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How To Implement Specific Distributed System Patterns Using Spring Boot: Introduction

Aggregated on: 2024-09-11 18:36:10

Regarding contemporary software architecture, distributed systems have been widely recognized for quite some time as the foundation for applications with high availability, scalability, and reliability goals. When systems shifted from a centralized structure, it became increasingly important to focus on the components and architectures that support a distributed structure. Regarding the choice of frameworks, Spring Boot is a widely adopted framework encompassing many tools, libraries, and components to support these patterns. This article will focus on the specific recommendations for implementing various distributed system patterns regarding Spring Boot, backed by sample code and professional advice. Spring Boot Overview One of the most popular Java EE frameworks for creating apps is Spring. The Spring framework offers a comprehensive programming and configuration mechanism for the Java platform. It seeks to make Java EE programming easier and increase developers' productivity in the workplace. Any type of deployment platform can use it. It tries to meet modern industry demands by making application development rapid and straightforward. While the Spring framework focuses on giving you flexibility, the goal of Spring Boot is to reduce the amount of code and give developers the most straightforward approach possible to create web applications. Spring Boot's default codes and annotation setup lessen the time it takes to design an application. It facilitates the creation of stand-alone applications with minimal, if any, configuration. It is constructed on top of a module of the Spring framework.

Optimizing Container Synchronization for Frequent Writes

Aggregated on: 2024-09-11 17:36:10

Efficient data synchronization is crucial in high-performance computing and multi-threaded applications. This article explores an optimization technique for scenarios where frequent writes to a container occur in a multi-threaded environment. We’ll examine the challenges of traditional synchronization methods and present an advanced approach that significantly improves performance for write-heavy environments. The method in question is beneficial because it is easy to implement and versatile, unlike pre-optimized containers that may be platform-specific, require special data types, or bring additional library dependencies. Traditional Approaches and Their Limitations Imagine a scenario where we have a cache of user transactions:

8 Practices Software Engineers Should Adopt and Champion for Cybersecurity

Aggregated on: 2024-09-11 16:21:10

The Importance of Cybersecurity I firmly believe that in today's cybersecurity expectations, software engineers should prioritize the security of their computer systems and internal IT networks. I would consider it to be a mistake to rely heavily on technology due to the simple fact that a lot of risks are non-technical in nature. The Internet can leave businesses vulnerable to data breaches and ransomware attacks that can cause lasting reputational damage. These non-technical risks can indeed be addressed using technical solutions. These incidents can additionally result in significant financial losses and potential legal issues. In my opinion, implementing strong cybersecurity measures is not just a technical requirement but a critical initiative for any business looking to strengthen its defenses and resilience.

The Significance of Complex Event Processing (CEP) With RisingWave for Delivering Accurate Business Decisions

Aggregated on: 2024-09-11 15:21:10

About Complex Event Processing (CEP) Complex event processing (CEP) is a highly effective and optimized mechanism that combines several sources of information and instantly determines and evaluates the relationships among events in real time. It is a real-time data and event identification, processing, and analysis approach. By gathering and combining across various IoT sensor feeds, CEP has a transformative effect by collecting IoT sensor streams for real-time monitoring, analytics, and troubleshooting. CEP provides insight into what's happening by continuously comparing incoming events to patterns. This enables us to operate proactively and effectively. Although event stream processing (ESP) and CEP are often used interchangeably, they are not exactly the same. Traditional ESP applications typically handle a single stream of data that arrives in the correct time sequence. For instance, in algorithmic trading, an ESP application might analyze a stream of pricing data to decide whether to buy or sell a stock. However, ESP generally doesn't account for event causality or hierarchies. This limitation led to the development of CEP, which is essentially a more advanced and sophisticated version of ESP.

Real-Time GenAI With RAG Using Apache Kafka and Flink To Prevent Hallucinations

Aggregated on: 2024-09-11 14:21:10

How do you prevent hallucinations from large language models (LLMs) in GenAI applications? LLMs need real-time, contextualized, and trustworthy data to generate the most reliable outputs. This blog post explains how RAG and a data streaming platform with Apache Kafka and Flink make that possible. A lightboard video shows how to build a context-specific real-time RAG architecture. Also, learn how the travel agency Expedia leverages data streaming with Generative AI using conversational chatbots to improve the customer experience and reduce the cost of service agents. What Is Retrieval Augmented Generation (RAG) in GenAI? Generative AI (GenAI) refers to artificial intelligence (AI) systems that can create new content, such as text, images, music, or code, often mimicking human creativity. These systems use advanced machine learning techniques, particularly deep learning models like neural networks, to generate data that resembles the training data they were fed. Popular examples include language models like GPT-3 for text generation and DALL-E for image creation.

Modes and Modality in Performance Testing

Aggregated on: 2024-09-11 13:21:10

When reporting summary statistics for performance test results, there's a common assumption that the data follows a central tendency. But is this always true? What if the data does not exhibit a single central tendency? In such cases, the traditional metrics like averages might be misleading. This article explores why it's crucial to check for modality of performance test results, how to detect multimodal distributions, and how to handle them. For users of JMeter, a new plugin is introduced to help automate this process.

Automatic 1111: Custom Sketch-To-Image API

Aggregated on: 2024-09-10 22:21:10

In this article, we will develop a custom Sketch-to-Image API for converting hand-drawn or digital sketches into photorealistic images using stable diffusion models powered by a ControlNet model. We will extend the Automatic 1111's txt2img API to develop this custom workflow. Prerequisites Stable Diffusion Web UI (Automatic 1111) running on your local machine. Follow the instructions here if you are starting from scratch. SD APIs Enabled. Follow the instructions on this page (scroll down to the Enabling APIs section) to enable the APIs if you haven't already done so. ControlNet extension installed: Click on the Extensions tab on Stable Diffusion Web UI. Navigate to the Install from URL tab. Paste the following link in URL for extension's git repository input field and click Install. After the successful installation, restart the application by closing and reopening the run.bat file if you're a PC user; Mac users may need to run ./webui.sh instead. After restarting the application, the ControlNet dropdown will become visible under the Generation tab in the txt2img screen. Download and add the following models to Automatic 1111: RealVisXL_V4.0_Lightning: HuggingFace: SG161222/RealVisXL_V4.0_Lightning. Copy this model to the Stable Diffusion models folder which is under the project root directory:/models/Stable-diffusion diffusers_xl_canny_full - HuggingFace: lllyasviel/sd_control_collection Copy the downloaded model to /extensions/sd-webui-controlnet Payload Now that we have all our prerequisites in place, let's build the payload for the/sdapi/v1/txt2img API.

Exploring Real-Time Data Ingestion Into Snowflake Using CockroachDB, Redpanda, and Kafka Connect

Aggregated on: 2024-09-10 21:21:10

Previous Articles on Snowflake Tour of Snowflake ingestion using CockroachDB and Redpanda Connect Integrating Snowflake with Trino Previous Articles on CockroachDB CDC Emitting Protocol Buffers with CockroachDB CDC Queries Using CockroachDB CDC with Apache Pulsar Using CockroachDB CDC with Azure Event Hubs SaaS Galore: Integrating CockroachDB with Confluent Kafka, FiveTran, and Snowflake Using CockroachDB CDC with Confluent Cloud Kafka and Schema Registry CockroachDB CDC using Minio as cloud storage sink CockroachDB CDC using Hadoop Ozone S3 Gateway as cloud storage sink Motivation This article builds upon the previous discussion in "Tour of Snowflake ingestion using CockroachDB and Redpanda Connect," where we investigated the process of streaming changefeeds from CockroachDB to Snowflake using Redpanda Connect and Snowpipe in batch mode. Here, we will shift our focus to Kafka Connect and demonstrate how both batch and streaming modes can be utilized for data ingestion into Snowflake. Overview Deploy a CockroachDB cluster with enterprise changefeeds Deploy Snowflake Deploy Kafka Connect Verify Conclusion Detailed Instructions Deploy a CockroachDB Cluster With Enterprise Changefeeds Start by either launching a CockroachDB instance or utilizing a managed service.

REST and HTTP Semantics

Aggregated on: 2024-09-10 20:21:10

Roy Fielding created REST as his doctorate dissertation. After reading it, I would boil it down to three basic elements: A document that describes object state A transport mechanism to transmit the object state back and forth between systems A set of operations to perform on the state While Roy was focused solely on HTTP, I don't see why another transport could not be used. Here are some examples:

Explainable AI (XAI): How Developers Build Trust and Transparency in AI Systems

Aggregated on: 2024-09-10 19:21:10

Developers working on Explainable AI (XAI) must address several key aspects, such as the problem, boundary scope, and potential solutions of XAI, as well as some specific use cases and benefits that can enhance an organization's credibility when implementing or leveraging this technology. The more AI is incorporated into different sectors, developers play a critical role in making those systems interpretable and transparent. XAI is crucial in making AI models highly interpretable and debuggable; it also guarantees responsible use of highly complex AI technologies, which should be fair, transparent, and accountable to society's users and stakeholders.

Transforming Continuous Delivery With Feature Flags

Aggregated on: 2024-09-10 18:21:10

Continuous Delivery is a practice and methodology that helps you build and deploy your software faster so that it can be released to production systems at any time. It facilitates shortening the lifecycle times of various development and operations processes. Effectively applying the concepts of Continuous Integration (CI) and Continuous Deployment (CD) helps achieve the benefits of the continuous delivery principles, also enabling faster software releases. We explore the challenges encountered by software teams implementing CI/CD and demonstrate how feature flags can help mitigate these risks.

Accelerate Your Journey to a Modern Data Platform Using Coalesce

Aggregated on: 2024-09-10 17:06:10

Most organizations face challenges while adapting to data platform modernization. The critical challenge that data platforms have faced is improving the scalability and performance of data processing due to the increased volume, variety, and velocity of data used for analytics. This article aims to summarize answers to the challenging questions of data platform modernization, and here are a few questions:

Digital Garden

Aggregated on: 2024-09-10 16:06:10

The topic of note-taking remains relevant today. We know the benefits it provides to the author. We are familiar with various approaches to note-taking and tools that can be used, and we have choices. Imagine you have found your approach, your tool, and your note base is growing and pleasing to the eye. What next? I want to discuss one path of development in this area. This article is dedicated to the concept of a digital garden — the philosophy of publicly maintaining personal notes.

How Can the Scalability of MySQL Be Improved for BenchmarkSQL TPC-C Testing?

Aggregated on: 2024-09-10 15:06:10

Current State of MySQL 5.7 MySQL 5.7 is not ideal in terms of scalability. The following figure illustrates the relationship between TPC-C throughput and concurrency in MySQL 5.7.39 under a specific configuration. This includes setting the transaction isolation level to Read Committed and adjusting the innodb_spin_wait_delay parameter to mitigate throughput degradation. Figure 1: Scalability problems in MySQL 5.7.39 during BenchmarkSQL testing

Mastering Multi-Cloud and Edge Data Synchronization: A Retail Use Case With KubeMQ’s Java SDK

Aggregated on: 2024-09-10 14:06:10

In today’s rapidly evolving enterprise landscape, managing and synchronizing data across complex environments is a significant challenge. As businesses increasingly adopt multi-cloud strategies to enhance resilience and avoid vendor lock-in, they are also turning to edge computing to process data closer to the source. This combination of multi-cloud and edge computing offers significant advantages, but it also presents unique challenges, particularly in ensuring seamless and reliable data synchronization across diverse environments. In this post, we’ll explore how the open-source KubeMQ’s Java SDK provides an ideal solution for these challenges. We’ll focus on a real-life use case involving a global retail chain that uses KubeMQ to manage inventory data across its multi-cloud and edge infrastructure. Through this example, we’ll demonstrate how the solution enables enterprises to achieve reliable, high-performance data synchronization, transforming their operations.

Top Security Flaws Hiding in Your Code Right Now and How To Fix Them

Aggregated on: 2024-09-10 13:51:10

In 2019, a famous breach in Fortnite, the famous game, reportedly put millions of players at risk of malware. The incident highlighted the importance of properly securing SQL databases. But this is not an isolated issue.

Zero To AI Hero, Part 2: Understanding Plugins in Semantic Kernel, A Deep Dive With Examples

Aggregated on: 2024-09-10 13:06:10

I talked a little about semantic kernel in Part 1 but decided to leave out the juicy part. There are a few gears in SK. They spin and connect like the inside of the watch to make it do the magic. One of those gears is plugins. Plugins are the robotic arms of Semantic Kernel, capable of doing some work beyond chit-chatting. Why Do We Need Plugins? We all know GenAI is about — surprise, surprise: "Generative AI". What do they train on? Tokens. These tokens are then mapped onto vector databases and can be used to predict the next token, etc, and the story goes on and on. What are these models capable of? Predicting subsequent tokens, and that's about it (at least as of now). So, for those who think GAI is equal to AGI, no! Not yet!

Spring Boot GoT: Game of Trace!

Aggregated on: 2024-09-09 23:06:09

When we, developers, find some bugs in our logs, this sometimes is worse than a dragon fight! Let's start with the basics. We have this order of severity of logs, from most detailed to no detail at all:

Working With Multiple testng.xml Files

Aggregated on: 2024-09-09 20:06:09

While working on an open source GitHub project that was created to showcase the working of Selenium WebDriver framework with Java, as the project grew, there was a need to create multiple testng.xml files for running different tests. These multiple files were created to segregate the tests and place all the tests related to a respective website in a single testng.xml (I have used different demo websites to demo different actions that can be automated using Selenium WebDriver).

Model-Driven Development and Testing

Aggregated on: 2024-09-09 19:06:09

The Meta of Design With several decades of experience, I love building enterprise applications for companies. Each solution requires a set of models: an SQL database, an API (Application Programming Interface), declarative rules, declarative security (role-based access control), test-driven scenarios, workflows, and user interfaces. The "meta" approach to design requires thinking of how each of these components interacts with the other. We also need to understand how changes in the scope of the project impact each of these meta-components. While I have worked in many different languages (APL, Revelation/PICK, BASIC, Smalltalk, Object/1, Java, JavaScript, Node.js, Python) these models are always the foundation that influences the final integrated solution. Models are meta abstractions that describe how the shape, content, and ability of the object will behave in the running environment regardless of language, platform, or operating system (OS). Model First Approach Starting with an existing SQL Schema and a good ORM allows the abstraction of the database and the generation of an API. I have been working with ApiLogicServer (a GenAI-powered Python open-source platform) which has a command line interface to connect the major SQL databases and create an SQLAlchemy ORM (Object-Relational Model). From this model, an Open API (aka Swagger) for JSON API is created, and a YAML file (model) drives a react-admin runtime. The YAML file is also used to build an Ontimize (Angular) user interface. Note that the GenAI part of ApiLogicServer lets me use a prompt-driven approach to get this entire running stack using just a few keywords.

The Pre-Mortem: Preventing Product Failure Before It Strikes

Aggregated on: 2024-09-09 17:06:09

TL; DR: The Pre-Mortem: A Non-negotiable Part of Your Product Development Toolbox Do you want to build products that avoid costly mistakes, meet customer needs, and drastically enhance your career prospects? The the pre-mortem is your secret weapon! By imagining how a project might fail before it even begins, teams can identify and mitigate hidden risks early, ensuring a more resilient, successful outcome. This article explains why pre-mortems are a brilliant tool for risk mitigation, improving your team’s decision process, and how they can transform your product development process. Learn how to apply this proactive strategy and create bulletproof products.

What Are Logging Levels?

Aggregated on: 2024-09-09 15:51:09

Logging is one of the most important parts of the distributed systems. Many things can break, but when the logging breaks, then we are completely lost. In this blog post, we will understand log levels and how to log efficiently in distributed systems. Logging Levels Whenever we log a message, we need to specify the log level or log severity. It’s an indicator of how important the message is and who should be concerned.

Data Storage Formats for Big Data Analytics: Performance and Cost Implications of Parquet, Avro, and ORC

Aggregated on: 2024-09-09 14:06:09

Efficient data processing is crucial for businesses and organizations that rely on big data analytics to make informed decisions. One key factor that significantly affects the performance of data processing is the storage format of the data. This article explores the impact of different storage formats, specifically Parquet, Avro, and ORC on query performance and costs in big data environments on Google Cloud Platform (GCP). This article provides benchmarks, discusses cost implications, and offers recommendations on selecting the appropriate format based on specific use cases. Introduction to Storage Formats in Big Data Data storage formats are the backbone of any big data processing environment. They define how data is stored, read, and written directly impacting storage efficiency, query performance, and data retrieval speeds. In the big data ecosystem, columnar formats like Parquet and ORC and row-based formats like Avro are widely used due to their optimized performance for specific types of queries and processing tasks.

Mastering Tailwind CSS: Overcome Styling Conflicts With Tailwind Merge and clsx

Aggregated on: 2024-09-06 23:08:09

People have been emailing and asking me to write something on some soft topics for beginners, as I write mostly for mid-level or seniors. So, here is a new article for beginners, especially for UI developers. Today, let's explore the common challenges developers face when working with Tailwind CSS and how to overcome them using the powerful combination of Tailwind Merge and clsx.

Mainframe Modernization: A Comprehensive Technical Blueprint

Aggregated on: 2024-09-06 21:08:09

Mainframe systems have been the backbone of enterprise computing for decades, renowned for their reliability, performance, and security. However, the evolving business landscape demands agility, scalability, and cost-effectiveness, prompting organizations to explore cloud-based solutions. Major technology companies, including cloud providers and system integrators, have invested heavily in mainframe migration practices, recognizing the significance of this transformation. Mainframes and cloud computing each have their strengths and specific use cases. It's not fair to generalize either, and in practice, a hybrid approach is common. This post will explore a practical solution for mainframe workload migration using a hybrid pattern, where certain workloads move to the cloud while still interacting with on-premises applications and data sources.

Comparison of Apache Astro and Airflow

Aggregated on: 2024-09-06 19:08:09

Effective workflow orchestration is the key to creating automation around complex process-oriented activities in the modern landscape of software development. Considering data engineering and data science, Astro and Apache Airflow rise to the top as important tools used in the management of these data workflows. This article compares Astro and Apache Airflow, explaining their architecture, features, scalability, usability, community support, and integration capabilities. This should help software developers and data engineers in selecting the right tool for their specific needs and project requirements. Astro Overview Astro is a fully Kubernetes-native platform designed to easily orchestrate the workflows in cloud-native systems. It uses Kubernetes itself to handle container orchestration, which adds fault tolerance and elasticity out of the box. Hence, Astro works effectively in scenarios that require microservices and containerization to be essential to the architecture.

Principles of Modern Data Infrastructure

Aggregated on: 2024-09-06 17:08:09

The evolution of the internet over the past few decades has undeniably impacted how our societies function. From facilitating globalization to making new technology like social media and consumer apps available to nearly every person on the planet, the web has seeped into most aspects of our day-to-day lives. However, this ubiquity comes with an ever-growing need to manage enormous amounts of data, which requires better and better data infrastructure. Back in the Web 1.0 era, we could really only read static content on the internet. A decade later, with Web 2.0, it became possible to read and write on online social networks. Now, with Web 3.0 and the dawn of AI and blockchain, a single person generates around 1.7 MB of data every second. That adds up to approximately 146.88 GB of data per person per day. Such demanding workloads mean that data infrastructure is now mission-critical for most businesses. Modern data infrastructure supports everything from daily operational workloads (OLTP) to strategic decision-making workloads (OLAP).

DRY Your Apache APISIX Config

Aggregated on: 2024-09-06 15:08:09

DRY is an important principle in software development. This post will show you how to apply it to Apache APISIX configuration. The DRY Principle "Don't repeat yourself" (DRY) is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.

Product Vision vs Technical Strategy: Bridging the Product-Engineering Gap

Aggregated on: 2024-09-06 13:08:09

In the world of software engineering, a conflict between a product manager's vision and the engineering team's technical strategy is a recurring obstacle for many teams. While product managers strive to create disruptive and innovative products, engineers need to ensure that these visions can be implemented into successful realities either within the constraints of current technology or discover a breakthrough themselves. The gap between the product vision and the technical realities can be a daunting challenge, but balancing these two aspects is crucial for the success of any project. This article explores the dynamics between product vision and technical reality and how taking an iterative approach can help navigate the gap between the aspect and the feasibility. Understanding the Product Vision Imagine you are a builder (software developer) and are hired by a family (product manager) to build a house. The family will have an image of a dream house in their mind — a beautiful, large, comfortable home that will fulfill all their functional and lifestyle dreams (vision). Now, for the builder to do their job well, they need to understand the family's vision and then build upon it. But at the same time, the family's vision also needs to be well crafted and decipherable for the builder to comprehend it. Along similar lines, a well-defined and well-constructed product vision is essential for guiding a successful technical strategy.

Ember.js vs React.js: Comparing JavaScript Technologies

Aggregated on: 2024-09-05 23:08:08

Frontend technologies are integral to web development as they determine how users interact with a website or app. For this reason, picking the right front-end technology is essential for optimal user engagement and subsequent project success. React.js and Ember.js are among the most popular front-end technologies used in modern web development. Although both fall under the JavaScript umbrella, these technologies differ significantly. In this article, we will compare React.js vs Ember.js and explore their strengths and weaknesses to help you choose the most suitable one for your needs.

Lead a Successful Agile Transformation With the VICTORY Framework

Aggregated on: 2024-09-05 21:08:08

Agile transformations can be tough. They’re messy, time-consuming, and more often than not, they fail to deliver the promises that got everyone excited in the first place. That’s why it’s so important to approach an Agile transformation as a full-scale organizational change rather than just a shift in how our development teams work. In my years as a change management consultant, I have studied and applied various change management models, from John Kotter’s 8-Step Change Model to ADKAR and Lean Change Management by Jason Little. I have learned through these experiences and countless transformations that there isn’t a one-size-fits-all approach.

The AI Security Gap: Protecting Systems in the Age of Generative AI

Aggregated on: 2024-09-05 19:08:08

The rapid adoption of Generative AI (GenAI) and Large Language Models (LLMs) is transforming industries at an unprecedented pace. Nearly 90% of organizations are actively implementing or exploring LLM use cases, eager to harness the power of these revolutionary technologies. However, this enthusiasm is juxtaposed with a concerning lack of security preparedness. A recent GenAI Readiness report by Lakera reveals that only about 5% of organizations are confident in their GenAI security frameworks. This glaring disparity between adoption and security readiness raises a critical question: Is the market prepared for GenAI's potential security risks?

Keeping Two Multi-Master Databases Aligned With a Vector Clock

Aggregated on: 2024-09-05 16:53:08

In today's tech environment, there is a frequent requirement to synchronize applications. This need often arises during technology upgrades, where the goal is to transition a database and its processes from an outdated legacy system to a newer technology. In such scenarios, it's typically required to allow both applications to coexist for a period of time. Sometimes both applications, together with their own databases, must be maintained as masters because dismantling the processes dependent on the legacy one is not viable. Consequently, specific solutions for keeping the two master databases aligned are essential, ensuring that operations on one database are mirrored on the other one, and vice versa. In this article, we discuss a real case we dealt with by abstracting away from several technical details, but focusing on those decisions that shape the structure of our solution.

Setting Up a Data Warehouse for Starlight: A Comprehensive Guide

Aggregated on: 2024-09-05 15:08:08

In the rapidly evolving fintech industry, data is a cornerstone for driving innovation, ensuring compliance, and making informed decisions. For Starlight, a burgeoning fintech company, harnessing the power of data is crucial for maintaining a competitive edge. A data warehouse serves as the backbone for such data-driven initiatives, providing a centralized repository where data from various sources is consolidated, analyzed, and made accessible. A data warehouse is a specialized type of database optimized for analysis and reporting. Unlike traditional databases designed for transactional processing, data warehouses are tailored for query performance and complex analytics. They enable businesses to store vast amounts of historical data, query it efficiently, and derive actionable insights.

How To Set Up Multiple JMS Pods With a Single jmsstore File per Queue in Maximo Application Suites (MAS8)

Aggregated on: 2024-09-05 13:08:08

Problem Statement By default, the IBM Manage JMS setup creates a single JMS store file for all queues, which effectively places all queues in one repository. This approach poses a risk: if one queue becomes corrupt and a message is affected, you would have to delete the store file for all queues to resolve the issue. How To Overcome the Problem We developed a solution to configure the MAS 8 application with a distinct JMS store file for each queue.

Supercharging IaC With AI for Next-Gen Infrastructure Efficiency

Aggregated on: 2024-09-04 21:08:08

In today’s technology landscape, it’s hard to overlook the impact AI is having across nearly every domain. As Infrastructure as Code (IaC) enthusiasts, we’ve been exploring how AI can drive the next evolution of the IaC ecosystem. As we have already seen, AI is playing a significant role in enhancing DevOps and platform capabilities, and it has become clear that AI will be central to the future of IaC practices. Below, we’ll explore some important areas where AI is reshaping IaC operations and discuss what the future may hold.

My Journey With AWS CDK and Java: What You Need To Know

Aggregated on: 2024-09-04 20:08:08

One of the first decisions you’ll need to make when working with the AWS Cloud Development Kit (CDK) is choosing the language for writing your Infrastructure as Code (IaC). The CDK currently supports TypeScript, JavaScript, Python, Java, C#, and Go. Over the past few years, I’ve worked with the CDK in TypeScript, Python, and Java. While there is ample information available online for TypeScript and Python, this post aims to share my experience using Java as the language of choice for the AWS CDK. Wait…What? Use Java With the AWS CDK? Some may say that TypeScript is the most obvious language to use while working with the AWS CDK. The CDK itself is written in TypeScript and it’s also the most used language according to the 2023 CDK Community Survey. Java is coming in 3rd place with a small percentage of use.

Order in Chaos: Python Configuration Management for Enterprise Applications

Aggregated on: 2024-09-04 19:08:08

Importance of Configuration Management In enterprise applications, configuration management is the most underrated operator that keeps everything integrated and running smoothly. It acts as a backstage manager ensuring all lights are in place, theatrical queues are ready, and the show can go on without a hiccup. Especially, while dealing with multi-environment deployments, with tight-knit CI/CD processes, one wrong configuration can pose an application-wide shutdown risk. Multi-environment enterprise applications carry their own set of challenges and managing configs is no exception. We all have heard the famous “But, it was working on my machine!” excuse more times than daily salutations.

Cutting the High Cost of Testing Microservices

Aggregated on: 2024-09-04 18:08:08

A specter is haunting modern development: as our architecture has grown more mature, developer velocity has slowed. A primary cause of lost developer velocity is a decline in testing: in testing speed, accuracy, and reliability. Duplicating environments for microservices has become a common practice in the quest for consistent testing and production setups. However, this approach often incurs significant infrastructure costs that can affect both budget and efficiency. Testing services in isolation isn’t usually effective; we want to test these components together.

Overcoming Alert Fatigue: A Team's Journey to Effective Incident Response

Aggregated on: 2024-09-04 17:08:08

The Night That Changed Everything Remember the days when your phone buzzed more often than a beehive in spring? That was us, drowning in a sea of alerts. Our Slack channels looked like Times Square on New Year's Eve, and our PagerDuty . . . well, let's just say it was living up to its name a little too enthusiastically. We were facing a classic case of alert fatigue, and it wasn't just costing us sleep — it was impacting our ability to respond to real incidents. Something had to give, and it wasn't going to be our sanity.

Mastering Test Automation: How data-testid Can Revolutionize UI Testing

Aggregated on: 2024-09-04 16:23:08

How Can I Implement This Approach? Implementing the data-testid approach in your front-end development process involves several steps, from setting up your project to best practices for using the attribute effectively. Here’s a step-by-step guide on how to implement this approach. Adopt a Testing-First Mindset Plan for Testing Before diving into coding, ensure that testability is a key consideration in your UI component design. Discuss with your team how elements will be tested and where data-testid will be applied.

5 Steps To Integrate Istio With OPA

Aggregated on: 2024-09-04 15:23:08

Authentication and Authorization are big parts of the security puzzle that need to be solved by cloud architects and DevOps engineers. In this blog, we will specifically look at how to achieve authorization/access control; i.e., what actions the authenticated entity can perform in the Istio service mesh. It helps to secure the infrastructure by preventing actions with malicious intent. Authorization in a service mesh can be defined using OPA policies. OPA is a mechanism that helps DevOps folks define and enforce authorization policies for Kubernetes workloads. In this piece, we will see:

A Comprehensive Guide to Access and Secrets Management: From Zero Trust to AI Integration — Innovations in Safeguarding Sensitive Information

Aggregated on: 2024-09-04 14:23:08

Editor's Note: The following is an article written for and published in DZone's 2024 Trend Report, Enterprise Security: Reinforcing Enterprise Application Defense. Access and secrets management involves securing and managing sensitive information such as passwords, API keys, and certificates. In today's cybersecurity landscape, this practice is essential for protecting against breaches, ensuring compliance, and enhancing DevOps and cloud security. By implementing effective secrets management, organizations can reduce risk, improve operational efficiency, and respond to incidents more quickly. For developers, it provides a secure, convenient, and collaborative way to handle sensitive information, allowing them to focus on coding without worrying about the complexities of secure secrets handling.

How To Conduct Effective Data Security Audits for Big Data Systems

Aggregated on: 2024-09-04 13:23:08

Big data systems are an increasingly common aspect of many business operations. As helpful as such a wealth of information is, these projects can dramatically impact an organization’s cybersecurity posture. Consequently, any company embracing this trend must also embrace the big data security audit. Why Big Data Security Audits Are Necessary The sheer size of big data necessitates proactive cybersecurity. Global volumes could reach 181 zettabytes by 2025, leaving businesses with massive amounts of information to safeguard. Failing to secure big data systems could expose countless consumers’ personal details to cybercriminals, incurring significant costs.

MLOps: How To Build a Toolkit To Boost AI Project Performance

Aggregated on: 2024-09-03 22:23:07

Numerous AI projects launched with promise fail to set sail. This is not usually because of the quality of the machine learning (ML) models. Poor implementation and system integration sink 90% of projects. Organizations can save their AI endeavors. They should adopt adequate MLOps practices and choose the right set of tools. This article discusses MLOps practices and tools that can save sinking AI projects and boost robust ones, potentially doubling project launch speed. MLOps in a Nutshell MLOps is a mix of machine learning application development (Dev) and operational activities (Ops). It is a set of practices that helps automate and streamline the deployment of ML models. As a result, the entire ML lifecycle becomes standardized.

Implementing an IaC Platform With Terraform, Ansible, and GitLab

Aggregated on: 2024-09-03 21:23:07

Given the need to create infrastructure across multiple environments while ensuring standardization and effective monitoring, it becomes crucial to provision these environments securely. To achieve this, adopting an immutable infrastructure approach, where environments are provisioned as code, is essential. The purpose of this article is to demonstrate a possible approach to achieving this by using GitLab’s structures to enforce templates and standards, Terraform to apply and maintain standards across servers, and Ansible for software provisioning and configuration, utilizing a shared roles model across repositories. To manage the state of machines with Terraform, we use MinIO, as it enables this implementation on-premises.

How We Optimized Read Performance: Readahead, Prefetch, and Cache

Aggregated on: 2024-09-03 20:23:07

High-performance computing systems often use all-flash architectures and kernel-mode parallel file systems to satisfy performance demands. However, the increasing sizes of both data volumes and distributed system clusters raise significant cost challenges for all-flash storage and vast operational challenges for kernel clients. JuiceFS is a cloud-native distributed file system that operates entirely in user space. It improves I/O throughput substantially through the distributed cache and uses cost-effective object storage for data storage. It’s hence suitable for serving large-scale AI workloads.

Automating Cucumber Data Table to Java Object Mapping in Your Cucumber Tests

Aggregated on: 2024-09-03 19:23:07

As a Java developer, using Cucumber for Behavior-Driven Development (BDD) can be a great way to ensure that your code meets business requirements by writing tests in plain language. One of the most powerful features of Cucumber is the ability to use Data Tables in feature files. However, manually mapping these tables to Java objects can be repetitive and error-prone. To streamline this process, the library cucumber-datatable-to-bean-mapping aims to automatically map Cucumber Data Tables to Java objects. In this article, I will walk you through the library's functionality and how you can easily integrate it into your Cucumber projects to save time and reduce boilerplate code.

Configuring a Connection Pool

Aggregated on: 2024-09-03 18:23:07

A connection pooler is a software component that manages database connections. This can help in multiple ways to improve resource utilization, help with load balancing or failover, and can greatly reduce transaction times. In this blog post, we’re going to see what a connection pooler is and how to configure it. What a Connection Pooler Is and Why It’s Useful Opening a connection to the database takes many steps. We need to connect to the server and perform the initial handshake, agree on the encryption and connection settings, and then keep the new connection resource across all the layers (network driver, OS layer, database layer, etc.). Each connection consumes memory which size depends on the database engine. For PostgreSQL, this can be even 1.3MB of memory for one connection. Opening a connection also takes time as we need to negotiate the settings of the new connection.

Open Standards for Data Lineage: OpenLineage for Batch and Streaming

Aggregated on: 2024-09-03 17:23:07

One of the greatest wishes of companies is end-to-end visibility in their operational and analytical workflows. Where does data come from? Where does it go? To whom am I giving access to? How can I track data quality issues? The capability to follow the data flow to answer these questions is called data lineage. This blog post explores market trends, efforts to provide an open standard with OpenLineage, and how data governance solutions from vendors such as IBM, Google, Confluent, and Collibra help fulfill the enterprise-wide data governance needs of most companies, including data streaming technologies such as Apache Kafka and Flink. What Is Data Governance? Data governance refers to the overall management of the availability, usability, integrity, and security of data used in an organization. It involves establishing processes, roles, policies, standards, and metrics to ensure that data is properly managed throughout its lifecycle. Data governance aims to ensure that data is accurate, consistent, secure, and compliant with regulatory requirements and organizational policies. It encompasses activities such as data quality management, data security, metadata management, and compliance with data-related regulations and standards.