News Aggregator

Top Methods to Improve ETL Performance Using SSIS

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

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

How to Set Up Redis Properties Programmatically

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

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

STRIDE: A Guide to Threat Modeling and Secure Implementation

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

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

Micronaut vs Spring Boot: A Detailed Comparison

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

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

Handling Embedded Data in NoSQL With Java

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

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

The Outbox Pattern: Reliable Messaging in Distributed Systems

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

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

Efficient Multimodal Data Processing: A Technical Deep Dive

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

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

Cloud-Driven Analytics Solution Strategy in Healthcare

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

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

Networking in DevOps: Your Beginner Guide

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

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

Banking Fraud Prevention With DeepSeek AI and AI Explainability

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

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

Identity and Access Management Solution to Safeguard LLMs

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

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

How to Scale Elasticsearch to Solve Your Scalability Issues

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

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

AI-Powered Professor Rating Assistant With RAG and Pinecone

Aggregated on: 2025-02-26 19:27:59

Artificial intelligence is transforming how people interact with information, and retrieval-augmented generation (RAG) is at the forefront of this innovation. RAG enhances large language models by enabling access to external knowledge bases, providing highly accurate and context-aware answers. In this tutorial, I’ll guide you through building an AI-powered assistant using RAG to create a smarter, more informed system for rating professors. Using tools like Next.js, React, Pinecone, and OpenAI’s API, this project is designed to be approachable for all, whether you’re just starting or already have experience in AI.

A Platform-Agnostic Approach in Cloud Security

Aggregated on: 2025-02-26 18:27:59

Companies are now turning to data as one of the most important assets in their businesses, and data engineers are in the midst of managing and improving this asset and its effectiveness. In addition, the integration of data engineering with the use of cloud computing offers scalability, accessibility, and reduced expenses. However, there are security challenges that come with this integration that need to be solved. It is essential to know the rates and causes of cloud security incidents in order to identify the vulnerabilities of the cloud systems. The cost of security incidents in businesses has shockingly increased to 61% in 2024 from the previous year’s 24%.

10 Best Practices for Managing Kubernetes at Scale

Aggregated on: 2025-02-26 17:42:59

As organizations use microservices and cloud-native architectures, Kubernetes is becoming the norm for container orchestration. As much as Kubernetes simplifies deploying and managing containers, workloads at scale make life complex, and robust practices are necessary. In this article, I will cover technical strategies and best practices for workload management at scale in Kubernetes.

PostgreSQL 12 End of Life: What to Know and How to Prepare

Aggregated on: 2025-02-26 16:42:59

Amazon Aurora PostgreSQL-compatible edition major version 12.x and Amazon RDS for PostgreSQL 12 reach the end of standard support on February 28, 2025. Higher database versions introduce new features, enhancing operational efficiency and cost-effectiveness. Identifying qualified databases and upgrading them promptly is crucial. As the end of standard support is approaching, it's crucial for database administrators and developers to understand the implications and plan for the future. This article discusses PostgreSQL 12's end-of-standard support for Aurora and RDS PostgreSQL 12, Amazon RDS extended support, upgrade options, and the benefits of moving to PostgreSQL 16.

A Step-by-Step Guide to Write a System Design Document

Aggregated on: 2025-02-26 15:27:59

Have you ever wondered how large-scale systems handle millions of requests seamlessly while ensuring speed, reliability, and scalability? Behind every high-performing application — whether it’s a search engine, an e-commerce platform, or a real-time messaging service — lies a well-thought-out system design. Without it, applications would struggle with bottlenecks, downtimes, and an overall poor user experience. System design is more than just structuring components; it's about anticipating future needs, balancing trade-offs, and building a solution that can scale gracefully under heavy loads. In this blog, we’ll explore a structured approach to system design using a proven template that can help engineers, architects, and teams craft efficient, high-performing systems.

Annotating Data at Scale in Real Time

Aggregated on: 2025-02-26 14:27:59

As enterprises deal with large datasets, the demand for high-quality annotations has increased exponentially. Annotating data at a petabyte scale and in real time introduces unique challenges that require creative solutions. This article discusses the architecture for real-time annotation pipelines, leveraging LLMs, feedback loops, and active learning. Challenges in Scaling Data Annotation Volume Petabyte-scale datasets often involve millions of entries spanning diverse modalities, including text, images, and videos. Efficiently handling this scale requires:

AI-Powered Ransomware Attacks

Aggregated on: 2025-02-26 13:27:59

The improvement of artificial brainpower (artificial intelligence) has improved many fields, including digital protection. Notwithstanding, this mechanical improvement is a two-sided deal. While computerized reasoning brings many advantages, it also empowers cybercriminals to send off progressively complex and disastrous assaults. One of the most upsetting viewpoints is using AI in ransomware assaults. These AI-controlled assaults are robotized at different levels and find unpretentious procedures to make them greener, more complex, and more impressive. Most importantly, the danger scene quickly develops, creating more difficulties for people and associations.

Driving Developer Advocacy and Satisfaction: Developer Experience Initiatives Need Developer Advocacy to Be Successful

Aggregated on: 2025-02-26 12:27:59

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. Developer experience has become a topic of interest in organizations over the last few years. In general, it is always nice to know that organizations are worrying about the experience of their employees, but in a market economy, there is probably more to it than just the goodwill of the C-suite. If we take a step back and consider that many organizations have come to terms with the importance of software for their business' success, it is clear that developers are critical employees not just for software companies but for every organization. It is as Satya Nadella famously stated:

Non-Human Identity Security in the Age of AI

Aggregated on: 2025-02-25 22:42:59

It is not a coincidence that non-human identities (NHIs) have come into focus recently while AI-powered tools and autonomous agents are rapidly being adopted. In fact, this is partially what is driving the explosion of NHIs in the enterprise. This has sparked a lot of research and conversations about machine identity and governance. Like human users of systems, NHIs, such as AI agents, bots, scripts, and cloud workloads, operate using secrets. These credentials grant access to sensitive systems and data. They can take many forms and must always be accounted for, from creation to offboarding. Unlike humans, machines can't use multifactor authentication or passkeys, and developers can generate hundreds of these credentials through their work deploying applications.

How Generative AI Is Revolutionizing Cloud Operations

Aggregated on: 2025-02-25 21:12:59

LLMs have made it possible to operate cloud services more effectively and cheaply than ever before. They can assimilate natural language and code, enabling new preventative and remediatory tools. Language models are improving at a breakneck velocity. As the models get better, services that have integrated them into their operations will reap the benefits for free. We explore the most compelling applications in this article, many of which are already being deployed at top tech companies.

Spring Framework or Hibernate, Which One Is Better?

Aggregated on: 2025-02-25 20:12:59

In modern software or website development processes, Java frameworks are widely used as they make it easy to build dynamic apps and websites. Moreover, in 2023, the value of the Java frameworks software market was USD 3,982.40 million. Furthermore, it is forecasted to reach USD 9,049.22 million by 2030. This proves the significance of using Java frameworks such as Grails, Google Web Toolkit (GWT), Quarkus, and not to mention the Hibernate and Spring frameworks.

Spark Job Optimization

Aggregated on: 2025-02-25 19:12:59

We are living in an age where data is of utmost importance, be it analysis or reporting, training data for LLM models, etc. The amount of data we capture in any field is increasing exponentially, which requires a technology that can process large amounts of data in a short duration. One such technology would be Apache Spark. Apache Spark is a cluster-based architecture that can be accessed in different flavors like Python, Scala, Java, and Spark SQL, which would make it versatile and easy to fit into most applications.

Protecting Critical Infrastructure From Ransomware

Aggregated on: 2025-02-25 18:42:59

Safeguarding critical infrastructure from ransomware has become a critical issue in today's interconnected world. Regions, for instance, power clinical benefits and government face extending perils that could disturb supplies, impact fragile data, and cause essential financial and reputational hurt. Ransomware attacks planned to pressure portions by encoding significant information highlight the sincere necessity for solid organization insurance strategies. This plan examines necessary techniques to defend against ransomware in critical infrastructure, focusing on proactive specific gatekeepers and a solid procedure framework. By grasping the attack and completing comprehensive protections, associations can lessen the chance and ensure the adaptability of critical infrastructure against advanced risks.

The Future of Data Lakehouses: Apache Iceberg Explained

Aggregated on: 2025-02-25 17:12:59

We know that data management today is changing completely. For decades, businesses relied on data warehouses, which stored information in an appropriate manner. They are structured, governed, and quick to extract information from, although expensive and rigid in nature. In contrast, data lakes are more efficient and allow for the storage of enormous amounts of data regardless of structure. However, the emergence of the data lakehouse architecture combines the benefits of the data lakes and data warehouses. Lakehouse models allow the retention of the flexibility provided by data lakes while integrating the reliability, governance, and performance of a data warehouse. The most notable open-source table format created for large-scale data analytics is Apache Iceberg. Iceberg is at the forefront of this transformation and enhances the value of data in the lakehouse architecture. Additionally, Iceberg provides solutions for many of the problems that data lakes face, including schema evolution, ACID transactions, data consistency, and query performance.

The Hidden Cost of Dirty Data in AI Development

Aggregated on: 2025-02-25 16:12:59

Artificial intelligence operates as a transformative force that transforms various industries, including healthcare, together with finance and all other sectors. AI systems achieve their highest performance through data that has been properly prepared for training purposes. AI success depends on high-quality data because inaccurate all-inclusive or duplicated data or conflicting records lead to both diminished performance and higher operational costs, biased decisions, and flawed insights. AI developers understate the true impact of dirty data-related expenses because these factors directly affect business performance levels together with user trust and project achievement. The Financial Burden of Poor Data Quality The financial costs represent one direct expense related to using dirty data during AI development processes. Organizations that depend on AI systems for decision automation need to budget sizable expenses toward cleaning data, preparing it for processing, and validating existing datasets. Studies show poor data quality annually creates millions of dollars of financial losses through several efficiency issues, prediction mistakes, and resource ineffectiveness. Faulty data that train AI models sometimes leads businesses to make mistakes involving resource wastage and incorrect targeting of customers, followed by incorrect healthcare diagnoses of patients.

Integrating AI Agent Workflows in the SOC

Aggregated on: 2025-02-25 15:12:58

Defending against zero- to low-cost attacks generated by threat actors (TA) is becoming increasingly complex as they leverage sophisticated generative AI-enabled infrastructure. TAs try to use AI tools in their attack planning to make social engineering schemes, convincing phishing emails, deepfake videos, different types of malware, and many other types of attack vectors. A potential solution to defend against these challenges is to enable the use of GenAI and AI agents in the Security Operations Center (SOC). An orchestrated workflow with a team of AI agents presents an opportunity for better response. In traditional detection and response, detections are not easily achieved, and manual responses cannot match the required machine-level speed. To avoid burnout and alert fatigue of SOC analysts, a shift in the SOC strategy is required by automating routine tasks using AI agents.

Redefining Developer Productivity: Balancing Data and Human Experience in Developer Success Measurements

Aggregated on: 2025-02-25 14:12:58

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. Delivering production-ready software tools requires focusing on developer productivity measured by qualitative and quantitative metrics. To understand developer productivity, this article focuses on three elements:

Simplifying Multi-LLM Integration With KubeMQ

Aggregated on: 2025-02-25 13:27:58

Integrating multiple large language models (LLMs) like OpenAI and Anthropic's Claude into applications can be a daunting task. The complexities of handling different APIs and communication protocols and ensuring efficient routing of requests can introduce significant challenges. But using a message broker and router can be an elegant solution to this problem, addressing these pain points and providing several key advantages.

A Comprehensive Guide to IAM in Object Storage

Aggregated on: 2025-02-25 12:27:58

Identity and access management (IAM), service IDs, and service credentials are crucial components in securing and managing access to object storage services across various cloud platforms. These elements work together to provide a robust framework for controlling who can access data stored in the cloud and what actions they can perform. In the previous article, you were introduced to the top tools for object storage and data management. In this article, you will learn how to restrict access (read-only) to the object storage bucket through custom roles, access groups, and service credentials.

Codify Your Cloud and Kubernetes With Crossplane and IaC

Aggregated on: 2025-02-24 22:42:58

As organizations embrace Kubernetes for cloud-native applications, managing infrastructure efficiently becomes challenging. Traditional Infrastructure as Code (IaC) tools like Terraform, Pulumi, and others provide declarative configurations but lack seamless integration into the Kubernetes-native workflows. Crossplane effectively bridges the gap between Kubernetes and cloud infrastructure in this situation. In this blog, we’ll explore how Crossplane enables IaC for Kubernetes and beyond.

Use Azure Cosmos DB as a Docker Container in CI/CD Pipelines

Aggregated on: 2025-02-24 21:42:58

There are many benefits to using Docker containers in CI/CD pipelines, especially for stateful systems like databases. For example, when you run integration tests, each CI job can start the database in an isolated container with a clean state, preventing conflicts between tests. This results in a testing environment that is reliable, consistent, and cost-effective. This approach also reduces latency and improves the overall performance of the CI/CD pipeline because the database is locally accessible. The Linux-based Azure Cosmos DB emulator is available as a Docker container and can run on a variety of platforms, including ARM64 architectures like Apple Silicon. It allows local development and testing of applications without needing an Azure subscription or incurring service costs. You can easily run it as a Docker container and use it for local development and testing:

Tips to Choose the Right SQL Database

Aggregated on: 2025-02-24 20:27:58

It’s the same in the world of data, where choosing the right SQL database can make or break your organization’s success. With several options available, database selection is a crucial decision that can shape the performance, scalability and efficiency of your data platform. Finding the perfect fit for your specific needs requires careful consideration of various factors and taking time to understand different database types. This article guides you through the process of selecting a SQL database. We'll explore the main types of SQL databases, discuss key factors to consider when making your choice, and take a look at some popular options in the market. By the end, you'll have a clearer picture of how to pick a database that aligns with your project requirements and business goals — setting you up for better data management and analysis.

How to Integrate Platform Engineering Into Your Business

Aggregated on: 2025-02-24 19:27:58

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. How do we even start approaching platform engineering? The good news is that major organizations that have successfully adopted platform engineering have contributed their insights, best practices, and lessons learned to frameworks like the Cloud Native Computing Foundation's (CNCF) Platform Maturity Model and Microsoft's Platform Engineering Capability Model. These models provide a structured pathway for organizations to evaluate their current state and identify gaps and actionable steps toward building an effective internal developer platform (IDP).

API Mesh: The Next Big Leap in Distributed Backend Systems

Aggregated on: 2025-02-24 18:27:58

API Mesh simplifies API management across distributed systems by providing a unified layer for orchestration, security, and observability. In this article, we’ll explore the intricacies of API Mesh, its unique capabilities, and how it is set to redefine how businesses manage their APIs. Understanding API Mesh To understand the value of an API Mesh, we first need to distinguish it from other tools like API gateways and service meshes:

The Perceptron Algorithm and the Kernel Trick

Aggregated on: 2025-02-24 17:12:58

The Perceptron Algorithm is one of the earliest and most influential machine learning models, forming the foundation for modern neural networks and support vector machines (SVMs). Proposed by Frank Rosenblatt in 1958 (Rosenblatt, 1958), the perceptron is a simple yet powerful linear classifier designed for binary classification tasks. Despite its simplicity, the perceptron introduced key concepts that remain central to machine learning today, such as iterative weight updates, the use of activation functions, and learning a decision boundary (Goodfellow, Bengio & Courville, 2016). These ideas have directly influenced the development of multi-layer neural networks by introducing weight adjustment rules that underpin backpropagation (LeCun, Bengio & Hinton, 2015).

Rust vs Python: Differences and Ideal Use Cases

Aggregated on: 2025-02-24 16:42:58

Rust and Python are widely used programming languages in software development and data science. Rust’s adoption has grown significantly in recent years, leaving many wondering if it will eventually replace Python as a top programming language. Compared to Python, Rust is a newbie but is making its mark among developers. According to the StackOverflow Developer Survey, Python is preferred over Rust, but in some cases, Rust is better. To better understand which one to choose, this article walks you through both languages' features, what makes them different, and how they fit into specific projects.

Mastering Redirects With Cloudflare Bulk Redirects

Aggregated on: 2025-02-24 15:27:58

Problem Statement Controlling numerous URL redirects in IIS Manager operating on Windows Server systems proves difficult because it requires extended work time. When redirect rules within the IIS interface and web.config file require manual configuration, their management becomes more complicated due to the growing number of redirects. Website migrations and site restructurings lead to this particular challenge since teams need to maintain multiple redirects numbering in the dozens and potentially even hundreds. The end result of manual processing methods creates slower operations followed by elevated possibilities of long-term configuration mistakes and human errors. Multiple team members working with the web.config file for editing encounters complicated backup and version control challenges because of repeated edits.

Simplify Your Compliance With Google Cloud Assured Workloads

Aggregated on: 2025-02-24 14:42:58

To navigate the complex world of cloud compliance, Google Cloud provides a tool, Google Cloud Assured Workloads, that helps organizations create a secure and compliant environment to run their workloads in Google Cloud. It helps organizations enforce strict data residency controls that restrict the resources to run only in specific Google Cloud Regions. Assured Workloads Monitoring and Auditing helps organizations identify compliance policy violations in the Google Cloud environment. Additionally, Assured Support gives organizations control over their support experience. Organizations can decide who can access their data and restrict support personnel’s data access based on their location.

How to Quarantine a Malicious File in Java

Aggregated on: 2025-02-24 13:27:58

Scanning file uploads for viruses, malware, and other threats is standard practice in any application that processes files from an external source. No matter which antimalware we use, the goal is always the same: to prevent malicious executables from reaching a downstream user (directly, via database storage, etc.) or automated workflow that might inadvertently execute the malicious content.

Build a Local AI-Powered Document Summarization Tool

Aggregated on: 2025-02-24 12:42:58

When I began my journey into the field of AI and large language models (LLMs), my initial aim was to experiment with various models and learn about their effectiveness. Like most developers, I also began using cloud-hosted services, enticed by the ease of quick setup and availability of ready-to-use LLMs at my fingertips. But pretty quickly, I ran into a snag: cost. It is convenient to use LLMs in the cloud, but the pay-per-token model can suddenly get really expensive, especially when working with lots of text or asking many questions. It made me realize I needed a better way to learn and experiment with AI without blowing my budget. This is where Ollama came in, and it offered a rather interesting solution.

Beating the 100-Scheduled-Job Limit in Salesforce

Aggregated on: 2025-02-21 22:42:44

Salesforce’s 100-scheduled-job limit can sneak up on you when your org scales. You might think 100 scheduled jobs sounds like plenty — until various business units need daily batch runs, monthly triggers, specialized reporting tasks, and more. Suddenly, you’re stuck trying to figure out how to add more time-based processes without hitting that cap. To tackle this, I designed a dynamic scheduling framework that consolidates multiple jobs into just one. Instead of scheduling every single job separately, we rely on custom settings to instruct a “master” scheduled job which tasks to run and when.

Designing a Blog Application Using Document Databases

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

Let’s say you’re building a blog website. On the homepage, you need to display a list of the 10 most recent posts, with pagination allowing users to view older posts. When a user clicks on a post, they should see its content along with metadata, such as the author’s name and the creation date. Each post also supports comments, so at the bottom of a post, you’ll display the five earliest comments with an option to load more.

Controlling Access to Google BigQuery Data

Aggregated on: 2025-02-21 20:42:44

Google BigQuery, Google Cloud's data warehouse, provides a comprehensive suite of tools to help you control who can access your valuable data and what they can do with it. This blog post dives into the essential principles and practical techniques for managing data access in BigQuery and covers everything from basic Identity and Access Management (IAM) to more advanced features like authorized datasets, views, routines, and materialized views. We'll guide you through setting up granular permissions, ensuring your data remains secure and accessible only to authorized individuals and services. This guide will equip you with the knowledge you need to take control of your BigQuery data.

Hexagonal Architecture: A Lyrics App Example Using Java

Aggregated on: 2025-02-21 19:42:44

This architecture principle was created by Alistair Cockburn in 2005. This is one of the many forms of Domain-Driven Design (DDD) Architecture. The goal was to find a way to solve or otherwise mitigate general caveats introduced by object-oriented programming. This is also known as the Ports and Adapters Architecture. The hexagon concept isn’t related to a six-side architecture, nor does it have anything to do with the geometrical form. A hexagon has six sides indeed, but the idea is to illustrate the concept of many ports.

A Comprehensive Guide to Generative AI Training

Aggregated on: 2025-02-21 19:12:44

Large language models (LLMs) have impacted natural language processing (NLP) by introducing advanced applications such as text generation, summarization, and conversational AI. Models like ChatGPT use a specific neural architecture called a transformer to predict the next word in a sequence, learning from enormous text datasets through self-attention mechanisms. This guide breaks down the step-by-step process for training generative AI models, including pre-training, fine-tuning, alignment, and practical considerations.

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.