News Aggregator

TFVC to Git Migration: Step-by-Step Guide for Modern DevOps Teams

Aggregated on: 2025-06-06 14:58:09

The Challenge Our organization has maintained a large monolithic codebase in Team Foundation Version Control (TFVC) for over a decade. As development velocity has increased and teams have moved toward agile methodologies, microservices, and cloud-native architectures, the limitations of TFVC have become increasingly apparent. The centralized version control model hinders collaboration, branching, and automation, and our existing classic build and release pipelines in TFS are tightly coupled with legacy tooling that no longer aligns with modern DevOps practices. We have observed significant bottlenecks in:

Guide to Optimizing Your Snowflake Data Warehouse for Performance, Cost Efficiency, and Scalability

Aggregated on: 2025-06-06 14:58:09

Optimizing a Snowflake data warehouse (DWH) is crucial for ensuring high performance, cost-efficiency, and long-term effectiveness in data processing and analytics. The following outlines the key reasons optimization is essential: Performance Optimization Why It's Important Query Speed: As data volumes grow, unoptimized queries can slow down performance, resulting in longer execution times and poor user experience. Optimization helps speed up query execution, delivering quicker insights.

How to Identify the Underlying Causes of Connection Timeout Errors for MongoDB With Java

Aggregated on: 2025-06-06 14:58:09

Java developers and MongoDB are like Aladdin and the Genie from Arabian Nights. Developers rub the lamp with their wildest NoSQL wishes, and MongoDB swoops in, granting Spring Boot microservices and REST APIs the magic they need to soar. But every so often, a Jafar-like menace swoops in, forcing our Aladdin (Java devs) to wrestle with sleepless nights. One such villainous foe is the connection timeout, locking APIs in a cave of wonders with no escape, leaving developers yearning for a magic carpet fix. So, what’s a connection timeout error? Imagine Aladdin, the developer, sending Abu, his trusty monkey, to fetch a shiny treasure—data—from MongoDB’s palace vault. Abu’s got 30 seconds to scamper over and back. But if the palace is packed with guards (server overload), the gates are jammed shut (network issues), or Abu’s running to the wrong hideout (bad address), and he doesn’t make it in time. That’s a timeout: MongoClient can’t grab the data, the mission fails, and your app’s stuck with a MongoTimeoutException, leaving your API as empty-handed as Aladdin without his loot. In simple terms, it’s when your MongoClient—the trusty bridge between your Java app and MongoDB—can’t reach the server before the clock runs out.

When Caching Goes Wrong: How One Misconfigured Cache Took Down an Entire System

Aggregated on: 2025-06-06 14:58:09

Caching is a cornerstone of modern software architecture. By temporarily storing frequently accessed data in fast storage (memory or dedicated cache servers), applications can serve repeated requests quickly without hitting slower back-end systems each time. In high-traffic systems, caching dramatically reduces database load and improves response times. A well-tuned cache can be the difference between a snappy user experience and a sluggish one. However, caching is a double-edged sword. When configured correctly, it accelerates performance and enables systems to scale. But if something goes wrong in the cache layer—a subtle bug or misconfiguration—the consequences can ripple throughout the entire stack. In this case study, we’ll explore a fictional scenario where a single misconfigured cache brought down an entire system, illustrating how critical caching is and how easily it can become a single point of failure.

How I Built an AI Portal for Document Q and A, Summarization, Transcription, Translation, and Extraction

Aggregated on: 2025-06-06 14:58:09

These days, AI is everywhere, but most people at work are still stuck using a mix of disconnected tools. Some folks use a chatbot here, someone else copies text into a summarizer there, and there’s always a messy process to get meeting recordings transcribed or translated. It’s kind of a headache. I kept hearing the same complaints from my team: “Why can’t all of this just be in one place?”

Revolutionizing Software Development: Agile, Shift-Left, and Cybersecurity Integration

Aggregated on: 2025-06-06 14:58:09

Software development evolved dramatically since the days of waterfall project management. Today, reliability and security are more prominent in product expectations—usable, secure, and defect-free software is the gold standard. The shift-left Agile approach addresses these concerns by facilitating quicker turnaround times, incremental deliverables, more frequent client input, and higher success rates. In a typical Agile workflow, teams start the planning and development process on the left and move to the right as a project enters production. Where security and quality assurance were introduced later in the process, shift-left leverages Agile practices to include testing for bugs at the earliest planning and development stages. This approach reduces the likeliness of significant flaws and vulnerabilities entering the production phase and eventually being shipped out to customers. Shift-left addresses concerns as they arise with early testing and automation, facilitating smoother and faster integration and deployment. In a successful shift-left scenario, software quality is high, automation is effective, and customer experience is improved.

Enhancing SQL Server Security With AI-Driven Anomaly Detection

Aggregated on: 2025-06-06 14:58:09

As SQL Server databases become increasingly targeted by cybercriminals, it's crucial to adopt proactive security measures. Traditional database security mechanisms, such as access controls, role-based permissions, and firewalls, are important but may not be sufficient to detect advanced threats or malicious insider activities. In this tutorial, we’ll show you how to integrate AI-powered anomaly detection to enhance the security of your SQL Server environment. Using machine learning, this system can identify suspicious activity, unauthorized access, and potential breaches in real-time, providing an additional layer of defense. We’ll walk through the process of collecting data, building the model, integrating it into SQL Server, and deploying it for ongoing threat detection.

Zero-Latency Architecture: Database Triggers + Serverless Functions for Modern Reactive Architectures

Aggregated on: 2025-06-06 14:58:09

After working on several cloud-native applications over the past few years, I've found that one of the most impactful architectural patterns combines database triggers with serverless functions. This approach has consistently delivered benefits in terms of scalability, cost efficiency, and development speed across various projects. In this article, I'll share practical insights from implementing these patterns across different cloud providers, along with specific use cases and lessons learned from real-world deployments.

How I Supercharged My GenAI App and Saved My Sanity

Aggregated on: 2025-06-06 14:58:09

Did you ever feel like working with Redshift is like being stuck in a never-ending queue at Starbucks during morning rush hour? Everyone’s waiting, getting cranky, and you’re hoping that your simplest request get processed before you’re next birthday! After spending years working with various data warehousing solutions, I recently made a rather unconventional choice that I am excited to share. I switched from Amazon Redshift to DuckDB for my real-time GenAI application, and the results were eye-opening.

Supercharge Your Java Apps With AI: A Practical Tutorial

Aggregated on: 2025-06-06 14:58:09

Artificial intelligence (AI) offers great potential for software applications by providing options like natural language processing, image recognition, and predictive analysis, which can be integrated within software. This tutorial aims to empower developers to unlock advanced functionalities by providing a blend of theoretical insights and practical, code-centric examples, allowing for seamless integration of AI in their Java applications.

Master SQL Performance Optimization: Step-by-Step Techniques With Case Studies

Aggregated on: 2025-06-06 14:58:09

Optimizing SQL queries is essential for ensuring efficient database performance, especially as data volumes continue to grow. Slow queries can lead to sluggish applications and a poor user experience. This article delves into various strategies for optimizing SQL queries, highlighting common pitfalls, best practices, advanced techniques, and real-world case studies to illustrate effective optimization methods. Today, the exponential growth of information necessitates efficient SQL query performance. Slow database queries can degrade application responsiveness, leading to user dissatisfaction and potential revenue loss.

From Monolith to Containers: Real-World Migration Blueprint

Aggregated on: 2025-06-06 14:58:09

Over the years, I’ve worked on several enterprise applications that started out as monoliths. Initially, these systems worked beautifully. Everything was packaged in a single codebase, deployment was straightforward, and communication between components was simple and efficient. But as user demand grew and development teams expanded, these same applications began to show signs of strain. Release cycles slowed, onboarding became painful, and scaling even a small feature required far too much coordination. That’s when the containerization journey began. This article is a real-world blueprint drawn from experience. It’s not just a checklist, but a practical migration story that walks through the exact stages I follow while moving from a monolith to containers. I’ll also reflect on the challenges and insights I’ve picked up along the way.

Building AI Agents With Python, LangChain, and GPT APIs

Aggregated on: 2025-06-06 14:58:09

Artificial intelligence (AI) research has made it possible to develop autonomous AI agents that are capable of performing complex tasks with minimal or no human intervention. LangChain and OpenAI GPT APIs facilitate the development of such agents, and problem-solving and creativity are the responsibility of the developers. In this tutorial, I will cover how to use Python, LangChain, and OpenAI GPT APIs in developing successful AI agents. Autonomous AI agents have key contextual comprehension, enabling them to respond to inputs and act accordingly. The decision-making ability is reason-based, and they learn and select the best one.

Managing Encrypted Aurora DAS Over Kinesis With AWS SDK

Aggregated on: 2025-06-06 14:58:09

When it comes to auditing and monitoring database activity, Amazon Aurora's Database Activity Stream (DAS) provides a secure and near real-time stream of database activity. By default, DAS encrypts all data in transit using AWS Key Management Service (KMS) with a customer-managed key (CMK) and streams this encrypted data into a Serverless Streaming Data Service - Amazon Kinesis. While this is great for compliance and security, reading and interpreting the encrypted data stream requires additional effort — particularly if you're building custom analytics, alerting, or logging solutions. This article walks you through how to read the encrypted Aurora DAS records from Kinesis using the AWS Encryption SDK.

The Rise of Vibe Coding: Innovation at the Cost of Security

Aggregated on: 2025-06-06 14:58:09

Software development teams and professionals are increasingly adopting vibe coding as their preferred approach. Vibe coding involves creating software through instinctual coding methods and minimal planning to achieve quick prototyping or making solutions work immediately. While vibe coding can spark creativity and speed up early development, it usually comes at the cost of security, maintainability, and reliability. This article analyzes the security vulnerabilities of vibe coding and provides essential guidance for developers and organizations to minimize these risks while preserving innovative processes.

OTel Me Why: The Case for OpenTelemetry Beyond the Shine

Aggregated on: 2025-06-06 14:58:09

My blog on pricing from the other day caught the attention of the folks over at MetricFire, and we struck up a conversation about some of the ideas, ideals, and challenges swirling around monitoring, observability, and its place in the broader IT landscape. At one point, JJ, the lead engineer, asked, “You blogged about gearing up to get a certification in Open Telemetry. What is it about OTel that has you so excited?”

Privacy-Preserving AI: How Multimodal Models Are Changing Data Security

Aggregated on: 2025-06-06 14:58:09

Ever had that feeling that your phone is listening to you? You mention something random in conversation, and suddenly you're bombarded with ads about it. Creepy, right? Privacy concerns surrounding AI have always been there. But something fascinating is happening that most techies aren't talking about yet: multimodal AI models are actually starting to improve privacy, not just threaten it.

Automating Kubernetes RBAC Sync With LDAP Entitlements Using Python

Aggregated on: 2025-06-06 14:58:09

In enterprise Kubernetes environments, particularly those supporting data science and analytics teams, managing namespace access becomes increasingly complex as user roles and responsibilities evolve. Teams often rely on centralized identity platforms like LDAP or Active Directory, where group entitlements define access rights. However, Kubernetes lacks native integration with LDAP, which forces teams to maintain RoleBindings manually — a tedious, error-prone, and unscalable process. This exact challenge emerged in our organization, where dozens of data scientists and engineers needed timely, accurate access to shared Kubernetes namespaces. We were stuck managing access through a manual process involving support tickets, group membership checks, and handcrafted YAML RoleBindings. It was slow, insecure, and operationally painful.

Maximizing Cloud Cost Efficiency: Intelligent Management of Non-Production Environments

Aggregated on: 2025-06-06 14:58:09

In the fast-paced world of cloud computing, organizations continually seek ways to optimize their infrastructure spending. One of the most overlooked areas of potential cost savings lies in non-production environments, specifically the development, staging, and testing landscapes. Organizations transitioning to the cloud often carry over habits from traditional data centers, where maintaining multiple environments had minimal cost. This mindset persists despite the different cost dynamics in cloud environments. There are also misconceptions about resource management. For instance, many believe databases can't be stopped without risking data loss. However, modern cloud technologies allow for efficient start-stop operations, state persistence, and rapid environment restoration. Unlike mission-critical production infrastructure that requires constant availability, non-production environments can be dynamically managed with minimal friction and maximum cost efficiency.

The Synergy of Security and Development: Integrating Threat Models With DevOps

Aggregated on: 2025-06-06 14:58:09

In our digital-first world, security isn't just important — it's non-negotiable, especially within DevOps environments. Yes, DevOps brilliantly accelerates development by bridging the gap between development and operations teams. But here's the catch: that impressive speed sometimes races past essential security checkpoints. That's why weaving threat modeling directly into your DevOps workflow isn't just smart — it's necessary to spot and neutralize security threats before they become problems. IBM's 2024 Cost of a Data Breach report demonstrates that the global average cost of a data breach in 2024 is 4.88M USD, which is a 10% increase over last year and the highest total ever. What do these eye-opening statistics tell us? Simple: weaving security into your DevOps isn't optional — it's critical. Beyond just shielding you from devastating data breaches, DevSecOps actually turbocharges your development cycle, trims unnecessary spending, and takes your product quality to new heights.

Edge AI: TensorFlow Lite vs. ONNX Runtime vs. PyTorch Mobile

Aggregated on: 2025-06-06 14:58:09

My introduction to the world of edge AI deployment came with many tough lessons learned over five years of squeezing neural networks onto resource-constrained devices. If you're considering moving your AI models from comfortable cloud servers to the chaotic wilderness of edge devices, this article might save you some of the headaches I've endured. The Edge AI Reality Check Before I dive into comparing frameworks, let me share what prompted our team's journey to edge computing. We were building a visual inspection system for a manufacturing client, and everything was working beautifully... until the factory floor lost internet connectivity for three days. Our cloud-based solution became useless, and the client was not happy.

Guide to Repairing Damaged Apache Doris Tablets

Aggregated on: 2025-06-06 14:58:09

Doris's Tablet is damaged. Can it be repaired? Will data be lost? It's really hard to say.

8 Steps to Proactively Handle PostgreSQL Database Disaster Recovery

Aggregated on: 2025-06-06 14:58:09

When disaster strikes, whether a natural disaster or a technical event, its impact on your network, database, and end-users can cause data corruption. Data corruption, whether sparked by hardware failures like dying disks or faulty RAM, software glitches such as operating system bugs, or human missteps like accidental overwrites, is a terrifying prospect for any administrator. Yet, it’s not a death sentence. Your PostgreSQL database is typically a dependable cornerstone of your operations. Still, when disaster strikes, it can swiftly morph into an inaccessible liability, bringing applications to a grinding halt and leaving critical data at risk. PostgreSQL 17 arms you with an enhanced arsenal to tackle this challenge head-on, offering built-in tools like pg_amcheck for pinpointing corruption, improved failover slot synchronization to keep replication intact during recovery, and finer-grained Write-Ahead Logging (WAL) control for precise restoration. In this blog, we'll dive deep into the disaster management process, equipping you with real-world commands and expected outputs to diagnose corruption accurately and recover effectively, whether you’re restoring from a robust backup or salvaging scraps from a crippled cluster with no safety net. With the right approach, you can turn panic into a plan and restore order to your database.

New Google Search AI Mode is 'Total Reimagining,' Says CEO Sundar Pichai

Aggregated on: 2025-06-06 14:58:09

Most of Google’s AI usage comes from AI Overviews in Search, said Google CEO Sundar Pichai in a wide-ranging series of announcements during the Google I/O keynote on May 20, in Mountain View, California. This year’s I/O presentation shows Google trying to dominate the hot AI assistant landscape, from AR glasses that can answer questions about objects in view to collapsing the difference between search engines and generative AI queries. The best of Google’s offerings don’t come cheap: Gemini subscription plans will now be split into a Pro and Ultra plan. The $19.99 AI Pro plan brings a suite of products and higher rate limits than the free version. The pricey ($249.99) Ultra plan includes the highest rate limit and early access to products like the upcoming Gemini 2.5 Pro with deep reasoning, plus the full suite of AI products such as the moviemaker Flow.

Securing Software Created by AI Agents: The Next Security Paradigm

Aggregated on: 2025-06-03 16:13:07

The rise of impact has had a direct effect on the software development industry since ChatGPT and Generative AI became mainstream in late 2022. The ability of GenAI tools to write workable code was touted as one of its significant advantages, and AI has continued to improve since then. The rise of agentic AI, which can autonomously write, debug, and deploy code to environments, is the next major shift in software development. It also needs a fresh relook from a security perspective. For years, cybersecurity professionals have highlighted the shift-left approach as a key security pillar, where controls are integrated as early as possible within the lifecycle. However, as agentic AI becomes more intelligent, we now need to secure software in an environment written entirely by AI, with no human involvement.

Improving Cloud Data Warehouse Performance: Overcoming Bottlenecks With AWS and Third-Party Tools

Aggregated on: 2025-06-03 15:13:07

Performance optimization has become paramount in cloud data warehousing for organisations that need to make decisions based on fast, accurate insights. As cloud-native data platforms become the norm for modern businesses, performance bottlenecks that can slow data processing and query execution times present new challenges. These obstacles slow down operations and can also cause higher operational costs, less efficient data processing, and lost business opportunities. To address these hurdles, organizations turn to AWS, a robust cloud infrastructure capable of providing scalable and reliable solutions, alongside third-party tools for specific performance challenges. In this article, we'll examine typical performance bottlenecks, how AWS tools can help mitigate them, and the role of third-party tools in improving cloud data warehouse performance.

Beyond Bytecode: Exploring the Relationship Between JVM, JIT, and Performance

Aggregated on: 2025-06-03 14:13:08

In computing, the execution of programs written in high-level languages requires that the source code be compiled to a low-level or native language. This compilation is referred to as Ahead-of-Time (AOT) and is typically done during build time. Effectively reducing the work to be done during runtime. In case of Java, the AOT produces an intermediate binary, viz. bytecode, which is then translated to native machine code during execution by the Java Virtual Machine (JVM). This is in line with Java’s philosophy of Write-Once-Run-Anywhere (WORA), or simply put, platform independence.

What is Microsoft Fabric for Azure Cloud (Beyond the Buzz) and How It Competes with Snowflake and Databricks

Aggregated on: 2025-06-03 13:43:07

If you ask your favorite large language model, Microsoft Fabric appears to be the ultimate solution for any data challenge you can imagine. That’s also the impression many people get from Microsoft’s sales teams. But is it really the silver bullet it’s made out to be? This article takes a closer look. The first part explores the glossy marketing and sales definition of the platform. The second part looks at Fabris's layers and deconstructs it from a more practical perspective. The third part uncovers what Microsoft Fabric is truly built for, and how it fits into the wider data landscape, especially in comparison to other major players in the data analytics market like Databricks and Snowflake.

It Costs That Much Because Observability Takes Hours

Aggregated on: 2025-06-03 12:13:07

Today’s blog title is inspired by this song, "It Costs That Much." My daughter started singing it regularly after she opened her bakery. Read on for details on that story, and how it relates to observability. I thought of it, and my daughter’s reasons for singing it, after a few responses to my recent blog post, "Observability Expenses: When ‘Pennies on the Dollar’ Add Up Quickly." It touched a nerve, which was nice to see. This is an important, nuanced, and complex conversation. I believe that getting folks involved in this conversation is better for everyone.

Domain-Centric Agile Modeling for Legacy Insurance Systems

Aggregated on: 2025-06-02 21:13:07

Legacy insurance systems have accumulated decades of complexity in their codebases and business logic. This complexity is spread across batch jobs and shaped by regulation, rather than architecture. Directly applying modern Agile modeling to such a landscape often throws developers off track and into frustration. That is where Agile can work, but only when recentered around the realities of the domain. A domain-first perspective is captured by the fact that success in these environments cannot be achieved by providing screens and endpoints but by replicating the essence of how the business operates.

AI-Powered Smart Contracts: The Future Of Automated Decision-Making

Aggregated on: 2025-06-02 20:13:07

Introduction I've seen many people struggle with slow, error-prone contracts. It's frustrating when deals get held up by paperwork or mistakes. I get it — I've been there too. But here's some good news: AI-powered smart contracts are changing the game. I've done a ton of research on this topic. When AI and blockchain team up, they work together to make contracts smarter and faster because they use tech like natural language processing to understand contracts better. I'll show you how these smart contracts can speed up your work and cut down on errors.

Securing DevOps Pipelines: A Practical Guide to Balancing Speed and Security

Aggregated on: 2025-06-02 19:13:07

Security has been a major concern in today’s world. Security issues lead to data breaches with consequences such as data loss and financial losses. As a result, there is a need to focus on enhancing security. The OWASP top 10 is a good guide for DevOps teams to mitigate key web application security risks. Integrating security strategies from the beginning to the end of the process can enable DevOps teams to enhance the overall security of the applications

Enterprise Data Loss Prevention (DLP) Security Policies and Tuning

Aggregated on: 2025-06-02 18:13:07

I’ve worked with a lot of enterprise customers over the years—big ones, too—and a common struggle I see is with their Data Loss Prevention (DLP) policies. Even though they’ve had the product for years, they often face one of two issues: either the policies are too weak and don’t flag anything, or they’re too strict, overwhelming teams with false alerts. When DLP policies aren’t properly tuned, it creates gaps that can lead to business disruptions and even huge losses. A well-known example is NASA’s ITAR email filtering issue in 2019, where an excessively strict DLP policy blocked legitimate emails, grinding operations to a halt. While there are many such cases, enterprises rarely disclose disruptions caused by poor policy design. The stakes are simply too high—reputation, confidential information, and, most importantly, customer trust are all on the line. Because of this, companies are often reluctant to seek external help in refining their security policy infrastructure, even when expert guidance could prevent costly mistakes. Ultimately, security software vendors play a crucial role in simplifying policy tuning, ensuring enterprises can strike the right balance between protection and usability.

PostgreSQL Performance Tuning

Aggregated on: 2025-06-02 17:13:07

PostgreSQL is already known for its reliability, extensibility, and open-source pedigree and continues to grow and evolve with each release. PostgreSQL 17 introduces several performance improvements and features that make it a powerhouse for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) workloads. This blog will explore advanced performance tuning techniques for PostgreSQL 17 and highlight key improvements compared to versions 15 and 16.

From Hype to Harm: Why AI Governance Needs More Than Good Intentions

Aggregated on: 2025-06-02 16:13:07

The race to implement AI technologies has created a significant gap between intention and implementation, particularly in governance. According to recent data from the IAPP and Credo AI's 2025 report, while 77% of organizations are working on AI governance, only a fraction have mature frameworks in place. This disconnect between aspirational goals and practical governance has real consequences, as we've witnessed throughout 2024-2025 with high-profile failures and data breaches. I've spent the last decade working with organizations implementing AI solutions, and the pattern is distressingly familiar: enthusiasm for AI capabilities outpaces the willingness to establish robust guardrails.

The Truth About AI and Job Loss

Aggregated on: 2025-06-02 15:58:07

I keep finding myself in conversations with family and friends asking, “Is AI coming for our jobs?” Which roles are getting Thanos-snapped first? And will there still be space for junior individual contributors in organizations? And many more. With so many conflicting opinions, I felt overwhelmed and anxious, so I decided to take action instead of staying stuck in uncertainty. So, I began collecting historical data and relevant facts to gain a clearer understanding of the direction and impact of the current AI surge.

MySQL Formatter: How to Make Beautiful Code and Why You Need It

Aggregated on: 2025-06-02 15:13:07

A MySQL formatter makes code beautiful. But have you ever wondered what beautiful code looks like? You might think that this is not so important. As long as it works as intended, why make a case about it?

How to Improve Copilot's Accuracy and Performance in Power BI

Aggregated on: 2025-06-02 14:13:07

Copilot in Power BI has been a powerful advancement in making data analysis accessible to everyone. But the quality of Copilot's output is heavily dependent on the foundation it sits upon — your Power BI data model and metadata. If Copilot doesn't understand your data structure clearly, its responses can become vague, inaccurate, or not business-friendly. This article will explain how building a strong semantic model and using rich metadata and descriptions could improve Copilot’s accuracy in Power BI.

Revolutionizing KYC: Leveraging AI/ML for Regulatory Compliance

Aggregated on: 2025-06-02 13:13:07

Know Your Customer (KYC) embodies a sophisticated and proactive compliance framework strategically adopted by financial institutions to methodically scrutinize and validate client identities, transactional behaviors, and risk exposures. Beyond mere regulatory formality, KYC constitutes an integral pillar for institutional integrity, meticulously architected to mitigate systemic vulnerabilities such as identity fraud, illicit financial flows, and potential terrorist financing. Fundamentally, KYC represents an intersection of regulatory rigor and advanced analytical methodologies. It encompasses a structured process of gathering detailed identity evidence—ranging from government-issued documentation to transactional patterns—and applying intricate risk-scoring models to ascertain and continuously reassess customer authenticity, credibility, and behavioral consistency.

Observability Expenses: When ‘Pennies on the Dollar’ Add Up Quickly

Aggregated on: 2025-06-02 12:13:07

I’ve specialized in monitoring and observability for 27 years now, and I’ve seen a lot of tools and techniques come and go (RMon, anyone?); and more than a few come and stay (rumors of the death of SNMP have been – and continue to be – greatly exaggerated). Lately I’ve been exploring one of the more recent improvements in the space – OpenTelemetry (which I’m abbreviating to “OTel” for the remainder of this blog). I wrote about my decision to dive into OTel recently: "What’s Got Me Interested in OpenTelemetry—And Pursuing Certification". For the most part, I’m enjoying the journey. But there’s a problem that has existed with observability for a while now, and it’s something OTel is not helping. The title of this post hints at the issue, but I want to be more explicit. Let’s start with some comparison shopping.

Designing Embedded Web Device Dashboards

Aggregated on: 2025-06-02 11:13:07

Overview A web dashboard serves as the “front panel” for an embedded product — whether that product is a rack-mounted industrial controller, a bike-mounted GPS tracker, or a battery-powered soil-moisture sensor buried in a greenhouse bed. Because the dashboard is delivered over plain HTTP(S) and rendered in any modern browser, users do not have to download a native app, install drivers, or worry about operating-system compatibility; the interface is as portable as a URL. Typical tasks include: Toggling outputs (relays, MOSFETs, LEDs) Inspecting live data such as temperature, humidity, current draw, or RSSI Adjusting parameters like Wi-Fi credentials, alarm set-points, sampling rates Collecting diagnostics like log files or memory statistics for field support staff Implementation Approaches Embed an HTTP server — Mongoose, lwIP-HTTPD, MicroPython’s uHTTPD, or a hand-rolled socket handler - inside the firmware. Then choose, or mix, the patterns below. Each technique sits at a distinct point on the scale of resource cost versus user-experience richness.

Scaling Azure Microservices for Holiday Peak Traffic Using Automated CI/CD Pipelines and Cost Optimization

Aggregated on: 2025-05-30 20:28:05

Scaling microservices for holiday peak traffic is crucial to prevent downtime and ensure a seamless user experience. This guide explores Azure DevOps automation, CI/CD pipelines, and cost-optimization strategies to handle high-demand traffic seamlessly. Manual scaling quickly becomes a bottleneck as organizations deploy dozens, sometimes hundreds, of microservices powered by distinct backend services like Cosmos DB, Event Hubs, App Configuration, and Traffic Manager. Multiple teams juggling these components risk costly delays and errors at the worst possible moments. This is where automation comes in: a game-changing solution that transforms complex, error-prone processes into streamlined, efficient operations.

Agentic AI Systems: Smarter Automation With LangChain and LangGraph

Aggregated on: 2025-05-30 19:13:05

Things are changing fast in the world of automation. We're not just talking about those old, clunky robots that do the same thing over and over. Now, we're seeing really clever systems that can actually adapt and figure things out on their own. Leading the charge in this exciting shift are what we call Agentic AI Systems, and they're powered by some seriously cool tools like LangChain and LangGraph. These technologies are opening up a whole new level of 'smart automation.' We're talking about systems that can actually think through problems, make plans, take action, and even learn as they go. This makes them incredibly useful for those tricky tasks and situations that are always changing.

Web Crawling for RAG With Crawl4AI

Aggregated on: 2025-05-30 18:13:05

The importance of AI-powered web crawling and data extraction cannot be overstated. With the exponential growth of online data, businesses and organizations need efficient and accurate methods for collecting and analyzing data to inform their decision-making processes. Crawl4AI and Ollama offer a range of features and benefits that can help address these challenges, from automated web crawling and data extraction to natural language processing and machine learning. Crawl4AI is a powerful tool for AI-powered web crawling and data extraction. It offers a range of features and benefits, including automated web crawling, data extraction, and natural language processing. With Crawl4AI, users can easily extract data from websites, social media platforms, and other online sources, and then analyze and visualize the data using a range of tools and techniques. Crawl4AI is particularly useful for data scientists and machine learning engineers who need to collect and analyze large datasets for their projects.

My Favorite Interview Question

Aggregated on: 2025-05-30 17:13:05

Interviews are on my mind again (read into that whatever you want) and I’ve been having conversations about the experience on both sides of the Zoom camera. Finding out whether a candidate can do the job is incredibly challenging. The usual slate of techniques—from so-called “experiential questions” (“tell me about a time when you didn’t agree with a coworker”) to google-style brain teasers (“how would you go about finding out the weight of the moon using nothing but croutons”) to supposed leetcode questions (“You have two linked lists and you need to combine them”)—fall short in so many ways, but primarily they fail in the most critical way:

Yet Another GenAI Nightmare: Seven Shadow AI Pitfalls to Avoid

Aggregated on: 2025-05-30 16:13:05

If you’re ancient like me, you probably remember Lotus Notes. The leading groupware platform of the last millennium, it not only provided corporate email and pre-Slack communications, it also empowered anyone in the organization to build and publish mini-web sites for anyone to use. It didn’t take long for this whole employee empowerment train to go off the rails. Suddenly, Madge in accounting could slap up a site that exposed private corporate data—with the IT organization none the wiser. No testing, no compliance, no oversight at all.

Resolving Parameter Sensitivity With Parameter Sensitive Plan Optimization in SQL Server 2022

Aggregated on: 2025-05-30 15:13:05

For years, database administrators and developers working with SQL Server faced a persistent performance issue known as parameter sniffing. This problem arises because SQL Server’s traditional query plan caching mechanism generates only a single execution plan for a parameterized query. That plan is based on the parameter values used during the query's first execution. While efficient in many cases, this behavior leads to significant performance degradation when parameter values vary widely in terms of their data selectivity or distribution. For example, a plan optimized for a parameter value that filters a small subset of rows can be reused for a parameter that retrieves millions of rows, causing inefficient scans and resource overuse.

Source-Driven Development in Salesforce: Managing Metadata and API Versions

Aggregated on: 2025-05-30 14:13:05

Development on Salesforce has seen major changes in the last few years. SDD has made it possible for teams to match their Salesforce processes to the best modern DevOps approaches. Fundamentally, SDD depends on version control, automated deployments, and coding your data’s metadata. With benefits like consistency, traceability, and automation, such changes introduce new challenges about how versions and metadata should be managed throughout the project. Here, we’ll look at SDD principles and guide you through properly managing metadata and API versions in a Salesforce environment.

Designing Fault-Tolerant Messaging Workflows Using State Machine Architecture

Aggregated on: 2025-05-30 13:13:05

Abstract As a leader of projects for the backend of a global messaging platform that maintains millions of users daily, I was also responsible for a couple of efforts intended to enhance the stability and failure tolerance of our backend services. We replaced essential sections of our system with the help of the state machine patterns, notably Stateful Workflows. The usage of this model led to the elimination of problems in the field of message delivery, visibility of the read receipt, and device sync, such as a mismatch of phone directories. The intention of this article is to let the reader know how to keep a messaging infrastructure highly available and adaptable by sharing the practicalities and trials one faces when bringing the said architectures into production.

Apache Spark 4.0: Transforming Big Data Analytics to the Next Level

Aggregated on: 2025-05-30 12:13:05

Hurray! Apache Spark 4.0, released in 2025, redefines big data processing with innovations that enhance performance, accessibility, and developer productivity. With contributions from over 400 developers across organizations like Databricks, Apple, and NVIDIA, Spark 4.0 resolves thousands of JIRA issues, introducing transformative features: native plotting in PySpark, Python Data Source API, polymorphic User-Defined Table Functions (UDTFs), state store enhancements, SQL scripting, and Spark Connect improvements. This report provides an in-depth exploration of these features, their technical underpinnings, and practical applications through original examples and diagrams. The Evolution of Apache Spark Apache Spark’s in-memory processing delivers up to 100x faster performance than Hadoop MapReduce, making it a cornerstone for big data analytics. Spark 4.0 builds on this foundation by introducing optimizations that enhance query execution, expand Python accessibility, and improve streaming capabilities. These advancements make it a versatile tool for industries like finance, healthcare, and retail, where scalability and real-time analytics are critical. The community-driven development ensures Spark 4.0 meets enterprise needs while remaining accessible to diverse users, from data scientists to engineers.