS' robust AI services allows developers to build performant, scalable, and intelligent microservices devoted to diverse business needs. This blog explains how Go, and AWS AI services can be combined to create intelligent microservices, discusses the benefits of this approach, and provides a step-by-step guide to getting started. Why Use Go for Microservices? Golang, or Go, is a statically typed, compiled programming language that speaks Google. It aims to meet some requirements regarding simplicity, performance, and scalability. Combined, they make it an excellent choice for building microservices:

Data Privacy and Governance in Real-Time Data Streaming

Aggregated on: 2025-02-18 21:57:42

Real-time data streaming is changing the way organizations handle information. Whether it’s IoT devices sending sensor updates, retail platforms tracking customer activity, or financial institutions monitoring transactions for fraud, processing data “as it happens” gives you a major edge. When done well, real-time data streaming fuels faster decision-making, more personalized services, and even proactive threat detection. Despite these advantages, privacy and governance often don’t get the attention they deserve. Many streaming analytics initiatives focus heavily on throughput and latency — valid concerns — but that can mean overlooking critical items like encryption, access controls, and compliance requirements. This article looks at the main pitfalls of handling streaming data in a regulated environment, followed by proven strategies for building and maintaining secure, compliant pipelines.

Dive Into Tokenization, Attention, and Key-Value Caching

Aggregated on: 2025-02-18 20:42:42

The Rise of LLMs and the Need for Efficiency In recent years, large language models (LLMs) such as GPT, Llama, and Mistral have impacted natural language understanding and generation. However, a significant challenge in deploying these models lies in optimizing their performance, particularly for tasks involving long text generation. One powerful technique to address this challenge is key-value caching (KV cache). In this article, we will delve into how KV caching works, its role within the attention mechanism, and how it enhances efficiency in LLMs.

Creating an Agentic RAG for Text-to-SQL Applications

Aggregated on: 2025-02-18 19:57:42

The blend of retrieval-augmented generation (RAG) and generative AI models has brought changes to natural language processing by improving the responses to queries. In the realm of Agentic RAG, this conventional method of relying on a monolithic model for tasks has been enhanced by introducing modularity and autonomy. By breaking down the problem-solving process into tools integrated within an agent, Agentic RAG provides benefits like accuracy, transparency, scalability, and debugging capabilities. The Vision Behind Agentic RAG for Text-to-SQL Traditional RAG systems often retrieve relevant documents and rely on a single monolithic model to generate responses. Although this is an effective method in some cases, when it comes to structural outputs like the case of generating SQL, this approach may not be the most effective. This is where we can leverage the power of the Agentic RAG framework, where we:

Implement Amazon S3 Cross-Region Replication With Terraform

Aggregated on: 2025-02-18 18:42:42

With the information technology element finding its roots in every financial organization and across all industries, strong storage capacity forms the backbone for availability, durability, and scalability. Among these, Amazon S3 is one of the most popular services to meet these needs. As enterprises expand geographically, the need for data replication between locations starts to be felt significantly. Hence, the need arose to develop Cross-Region Replication in Amazon S3, where data replication between one bucket sourced from one AWS region to another bucket in a different AWS region is allowed. The article will describe how to configure Cross-Region Replication in Amazon S3 using Terraform, an IaC software. It gives a general overview of how to set up SLAs, discusses why one would implement cross-region replication, and shows how to get a proof of concept running.

Container Checkpointing in Kubernetes With a Custom API

Aggregated on: 2025-02-18 17:27:42

Problem Statement Challenge Organizations running containerized applications in Kubernetes often need to capture and preserve the state of running containers for: Disaster recovery Application migration Debug/troubleshooting State preservation Environment reproduction However, there's no straightforward, automated way to:

The Delegated Chain of Thought Architecture

Aggregated on: 2025-02-18 16:12:42

This article introduces the Delegated Chain of Thought (D-CoT) Architecture, a novel framework for large language models (LLMs) that decouples reasoning from execution.The architecture centralises reasoning in a "modulith" model while delegating execution tasks to smaller, specialised models. We are collaborating with AI engineers to create tools that software engineers can easily use. Merging these two disciplines is essential to mastering tools and integrating them into our information system effectively. This approach draws heavily on software architecture analogies and focuses on integrating advanced LLM techniques, such as Chain-of-Thought (CoT) prompting, ReAct, Toolformer, and modular AI design principles.

Generate Unit Tests With AI Using Ollama and Spring Boot

Aggregated on: 2025-02-18 15:27:42

There are scenarios where we would not want to use commercial large language models (LLMs) because the queries and data would go into the public domain. There are ways to run open-source LLMs locally. This article explores the option of running Ollama locally interfaced with the Sprint boot application using the SpringAI package. We will create an API endpoint that will generate unit test cases for the Java code that has been passed as part of the prompt using AI with the help of Ollama LLM.

Multimodal RAG With Colpali, Milvus, and VLMs

Aggregated on: 2025-02-18 14:12:42

In this post, we will see how to do multimodal RAG with ColPali, Milvus, and a visual language model (Gemini/GPT-4o). We will build an application to upload a PDF and then do Q&A queries on it. Q&A can be done on both text and visual elements of the PDF. We will not extract text from the PDF; instead, we will treat it as an image and use ColPali to get embeddings for the PDF pages. These embeddings will be indexed to Milvus, and then we will use a VLM to do Q&A queries on the PDF pages.

A Step-by-Step Guide to Enterprise Application Development

Aggregated on: 2025-02-18 13:27:42

Having spent more late nights untangling enterprise spaghetti code than I care to admit, I can confidently say developing enterprise applications is not for the faint of heart. While hobby apps crash because someone forgot a semicolon, enterprise code glitches could mean accidentally buying every employee a yacht. We’re talking about software that keeps multinational supply chains from imploding because someone in accounting fat-fingered a CSV export.

Search: From Basic Document Retrieval to Answer Generation

Aggregated on: 2025-02-18 12:12:42

In the digital age, the ability to find relevant information quickly and accurately has become increasingly critical. From simple web searches to complex enterprise knowledge management systems, search technology has evolved dramatically to meet growing demands. This article explores the journey from index-based basic search engines to retrieval-based generation, examining how modern techniques are revolutionizing information access. The Foundation: Traditional Search Systems Traditional search systems were built on relatively simple principles: matching keywords and ranking results based on relevance, user signals, frequency, positioning, and many more. While effective for basic queries, these systems faced significant limitations. They struggled with understanding context, handling complex multi-part queries, resolving indirect references, performing nuanced reasoning, and providing user-specific personalization. These limitations became particularly apparent in enterprise settings, where information retrieval needs to be both precise and comprehensive.

Understanding Infrastructure as Code at Scale

Aggregated on: 2025-02-17 22:57:42

Infrastructural as Code is an IT approach where the process involved in infrastructure configuration, deployment, and monitoring are checked through coded expressions. IaC also increases the deployment rate and is significant when applied with cloud resources. "IaC at scale" means using this approach for massive cloud infrastructures, for thousands of resources in single or multiple environments. That is why adopting IaC to scale up its use brings into focus the aspects of agility, efficiency, and consistency in the infrastructure. However, it also creates problems regarding the organization of the dependencies and the coordination of the configurations that are to be in place across several resources.

The Slides of Hands-On Agile 2025

Aggregated on: 2025-02-17 21:12:42

If you weren’t at the virtual Hands-on Agile 2025 conference earlier this month, you missed an incredible opportunity to explore the shift from concept-based to context-based agility with nearly 800 fellow agilists. But don’t worry — I’m here to share some of the key takeaways and insights! Check out the slides from the live-stream speakers below; I will keep you posted on the availability of the recordings.

Integrating Apex With Lightning Web Components

Aggregated on: 2025-02-17 20:12:42

Salesforce’s Lightning Web Component (LWC) is a modern UI framework that developers use to create custom pages and functionalities on the Salesforce Lightning platform. While LWC allows developers to build powerful and interactive user interfaces, it often requires back-end integration to fetch or update data from Salesforce. This back-end support is provided by Apex, Salesforce's server-side programming language. In this article, we will explore three common methods for integrating LWC with Apex:

Scaling ML Models Efficiently With Shared Neural Networks

Aggregated on: 2025-02-17 19:27:41

As machine learning models grow in complexity and size, organizations face increasing challenges in deploying and scaling these models efficiently. A particularly pressing challenge is balancing hardware memory constraints with the expanding size of ML models while maintaining high performance and cost-effectiveness. This article explores an innovative architectural solution that addresses these challenges through a hybrid approach combining shared neural encoders with specialized prediction heads. The Challenge: Memory Constraints in ML Model Deployment Traditional machine learning deployments often require loading complete models into memory for each distinct use case or customer application. For example, in natural language understanding (NLU) applications using BERT-based models, each model typically consumes around 210-450 MB of memory. When serving thousands of customers, this leads to significant scaling challenges. A typical server with 72 GB of CPU memory can only support approximately 100 models simultaneously, creating a hard ceiling on service capacity.

Creating a Web Project: Key Steps to Identify Issues

Aggregated on: 2025-02-17 18:12:41

When developing a product, issues inevitably arise that can impact both its performance and stability. Slow system response times, error rate increases, bugs, and failed updates can all damage the reputation and efficiency of your project. However, before addressing these problems, it is essential to gather and analyze statistics on their occurrence. This data will help you make informed decisions regarding refactoring, optimization, and error-fixing strategies.

Have LLMs Solved the Search Problem?

Aggregated on: 2025-02-17 17:27:41

The advent of large language models (LLMs) has catalyzed a paradigm shift in information retrieval and human-computer interaction. These models, trained on vast corpora of text and optimized for predictive linguistic tasks, have demonstrated substantial efficacy in responding to queries, summarizing textual content, and generating contextually relevant information. However, despite their impressive generative capabilities, LLMs do not inherently resolve the complexities of search and retrieval in structured and unstructured data landscapes. Instead, they require augmentation with advanced techniques such as semantic chunking, vector embeddings, and context-aware personalization to optimize precision and recall.

Apache Flink: Full Checkpoint vs Incremental Checkpoint

Aggregated on: 2025-02-17 16:12:41

Apache Flink is a real-time data stream processing engine. Most of the stream processing applications are ‘stateful.’ This means the state is stored and used for further processing. In Apache Flink, the state is managed through a configured state backend. Flink supports two-state backends in production. One is the HashMapStateBackend, and the other one is the EmbeddedRocksDBStateBackend. To prevent data loss and achieve fault tolerance, Flink can persist snapshots of the state to a durable storage. Flink can be configured to snapshot either the entire state into a durable location or the delta since the last snapshot. The former is called full checkpoint, and the latter is known as the incremental checkpoint.

Page Transactions and Page Object Model

Aggregated on: 2025-02-17 15:27:41

Recently, I wrote an article on Page Transactions as a new approach to test automation, focusing on simplicity, readability, and flexibility. Now, I present a structured comparison of Page Transactions (PT) and Page Object Model (POM), explaining the pros and cons of each pattern. Finally, I will give some tips on migrating from POM to PT in simple steps. To those who are not familiar with POM, in a nutshell, it is a design pattern used in testing automation where the objects on a UI page are represented as methods in a class and where each class represents the UI page itself.

Build a Data Analytics Platform With Flask, SQL, and Redis

Aggregated on: 2025-02-17 14:12:41

In this article, I’ll walk through the development of a Flask-based web application that interacts with an SQL Server database to analyze population data. The application allows users to query population ranges, fetch counties by state, and retrieve states within specific population ranges. I shall also discuss how to integrate Redis for caching query results to improve performance. Why Flask, SQL Server, and Redis? Flask is a lightweight and flexible Python web framework that is perfect for building small to medium-sized web applications. It provides the necessary tools to create RESTful APIs, render dynamic HTML templates, and interact with databases. On the other hand, SQL Server is a robust relational database management system (RDBMS) that is widely used in enterprise applications. Combining Flask with SQL Server allows us to build a powerful application for data analysis and visualization.

From Data to Decisions: Visualizing SAP Insights With Python

Aggregated on: 2025-02-17 13:27:41

SAP has always enjoyed the position of being the most trusted enterprise resource planning software where it brings in all the departments in an organization like sales, inventory, production, quality, human resources, and more. Data that resides in SAP ERP data is the bedrock for all decision-making as it provides a single source of truth to the entire organization. Visualizing this data can uncover market trends and patterns and provide actionable insights to the leadership team. While SAP itself has business objects as its flagship visualization tool, as developers, we are going to explore how Python, with its robust ecosystem of libraries, can be as powerful and can be consumed freely by any developer.

Why Cloud Matters: Building Global, Scalable Microservices

Aggregated on: 2025-02-17 12:27:41

Software engineers must develop applications that are not only functional but also scalable, resilient, and globally distributed. This is where cloud computing plays a crucial role. Cloud platforms provide the foundation to build scalable microservices, ensuring high availability, efficient resource management, and seamless integration with modern technologies. The Importance of the Cloud in Your Software Engineering Career Cloud computing is no longer optional but a necessity for modern software engineers. Here’s why:

Reactive Programming in React With RxJS

Aggregated on: 2025-02-14 22:57:40

ReactJS has become a go-to library for building dynamic and responsive user interfaces. However, as applications grow, managing asynchronous data streams becomes more challenging. Enter RxJS, a powerful library for reactive programming using observables. RxJS operators simplify handling complex asynchronous data flows, making your React components more manageable and efficient. In this article, we'll explore RxJS operators within the context of ReactJS. We'll walk through step-by-step examples, demonstrating how to integrate RxJS into your React applications. By the end of this guide, you'll have a solid understanding of RxJS operators and how they can enhance your ReactJS projects.

Redis as a Primary Database for Complex Applications

Aggregated on: 2025-02-14 22:12:40

First, we will see what Redis is and its usage, as well as why it is suitable for modern complex microservice applications. We will talk about how Redis supports storing multiple data formats for different purposes through its modules. Next, we will see how Redis, as an in-memory database, can persist data and recover from data loss. We’ll also talk about how Redis optimizes memory storage costs using Redis on Flash. Then, we will see very interesting use cases of scaling Redis and replicating it across multiple geographic regions. Finally, since one of the most popular platforms for running micro-services is Kubernetes, and since running stateful applications in Kubernetes is a bit challenging, we will see how you can easily run Redis on Kubernetes.

Optimizing Database Performance in Middleware Applications

Aggregated on: 2025-02-14 19:27:40

In the realm of modern software architecture, middleware plays a pivotal role in connecting various components of distributed systems. One of the most significant challenges faced by middleware applications is optimizing database interactions. This is crucial because middleware often serves as the bridge between client applications and backend databases, handling a high volume of requests and data processing tasks. Efficient database operations in middleware can dramatically improve overall system performance, reduce latency, and enhance user experience. This blog post explores various techniques to optimize database performance, specifically in the context of middleware applications.