News Aggregator

Fighting Climate Change One Line of Code at a Time

Aggregated on: 2024-02-06 13:02:04

As climate change accelerates, tech leaders are responding to rising expectations around corporate sustainability commitments. However, quantifying and optimizing the environmental impacts of complex IT ecosystems has remained an elusive challenge. This is now changing with the emergence of emissions monitoring solutions purpose-built to translate raw telemetry data from Dynatrace and other observability platforms into detailed carbon footprint analysis.

Best Practices and Phases of Data Migration From Legacy SAP to SAP

Aggregated on: 2024-02-06 12:47:04

When an organization decides to implement SAP S/4HANA while implementing S/4HANA, the first step is to identify whether it will be a system conversion, new implementation, or selective data transition. Usually, when implementing S/4, it would be a new implementation. Once the implementation type is identified, we have to make sure that you have a full data migration plan in place as part of the project. Data migration is a major part of a successful SAP migration project. If you don’t start working on data extraction, cleaning, and conversion early and continue that work throughout the project, it can sneak up on you and become a last-minute crisis.

Mastering Complex Stored Procedures in SQL Server: A Practical Guide

Aggregated on: 2024-02-06 12:47:04

In the realm of database management, SQL Server stands out for its robustness, security, and efficiency in handling data. One of the most powerful features of SQL Server is its ability to execute stored procedures, which are SQL scripts saved in the database that can be reused and executed to perform complex operations. This article delves into the intricacies of writing complex stored procedure logic in SQL Server, offering insights and a practical example to enhance your database management skills. Understanding Stored Procedures Stored procedures are essential for encapsulating logic, promoting code reuse, and improving performance. They allow you to execute multiple SQL statements as a single transaction, reducing server load and network traffic. Moreover, stored procedures can be parameterized, thus offering flexibility and security against SQL injection attacks.

Top 5 Reasons Why Your Redis Instance Might Fail

Aggregated on: 2024-02-05 23:47:04

If you’ve implemented a cache, message broker, or any other data use case that prioritizes speed, chances are you’ve used Redis. Redis has been the most popular in-memory data store for the past decade and for good reason; it’s built to handle these types of use cases. However, if you are operating a Redis instance, you should be aware of the most common points of failure, most of which are a result of its single-threaded design. If your Redis instance completely fails, or just becomes temporarily unavailable, data loss is likely to occur, as new data can’t be written during these periods. If you're using Redis as a cache, the result will be poor user performance and potentially a temporary outage. However, if you’re using Redis as a primary datastore, then you could suffer partial data loss. Even worse, you could end up losing your entire dataset if the Redis issue affects its ability to take proper snapshots, or if the snapshots get corrupted.

The Trusted Liquid Workforce

Aggregated on: 2024-02-05 22:47:04

Remote Developers Are Part of the Liquid Workforce The concept of a liquid workforce (see Forbes, Banco Santander, etc.) is mostly about this: A part of the workforce is not permanent and can be adapted to dynamic market conditions. In short, in a liquid workforce, a proportion of the staff is made of freelancers, contractors, and other non-permanent employees. Today, it is reported that about 20% of an IT workforce, including software developers, is liquid in a significant part of the Fortune 500 companies. Figure: It is reported that about 20% of an IT workforce is liquid in a significant part of the Fortune 500 companies. Actually, working as a freelancer has been a common practice in the media and entertainment industry for a long time. Many other industries are catching up to this model today. From the gig economy to the increasing sentiment stemming from Gen-Y and Gen-Z’ers that employment should be flexible, multiple catalysts are contributing to the idea that the liquid approach is likely to continue eroding the classic workforce.

Requirements, Code, and Tests: How Venn Diagrams Can Explain It All

Aggregated on: 2024-02-05 20:02:03

In software development, requirements, code, and tests may form the backbone of our activities. Requirements, specifications, user stories, and the like are essentially a way to depict what we want to develop. The implemented code represents what we’ve actually developed. Tests are a measure of how confident we are that we’ve built the right features in the right way. These elements, intertwined yet distinct, represent the essential building blocks that drive the creation of robust and reliable software systems. However, navigating the relationships between requirements, code implementation, and testing can often prove challenging, with complexities arising from varying perspectives, evolving priorities, and resource constraints. In this article, we delve into the symbiotic relationship between requirements, code, and tests, exploring how Venn diagrams serve as a powerful visual aid to showcase their interconnectedness. From missed requirements to untested code, we uncover many scenarios that can arise throughout the SDLC. We also highlight questions that may arise and how Venn diagrams offer clarity and insight into these dynamics.

Building and Deploying a Chatbot With Google Cloud Run and Dialogflow

Aggregated on: 2024-02-05 19:02:03

In this tutorial, we will learn how to build and deploy a conversational chatbot using Google Cloud Run and Dialogflow. This chatbot will provide responses to user queries on a specific topic, such as weather information, customer support, or any other domain you choose. We will cover the steps from creating the Dialogflow agent to deploying the webhook service on Google Cloud Run. Prerequisites A Google Cloud Platform (GCP) account. Basic knowledge of Python programming. Familiarity with Google Cloud Console. Step 1: Set Up Dialogflow Agent Create a Dialogflow Agent: Log into the Dialogflow Console (Google Dialogflow). Click on "Create Agent" and fill in the agent details. Select the Google Cloud Project you want to associate with this agent. Define Intents: Intents classify the user's intentions. For each intent, specify examples of user phrases and the responses you want Dialogflow to provide. For example, for a weather chatbot, you might create an intent named "WeatherInquiry" with user phrases like "What's the weather like in Dallas?" and set up appropriate responses. Step 2: Develop the Webhook Service The webhook service processes requests from Dialogflow and returns dynamic responses. We'll use Flask, a lightweight WSGI web application framework in Python, to create this service.

Unlocking the Power Duo: Kafka and ClickHouse for Lightning-Fast Data Processing

Aggregated on: 2024-02-05 18:02:03

Imagine the challenge of rapidly aggregating and processing large volumes of data from multiple point-of-sale (POS) systems for real-time analysis. In such scenarios, where speed is critical, the combination of Kafka and ClickHouse emerges as a formidable solution. Kafka excels in handling high-throughput data streams, while ClickHouse distinguishes itself with its lightning-fast data processing capabilities. Together, they form a powerful duo, enabling the construction of top-level analytical dashboards that provide timely and comprehensive insights. This article explores how Kafka and ClickHouse can be integrated to transform vast data streams into valuable, real-time analytics. This diagram depicts the initial, straightforward approach: data flows directly from POS systems to ClickHouse for storage and analysis. While seemingly effective, this somewhat naive solution may not scale well or handle the complexities of real-time processing demands, setting the stage for a more robust solution involving Kafka.

Demystifying Dynamic Programming: From Fibonacci to Load Balancing and Real-World Applications

Aggregated on: 2024-02-05 17:32:03

Dynamic Programming (DP) is a technique used in computer science and mathematics to solve problems by breaking them down into smaller overlapping subproblems. It stores the solutions to these subproblems in a table or cache, avoiding redundant computations and significantly improving the efficiency of algorithms. Dynamic Programming follows the principle of optimality and is particularly useful for optimization problems where the goal is to find the best or optimal solution among a set of feasible solutions. You may ask, I have been relying on recursion for such scenarios. What’s different about Dynamic Programming?

Developing Intelligent and Relevant Software Applications Through the Utilization of AI and ML Technologies

Aggregated on: 2024-02-05 17:32:03

The focal point of this article centers on harnessing the capabilities of Artificial Intelligence (AI) and Machine Learning (ML) to enhance the relevance and value of software applications. The key focus of this article is to illuminate the critical aspect of ensuring the sustained relevance and value of AI/ML capabilities integrated into software solutions. These capabilities constitute the core of applications, imbuing them with intelligent and self-decisioning functionalities that notably elevate the overall performance and utility of the software. The application of AI and ML capabilities has the potential to yield components endowed with predictive intelligence, thereby enhancing user experiences for end-users. Additionally, it can contribute to the development of more automated and highly optimized applications, leading to reduced maintenance and operational costs.

Navigating Legacy Labyrinths: Building on Unmaintainable Code vs. Crafting a New Module From Scratch

Aggregated on: 2024-02-05 17:02:03

In the dynamic realm of software development, developers often encounter the age-old dilemma of whether to build upon an existing, unmaintainable codebase or embark on the journey of creating a new module from scratch. This decision, akin to choosing between untangling a complex web and starting anew on a blank canvas, carries significant implications for the project's success. In this exploration, we delve into the nuances of these approaches, weighing the advantages, challenges, and strategic considerations that shape this pivotal decision-making process. The Landscape: Unmaintainable Code vs. Fresh Beginnings Building on Existing Unmaintainable Code Pros Time and Cost Efficiency

Next Generation Front-End Tooling: Vite

Aggregated on: 2024-02-05 16:47:03

In this article, we will look at Vite core features, basic setup, styling with Vite, Vite working with TypeScript and frameworks, working with static assets and images, building libraries, and server integration. Why Vite? Problems with traditional tools: Older build tools (grunt, gulp, webpack, etc.) require bundling, which becomes increasingly inefficient as the scale of a project grows. This leads to slow server start times and updates. Slow server start: Vite improves development server start time by categorizing modules into “dependencies” and “source code.” Dependencies are pre-bundled using esbuild, which is faster than JavaScript-based bundlers, while source code is served over native ESM, optimizing loading times. Slow updates: Vite makes Hot Module Replacement (HMR) faster and more efficient by only invalidating the necessary chain of modules when a file is edited. Why bundle for production: Despite the advancements, bundling is still necessary for optimal performance in production. Vite offers a pre-configured build command that includes performance optimizations. Bundler choice: Vite uses Rollup for its flexibility, although esbuild offers speed. The possibility of incorporating esbuild in the future isn’t ruled out. Vite Core Features Vite is a build tool and development server that is designed to make web development, particularly for modern JavaScript applications, faster and more efficient. It was created with the goal of improving the developer experience by leveraging native ES modules (ESM) in modern browsers and adopting a new, innovative approach to development and bundling. Here are the core features of Vite:

Mastering Concurrency: An In-Depth Guide to Java's ExecutorService

Aggregated on: 2024-02-05 15:32:03

In the realm of Java development, mastering concurrent programming is a quintessential skill for experienced software engineers. At the heart of Java's concurrency framework lies the ExecutorService, a sophisticated tool designed to streamline the management and execution of asynchronous tasks. This tutorial delves into the ExecutorService, offering insights and practical examples to harness its capabilities effectively. Understanding ExecutorService At its core, ExecutorService is an interface that abstracts the complexities of thread management, providing a versatile mechanism for executing concurrent tasks in Java applications. It represents a significant evolution from traditional thread management methods, enabling developers to focus on task execution logic rather than the intricacies of thread lifecycle and resource management. This abstraction facilitates a more scalable and maintainable approach to handling concurrent programming challenges.

Mastering Latency With P90, P99, and Mean Response Times

Aggregated on: 2024-02-05 15:32:03

In the fast-paced digital world, where every millisecond counts, understanding the nuances of network latency becomes paramount for developers and system architects. Latency, the delay before a transfer of data begins following an instruction for its transfer, can significantly impact user experience and system performance. This post dives into the critical metrics of latency: P90, P99, and mean response times, offering insights into their importance and how they can guide in optimizing services. The Essence of Latency Metrics Before diving into the specific metrics, it is crucial to understand why they matter. In the realm of web services, not all requests are treated equally, and their response times can vary greatly. Analyzing these variations through latency metrics provides a clearer picture of a system's performance, especially under load.

Effective Log Data Analysis With Amazon CloudWatch: Harnessing Machine Learning

Aggregated on: 2024-02-05 15:02:03

In today's cloud computing world, all types of logging data are extremely valuable. Logs can include a wide variety of data, including system events, transaction data, user activities, web browser logs, errors, and performance metrics. Managing logs efficiently is extremely important for organizations, but dealing with large volumes of data makes it challenging to detect anomalies and unusual patterns or predict potential issues before they become critical. Efficient log management strategies, such as implementing structured logging, using log aggregation tools, and applying machine learning for log analysis, are crucial for handling this data effectively. One of the latest advancements in effectively analyzing a large amount of logging data is Machine Learning (ML) powered analytics provided by Amazon CloudWatch. It is a brand new capability of CloudWatch. This innovative service is transforming the way organizations handle their log data. It offers a faster, more insightful, and automated log data analysis. This article specifically explores utilizing the machine learning-powered analytics of CloudWatch to overcome the challenges of effectively identifying hidden issues within the log data.

Data Lineage in Modern Data Engineering

Aggregated on: 2024-02-05 15:02:03

Data lineage is the tracking and visualization of the flow and transformation of data as it moves through various stages of a data pipeline or system. In simpler terms, it provides a detailed record of the origins, movements, transformations, and destinations of data within an organization's data infrastructure. This information helps to create a clear and transparent map of how data is sourced, processed, and utilized across different components of a data ecosystem. Data lineage allows developers to comprehend the journey of data from its source to its final destination. This understanding is crucial for designing, optimizing, and troubleshooting data pipelines. When issues arise in a data pipeline, having a detailed data lineage enables developers to quickly identify the root cause of problems. It facilitates efficient debugging and troubleshooting by providing insights into the sequence of transformations and actions performed on the data. Data lineage helps maintain data quality by enabling developers to trace any anomalies or discrepancies back to their source. It ensures that data transformations are executed correctly and that any inconsistencies can be easily traced and rectified.

Building a Simple gRPC Service in Go

Aggregated on: 2024-02-05 14:47:03

Client-server communication is a fundamental part of modern software architecture. Clients (on various platforms — web, mobile, desktop, and even IoT devices) request functionality (data and views) that servers compute, generate, and serve. There have been several paradigms facilitating this: REST/Http, SOAP, XML-RPC, and others. gRPC is a modern, open source, and highly performant remote procedure call (RPC) framework developed by Google enabling efficient communication in distributed systems. gRPC also uses an interface definition language (IDL) — protobuf — to define services, define methods, and messages as well as serializing structure data between servers and clients. Protobuf as a data serialization format is powerful and efficient — especially compared to text-based formats (like JSON). This makes a great choice for applications that require high performance and scalability.

Low-Code/No-Code Platforms: Seven Ways They Empower Developers

Aggregated on: 2024-02-05 14:47:03

There are people in the development world who dismiss low-code and no-code platforms as simplistic tools not meant for serious developers. But the truth is that these platforms are becoming increasingly popular among a wide range of professionals, including seasoned developers.

Guide for Voice Search Integration to Your Flutter Streaming App

Aggregated on: 2024-02-05 13:47:03

As the mobile app development world evolves, user engagement and satisfaction are at the forefront of considerations. Voice search, a transformative technology, has emerged as a key player in enhancing user experiences across various applications. In this step-by-step guide, we will explore how to seamlessly integrate voice search into your Flutter streaming app, providing users with a hands-free and intuitive way to interact with content. Why Flutter for Your Streaming Project? Flutter is a popular open-source framework for building cross-platform mobile applications, and it offers several advantages for streaming app development. Here are some reasons why Flutter might be a suitable choice for developing your streaming app:

Linux Mint Debian Edition Makes Me Believe It’s Finally the Year of the Linux Desktop

Aggregated on: 2024-02-05 12:32:03

It wasn't long ago that I decided to ditch my Ubuntu-based distros for openSUSE, finding LEAP 15 to be a steadier, more rock-solid flavor of Linux for my daily driver. The trouble is, I hadn't yet been introduced to Linux Mint Debian Edition (LMDE), and that sound you hear is my heels clicking with joy. LMDE 6 with the Cinnamon desktop.

Unveiling GitHub Copilot's Impact on Test Automation Productivity: A Five-Part Series

Aggregated on: 2024-02-05 12:02:03

Phase 1: Establishing the Foundation In the dynamic realm of test automation, GitHub Copilot stands out as a transformative force, reshaping the approach of developers and Quality Engineers (QE) towards testing. As QA teams navigate the landscape of this AI-driven coding assistant, a comprehensive set of metrics has emerged, shedding light on productivity and efficiency. Join us on a journey through the top key metrics, unveiling their rationale, formulas, and real-time applications tailored specifically for Test Automation Developers. 1. Automation Test Coverage Metrics Test Coverage for Automated Scenarios Rationale: Robust test coverage is crucial for effective test suites, ensuring all relevant scenarios are addressed. Test Coverage = (Number of Automated Scenarios / Total Number of Scenarios) * 100

Empowering Developers With Data in the Age of Platform Engineering

Aggregated on: 2024-02-05 12:02:03

The age of digital transformation has put immense pressure on developers. Research shows that developers spend just 40% of their time writing productive code, with the rest consumed by undifferentiated heavy lifting. This ineffective use of skilled talent hurts developer retention and productivity. At Dynatrace’s Perform 2024 conference, Andi Grabner, DevOps Activist at Dynatrace, sat down with Marcio Lena, IT Senior Director of Application Intelligence and SRE at Dell Technologies, to discuss how Dell is empowering developers in the platform engineering era.

How To Pass the Certified Kubernetes Administrator Examination

Aggregated on: 2024-02-05 12:02:03

The Certified Kubernetes Administrator (CKA) exam is a highly acclaimed credential for Kubernetes professionals. Kubernetes, an open-source container orchestration technology, is widely used for containerized application deployment and management. The CKA certification validates your knowledge of Kubernetes cluster design, deployment, and maintenance. We’ll walk you through the CKA test in this post, including advice, resources, and a study plan to help you succeed. Understanding the CKA Exam Before we dive into the preparation process, it’s essential to understand the CKA exam format and content. The CKA exam assesses your practical skills in the following areas:

GenAI in Data Engineering Beyond Text Generation

Aggregated on: 2024-02-05 01:17:03

Artificial Intelligence (AI) is driving unprecedented advancements in data engineering, with Generative AI (GenAI) at the forefront of innovation. While GenAI, exemplified by ChatGPT, is renowned for its prowess in text generation, its applications in data engineering extend far beyond mere linguistic tasks. This article illuminates the diverse and transformative uses of ChatGPT in data engineering, showcasing its potential to revolutionize processes, optimize workflows, and unlock new insights in the realm of data-centric operations. 1. Data Quality Assurance and Cleansing Ensuring data quality is a cornerstone of effective data engineering. ChatGPT can analyze datasets, pinpoint anomalies, and recommend data cleansing techniques. By leveraging its natural language understanding capabilities, ChatGPT aids in automating data validation processes, enhancing data integrity, and streamlining data cleansing efforts.

AWS SageMaker vs. Google Cloud AI: Unveiling the Powerhouses of Machine Learning

Aggregated on: 2024-02-05 01:02:03

AWS SageMaker and Google Cloud AI emerge as titans in the rapidly evolving landscape of cloud-based machine learning services, offering powerful tools and frameworks to drive innovation. As organizations navigate the realm of AI and seek the ideal platform to meet their machine learning needs, a comprehensive comparison of AWS SageMaker and Google Cloud AI becomes imperative. In this article, we dissect the strengths and capabilities of each, aiming to provide clarity for decision-makers in the ever-expanding domain of artificial intelligence. 1. Ease of Use and Integration AWS SageMaker AWS SageMaker boasts a user-friendly interface with a focus on simplifying the machine learning workflow. It seamlessly integrates with other AWS services, offering a cohesive environment for data preparation, model training, and deployment. The platform's managed services reduce the complexity associated with setting up and configuring infrastructure.

AIOps Now: Scaling Kubernetes With AI and Machine Learning

Aggregated on: 2024-02-04 19:17:03

If you are a site reliability engineer (SRE) for a large Kubernetes-powered application, optimizing resources and performance is a daunting job. Some spikes, like a busy shopping day, are things you can broadly schedule, but, if done right, would require painstakingly understanding the behavior of hundreds of microservices and their interdependence that has to be re-evaluated with each new release — not a very scalable approach, let alone the monotony and resulting stress to the SRE. Moreover, there will always be unexpected peaks to respond to. Continually keeping tabs on performance and putting the optimal amount of resources in the right place is essentially impossible. The way this is being solved now is through gross overprovisioning, or a combination of guesswork and endless alerts — requiring support teams to review and intervene. It’s simply not sustainable or practical, and certainly not scalable. But it’s just the kind of problem that machine learning and AI thrives on. We have spent the last decade dealing with such problems, and the arrival of the latest generation of AI tools such as generative AI has opened the possibility of applying machine learning to the real problems of the SRE to realize the promise of AIOps.

Oracle Cloud Infrastructure: A Comprehensive Suite of Cloud Services

Aggregated on: 2024-02-04 18:47:03

Oracle Cloud Infrastructure (OCI) is a dependable and scalable cloud platform that provides a diversified set of services to businesses and organizations. OCI has established itself as a key participant in the cloud computing business with to its cutting-edge technology, broad network of data centers, and complete suite of cloud products. In this article, we will look at the primary cloud services offered by Oracle Cloud Infrastructure and the benefits they give to enterprises. 1. Compute Services Oracle Cloud Infrastructure provides a range of compute services to cater to different workload requirements. These services include:

The Role of DevOps in Enhancing the Software Development Life Cycle

Aggregated on: 2024-02-03 20:02:02

Software development is a complex and dynamic field requiring constant input, iteration, and collaboration. The need for reliable, timely, and high-quality solutions has never been higher in today's fiercely competitive marketplace. Enter DevOps, a revolutionary approach that serves as the foundation for addressing such challenges. DevOps is more than just a methodology; it combines practices seamlessly integrating software development and IT operations for streamlining workflow. DevOps, with its emphasis on improving communication, promoting teamwork, and uniting software delivery teams, acts as a trigger for a development process that is more responsive and synchronized.

Optimize ASP.NET Core MVC Data Transfer With Custom Middleware

Aggregated on: 2024-02-03 19:47:02

In ASP.NET Core, middleware components are used to handle requests and responses as they flow through the application's pipeline. These middleware components can be chained together to process requests and responses in a specific order. Transferring data between middleware components can be achieved using various techniques. Here are a few commonly used methods. HttpContext.Items The HttpContext class in ASP.NET Core provides a dictionary-like collection (Items) that allows you to store and retrieve data within the scope of a single HTTP request. This data can be accessed by any middleware component in the request pipeline.

WebRTC vs. RTSP: Understanding The IoT Video Streaming Protocols

Aggregated on: 2024-02-03 19:32:02

At the moment, there is a constantly increasing number of smart video cameras collecting and streaming video throughout the world. Of course, many of those cameras are used for security. In fact, the global video surveillance market is expected to reach $83 billion in the next five years. But there are lots of other use cases besides security, including remote work, online education, and digital entertainment.

Advanced CI/CD Pipelines: Mastering GitHub Actions for Seamless Software Delivery

Aggregated on: 2024-02-03 19:02:02

In the rapidly evolving landscape of software development, continuous integration and continuous delivery (CI/CD) stand out as crucial practices that streamline the process from code development to deployment. GitHub Actions, a powerful automation tool integrated into GitHub, has transformed how developers implement CI/CD pipelines, offering seamless software delivery with minimal effort. This article delves into mastering GitHub Actions and provides an overview of a self-hosted runner to build advanced CI/CD pipelines, ensuring faster, more reliable software releases. Understanding GitHub Actions GitHub Actions enables automation of workflows directly in your GitHub repository. You can automate your build, test, and deployment phases by defining workflows in YAML files within your repository. This automation not only saves time but also reduces the potential for human error, making your software delivery process more efficient and reliable.

The Future Is Cloud-Native: Are You Ready?

Aggregated on: 2024-02-03 18:47:02

Why Go Cloud-Native? Cloud-native technologies empower us to produce increasingly larger and more complex systems at scale. It is a modern approach to designing, building, and deploying applications that can fully capitalize on the benefits of the cloud. The goal is to allow organizations to innovate swiftly and respond effectively to market demands. Agility and Flexibility Organizations often migrate to the cloud for the enhanced agility and the speed it offers. The ability to set up thousands of servers in minutes contrasts sharply with the weeks it typically takes for on-premises operations. Immutable infrastructure provides confidence in configurable and secure deployments and helps reduce time to market.

Software-Defined Networking in Distributed Systems: Transforming Data Centers and Cloud Computing Environments

Aggregated on: 2024-02-03 18:32:02

In the changing world of data centers and cloud computing, the desire for efficient, flexible, and scalable networking solutions has resulted in the broad use of Software-Defined Networking (SDN). This novel method to network management is playing an important role in improving the performance, agility, and overall efficiency of distributed systems. Understanding Software-Defined Networking (SDN) At its core, Software-Defined Networking (SDN) represents a fundamental shift in the way we conceptualize and manage network infrastructure. Traditional networking models have a tightly integrated control plane and data plane within network devices. This integration often leads to challenges in adapting to changing network conditions, scalability issues, and limitations in overall network management.

Mobile App Development Process: 6-Step Guide

Aggregated on: 2024-02-02 19:17:02

According to a McKinsey survey, more than 77 percent of CIOs are considering a mobile-first approach for digital transformation. The next generation of customers and employees will be digital-native and have greater familiarity with touch screen devices. Moreover, the business case for mobile apps continues to expand as 82 percent of American adults own a smartphone as of 2023, up from just 35 percent in 2011. Mobile apps are now a necessity for businesses to attract new customers and retain employees. Regardless of the size and scope of your project, following this mobile development process will help you launch your mobile apps successfully.

Implementation of the Raft Consensus Algorithm Using C++20 Coroutines

Aggregated on: 2024-02-02 19:02:02

This article describes how to implement a Raft Server consensus module in C++20 without using any additional libraries. The narrative is divided into three main sections: A comprehensive overview of the Raft algorithm A detailed account of the Raft Server's development A description of a custom coroutine-based network library The implementation makes use of the robust capabilities of C++20, particularly coroutines, to present an effective and modern methodology for building a critical component of distributed systems. This exposition not only demonstrates the practical application and benefits of C++20 coroutines in sophisticated programming environments, but it also provides an in-depth exploration of the challenges and resolutions encountered while building a consensus module from the ground up, such as Raft Server. The Raft Server and network library repositories, miniraft-cpp and coroio, are available for further exploration and practical applications.

Top 4 Developer Takeaways From the 2024 Kubernetes Benchmark Report

Aggregated on: 2024-02-02 18:47:02

We already know that Kubernetes revolutionized cloud-native computing by helping developers deploy and scale applications more easily. However, configuring Kubernetes clusters so they are optimized for security, efficiency, and reliability can be quite difficult. The 2024 Kubernetes Benchmark Report analyzed over 330,000 K8s workloads to identify common workload configuration issues as well as areas where software developers and the infrastructure teams that support them have made noticeable improvements over the last several years. 1. Optimize Cost Efficiency Efficient resource management is key to optimizing cloud spend. The Benchmark Report shows significant improvements in this area: 57% of organizations have 10% or fewer workloads that require container right-sizing. Software developers can use open-source tools such as Goldilocks, Prometheus, and Grafana to monitor and manage resource utilization. Appropriately setting CPU and memory requests and limits helps developers prevent resource contention issues and optimize cluster performance. Right-sizing means increasing resources to improve reliability or lowing resources to improve utilization and efficiency based on the requirements of each application and service.

Edge Computing Orchestration in IoT: Coordinating Distributed Workloads

Aggregated on: 2024-02-02 15:17:02

In the rapidly evolving landscape of the Internet of Things (IoT), edge computing has emerged as a critical paradigm to process data closer to the source—IoT devices. This proximity to data generation reduces latency, conserves bandwidth and enables real-time decision-making. However, managing distributed workloads across various edge nodes in a scalable and efficient manner is a complex challenge. In this article, we will delve into the concept of orchestration in IoT edge computing, exploring how coordination and management of distributed workloads can be enhanced through the integration of Artificial Intelligence (AI). Understanding Edge Computing Orchestration Edge computing orchestration is the art and science of managing the deployment, coordination, and scaling of workloads across a network of edge devices. It plays a pivotal role in ensuring that tasks are distributed effectively, resources are optimized, and the overall system operates efficiently. In IoT environments, orchestrating edge computing is particularly challenging due to the heterogeneity of devices, intermittent connectivity, and resource constraints.

Simplifying Data Management for Technology Teams With HYCU

Aggregated on: 2024-02-02 14:02:01

Managing data across complex on-premise, multi-cloud, and SaaS environments is an increasingly difficult challenge for technology developers, engineers, and architects. With data now spread across over 200 silos on average, most organizations are struggling to protect business critical information residing outside core infrastructure. To help address this issue, Boston-based HYCU has developed an innovative data management platform that aims to streamline processes for technology teams. As HYCU CEO and Founder Simon Taylor explained during the 53rd IT Press Tour, "When you don’t understand where your data is, and you can’t protect it, you’re setting yourself up for a SaaS data apocalypse."

From Chaos to Control: Nurturing a Culture of Data Governance

Aggregated on: 2024-02-02 13:32:01

The evolving nature of technology, increased data volumes, novel data regulations and compliance standards, and changing business landscapes in the last decade are resulting in data chaos and inconsistency for many enterprises, and that is resulting in enterprises going towards adopting a data governance culture. Data governance is a set of practices and policies that ensure high data quality, data management, data protection, and overall data stewardship within an organization. It involves defining and implementing processes, roles, responsibilities, and standards to ensure that data is managed effectively throughout its lifecycle. Data governance generally includes:

Community Software Used in Cloud Computing

Aggregated on: 2024-02-02 13:32:01

The cloud has transformed the way we store, process, and access data and applications. As the need for scalable, versatile, and cost-effective cloud solutions grows, open-source community software has played an important role in developing the cloud computing environment. In this post, we will look at the numerous community-driven software that enable cloud computing and how they have aided in the progress of the business. Understanding Cloud Computing Before we enter into the realm of community software in cloud computing, let us first define cloud computing and why it has become such an important aspect of modern technology.

How LangChain Enhances the Performance of Large Language Models

Aggregated on: 2024-02-02 13:17:01

What do you think of the Artificial Intelligence Development market? Well, as per a Markets and Markets report with a CAGR of nearly 36.8% for 2023-30, things are continuously changing and growing. This has paved the path for Large Language Models (LLMs) to do things they couldn’t before. There's a new technique called "LangChain" that has the potential to completely change how we use LLMs in generative AI development. In this dive, we will go deep into LangChain. Covering everything from its key principles to how it can be used in real-world applications. You'll have a better understanding of how it’s going to change the way AI generates content when you’re done. The Concept of LangChain LangChain is really exciting because it takes the powerful capabilities of Large Language Models, or LLMs, like GPT-3, and puts a spin on it. While LLMs are pretty impressive, there are times when they just can’t write with the finesse that humans can. They lack proper grammar, style, and context. In comes LangChain fixes this by using multiple specialized models that work together in perfect harmony.

DLP: AI-Based Approach

Aggregated on: 2024-02-02 13:02:01

DLP, or Data Loss Prevention, is a proactive approach and set of technologies designed to safeguard sensitive information from unauthorized access, sharing, or theft within an organization. Its primary goal is to prevent data breaches and leaks by monitoring, detecting, and controlling the flow of data across networks, endpoints, and storage systems. DLP solutions employ a variety of techniques to achieve their objectives:

Digital Transformation in Engineering: A Journey of Innovation in Retail

Aggregated on: 2024-02-02 12:32:01

Digital transformation is the goal of each business in the retail industry today. It is the tool used by various businesses across the world to understand and modify their business models. A digital transformation is a strategic approach through which businesses access a wider market. It is a process by which the company integrates new technologies into its operations. Different departments within the company can rely on the technology for data analytics, especially with the growing customer base. As a result, digital transformation gives companies a better avenue through which they can engage their customers to understand and meet their needs effectively. Digital transformation is relevant in the current business environments due to the changing customer needs. Organizations are experiencing a very competitive business environment in which new technologies are giving customers convenience. Customers’ expectations, therefore, already reflect the changing technical landscape. Online shopping, tracking orders online, and personalized advertisements that suit customers’ preferences are some of the elements affecting customer experience. In the retail sector, changing customer expectations in the wake of new technology influences a company’s competitive advantage. Markedly, companies that invest massive resources in digital transformations have an advantage compared to those still relying on traditional business models.

Keep Calm and Column Wise

Aggregated on: 2024-02-02 12:02:01

While SQL was invented for the relational model, it has been unreasonably effective for many forms of data, including document data with type heterogeneity, nesting, and no schema. Couchbase Capella has both operational and analytical engines. Both the operational and analytical engines support JSON for data modeling and SQL++ for querying. As operational and analytical use cases have different workload requirements, Couchbase's two engines have different capabilities that are tailored to address each workload's requirements. This article highlights some of the new features and capabilities of Couchbase's new analytical service, the Capella Columnar service. To improve real-time data processing, Couchbase has introduced the Capella Columnar service. There are many differentiating technologies in this new service, including column-wise storage for a schemaless data engine and its processing. In this article, we’ll give you an overview of the challenges of implementing column-wise storage for JSON and the techniques used in the Columnar service to address these challenges.

Legal and Compliance Considerations in Cloud Computing

Aggregated on: 2024-02-01 21:17:01

Cloud computing has transformed software development and management, facilitating unparalleled scalability, flexibility, and cost efficiency. Nevertheless, this paradigm change has faced challenges, primarily legal and compliance issues. Data, services, and infrastructure often reside in a nebulous space, not directly owned or fully controlled by the user. This can present severe legal issues, particularly regarding data ownership. According to S. Krishnan, the transforming nature of computing has created legal uncertainties, especially in establishing who owns or possesses data when it resides within the cloud. These legal and compliance challenges are studied in this article, specifically looking at the effects on software developers. With cloud computing dominating all technology sectors, comprehending these legal nuances is necessary for developers to appropriately navigate the modern digital landscape.

AI for Testers

Aggregated on: 2024-02-01 20:47:01

The excitement surrounding artificial intelligence has undeniably captured the attention of testers, much like it has for engineers and professionals across the IT landscape. As we step into 2024, the question arises: What does the future hold for testers in the realm of AI? I recall posing a similar question back in 2018 when the prevalence of cloud computing became an imperative and indispensable component, compelling every software solution and professional to adapt in order to remain pertinent in the ever-evolving IT landscape. Like any dedicated professional, staying attuned to and upskilling with the evolving times not only provides a strategic advantage for personal growth but also positions you ahead of the curve. Since 2020, artificial intelligence (AI) has undergone an observational phase. However, in the past year or so, a notable shift has occurred with the emergence of simulation and democratization, manifested through innovative chatbots and tools. These tools claim to seamlessly integrate with your existing test automation setup, enhancing productivity for testers. Despite the promising advancements, the lack of concrete case studies demonstrated some reluctance to go out all at once.

Decoding Data Analysis: Transforming Cross-Tabulation Into Structured Tabular Tables

Aggregated on: 2024-02-01 19:47:01

Looking at the two tables below, which format do you find more intuitive and easier to read? For years, people have been using spreadsheet software to create cross-tabulated (or contingency, multi-dimensional) reports or fill forms. These reports neatly organize categories, dates, and other data points into levels of rows and columns, making them easy to read and analyze.

What You Possibly Don’t Know About Columnar Storage

Aggregated on: 2024-02-01 18:17:01

Columnar storage is a commonly used storage technique. Often, it implies high performance and has basically become a standard configuration for today’s analytical databases. The basic principle of columnar storage is reducing the amount of data retrieved from the hard disk. A data table can have a lot of columns, but the computation may use only a very small number of them. With columnar storage, useless columns do not need to be retrieved, while with row-wise storage, all columns need to be scanned. When the retrieved columns only take up a very small part of the total, columnar storage has a big advantage in terms of IO time, and computation seems to get much faster.

Improving Upon My OpenTelemetry Tracing Demo

Aggregated on: 2024-02-01 17:47:01

Last year, I wrote a post on OpenTelemetry Tracing to understand more about the subject. I also created a demo around it, which featured the following components: The Apache APISIX API Gateway A Kotlin/Spring Boot service A Python/Flask service And a Rust/Axum service I've recently improved the demo to deepen my understanding and want to share my learning.

A Brief History of DevOps and the Link to Cloud Development Environments

Aggregated on: 2024-02-01 17:32:01

The history of DevOps is definitely worth reading in a few good books about it. On that topic, “The Phoenix Project,” self-characterized as “a novel of IT and DevOps,” is often mentioned as a must-read. Yet for practitioners like myself a more hands-on one is “The DevOps Handbook” (which shares Kim as author in addition to Debois, Willis, and Humble) that recounts some of the watershed moments around the evolution of software engineering and provides good references around implementation. This book actually describes how to replicate the transformation explained in the Phoenix Project and provides case studies. In this brief article, I will use my notes on this great book to regurgitate a concise history of DevOps, add my personal experience and opinion, and establish a link to Cloud Development Environments (CDEs), i.e., the practice of providing access to and running, development environments online as a service for developers.