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Self-Learning-Java

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Setup a GCP Account to Experiment

Google Cloud offers a free trial where new users receive $300 in credits valid for 12 months to explore and use various Google Cloud services.
Steps to Sign Up: Visit the Google Cloud website, click on 'Get started for free', sign in with your Google Account, accept the Terms of Service, provide account information, enter payment information, complete additional verification if required, submit and wait for approval.
Important Notes: After the trial, there are no auto-charges. Users must manually upgrade to a paid account to continue using the services. The free trial is available to new Google Cloud users with additional verification requirements in some regions.

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Self-Learning-Java

229

Core Components of BigQuery

BigQuery is a data analytics tool built on Google's scalable infrastructure, with key components including Colossus, Jupiter, Dremel, and Borg.
Colossus is BigQuery's distributed storage system that efficiently stores and manages large datasets in a column-based format, improving query speed and scalability.
Jupiter is Google's high-speed network that facilitates fast data transfer between machines, enabling BigQuery to handle massive workloads efficiently.
Dremel is BigQuery's query engine that processes SQL queries on huge datasets by breaking them into smaller tasks distributed across multiple machines.
Borg is the system managing Google's vast clusters, ensuring smooth operation, optimal resource utilization, and automatic failover in case of hardware failures.
BigQuery abstracts infrastructure complexities, allowing users to focus on data analysis, and leverages Google's internal infrastructure for consistent performance and scalability.
By utilizing systems like Colossus, Dremel, and Borg, BigQuery provides a seamless analytics experience, making it accessible for a wide range of users.
References to Google's research papers and cloud platform blogs provide further insights into the architecture and technologies powering BigQuery.

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Self-Learning-Java

250

Getting Started with Prometheus Key Terminologies

This article explains key terminologies in Prometheus for beginners, such as targets, jobs, instances, scrape, and alertmanager.
Scraping in Prometheus involves collecting metrics data from configured targets at regular intervals via HTTP endpoints.
Monitoring in Prometheus is the continuous process of collecting, recording, and analyzing data to track application performance and health.
Alerting in Prometheus involves setting up rules to detect abnormal conditions or thresholds based on collected metrics.
The Alertmanager in Prometheus is responsible for managing, routing, and delivering alerts effectively to prevent alert fatigue.
Targets in Prometheus are endpoints or systems where metrics are collected from, typically exposed via HTTP endpoints.
Instances in Prometheus refer to specific network endpoints where metrics are scraped, representing running copies of target services.
Jobs in Prometheus are logical groupings of instances serving similar roles, facilitating organization and analysis.
Samples in Prometheus are numeric values representing metrics at specific points in time stored in the time series database.
Understanding these terminologies is crucial for setting up effective monitoring and alerting systems in Prometheus.

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Self-Learning-Java

Prometheus Alternatives: A Beginner’s Guide to Monitoring Tools

Monitoring is crucial in today's cloud-native applications and distributed systems to track system performance and potential issues.
Prometheus, a popular monitoring tool, is compared to other options in this article to help users understand the best fit for their needs.
Some popular Prometheus alternatives include Graphite, InfluxDB, OpenTSDB, Nagios, and Sensu, each with its unique features and use cases.
Graphite is a time-series database focused on storage and visualization, while Prometheus offers a full-service monitoring solution with active data collection and a powerful query language.
Prometheus allows for per-instance metrics storage, flexible data filtering, and powerful querying with PromQL, making it suitable for modern dynamic environments.
Graphite is better for long-term historical storage, seamless integration with existing tools like StatsD, and a push-based model for metric collection.
Prometheus is recommended for new projects, end-to-end monitoring needs, and a pull-based model for better control over metric collection.
Prometheus's rich query language (PromQL) and integrated alerting with Alertmanager provide extensive monitoring capabilities for system performance and reliability.
With a strong community and growing ecosystem, Prometheus is a reliable choice for gaining insights into system performance in various environments.
This article covers the key features of Prometheus, its comparison with Graphite, and the benefits it offers for monitoring services in modern setups.
Whether monitoring a single service or a microservices ecosystem, Prometheus provides the tools needed for building robust observability systems.

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Dev

432

Image Credit: Dev

🎬 I Built a YouTube Clone

A developer built a YouTube clone using React, TypeScript, Next.js, Tailwind, and Framer Motion.
Week 1 involved creating a responsive layout, the main video feed, and making it resemble YouTube.
Week 2 focused on building a backend, adding a Shorts section, video lists, and metadata display.
Week 3 included refining the custom video player UI, responsive design, and deploying the project to Vercel.

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Medium

314

Image Credit: Medium

Why Minimal Technology Layers perform better than Complex Systems

Having a minimal tech stack can be more powerful than a complex setup with many tools.
Limiting the number of apps reduces decision fatigue and saves mental energy.
Mastering one or two tools deeply is more effective than being a beginner in multiple apps.
A minimal tech stack reduces maintenance overhead, saves time, and improves focus, leading to increased productivity.

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Medium

256

Image Credit: Medium

Build an AI-Powered Web Scraper That Thinks for You

The project involves a sequential workflow using LangGraph for processing web content through various AI-powered stages.
Key libraries utilized in the project include Groq LLM, bs4, and Meta’s Llama 4 Scout model.
The system manages data through a defined state structure and implements core scraping functionality with bs4.
Various AI-powered processing nodes are used for content categorization, summarization, tag extraction, sentiment analysis, key phrases identification, readability scoring, fact-checking, and content structure evaluation.
The project workflow combines these processing nodes to provide a comprehensive analysis of web content, and it can be extended for multi-page scraping, image analysis, data visualization, persistent storage, and custom pipelines.

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Medium

332

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Optimizing Bank Loan Approvals with Genetic Algorithms in Python

Genetic algorithms are being used to optimize loan approvals in banks by a data scientist.
Genetic algorithms offer a more efficient solution compared to traditional grid search and brute-force approaches.
GA is inspired by natural selection and evolves solutions over generations to find optimal outcomes.
This article explains the intuition behind genetic algorithms and their application in optimizing loan approval thresholds.

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Medium

118

Image Credit: Medium

Why is LLama 4 Much Better Than GPT-4o and Gemini 2.0 Flash — Here is The Result

Meta announced the latest large-scale language model, Llama 4, designed as a native multi-modality AI model that can process both text and images.
Llama 4 is a multimodal large model capable of processing text, video, images, and audio, and converting content between these formats.
It is the first in the Llama series to utilize a mixture of experts (MoE) architecture, enhancing efficiency in training and addressing user queries by dividing the model into specialized 'expert' sub-models.
Mark Zuckerberg emphasized the aim of creating the leading AI, open-sourcing it, and ensuring accessibility for all. Llama 4 is available in three main variations.

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7 Likes

Medium

437

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MacBook Air M4 Review: My First Blog and a Developer’s Dream

The MacBook Air M4 is praised for its Magic Keyboard and oversized Force Touch trackpad, making it a developer's dream machine.
Developers find the M4 efficient for running multiple software simultaneously with fast compilation times, thanks to its 16GB unified memory.
The M4's Neural Engine is highlighted for handling AI tasks well, making it ideal for prototyping and Core ML-optimized models.
With a price of ₹99,900 (or ₹89,000 during offers), the MacBook Air M4 is seen as a cost-effective option for developers seeking high performance in a compact package.

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Python Blogs

136

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SpyDialer Reverse Phone Lookup and Competitors

SpyDialer is a free reverse phone lookup tool that helps identify unknown numbers by searching public data, social media, and online sources for information like names, addresses, and voicemail previews.
SpyDialer is free, fast, and user-friendly, requiring no sign-up or personal information, making it convenient for everyday users.
While SpyDialer may not always be accurate, there are alternative reverse phone lookup tools like TrueCaller, WhitePages, BeenVerified, and NumLookup that offer different features such as deep background checks, social media data, and U.S. number searches.
These services are legal as they use publicly available information and can be useful for various purposes like identifying scams, checking unfamiliar numbers, ensuring online safety, or reconnecting with old acquaintances.

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8 Likes

Medium

397

Atomic Echo Theory: Déjà Vu as Memory Residue —A Doctrine of Memory Beyond Death—

Memory is proposed to be a persistent pattern embedded in atomic energy, transferring through atoms between forms, carrying memory potential.
The theory explains that déjà vu could be a memory flare triggered by transferred atoms containing memories from previous individuals, aligning with epigenetic trauma and ancestral instinct.
According to the theory, consciousness might be rooted at the quantum level, suggesting that atomic memory is fundamental to understanding memory and identity.
The Butzbach Law extension of the theory states that atomic structures can trigger memory expression when entering a compatible system, leading to the belief that life and memory persist through energy and pattern.

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23 Likes

Dev

223

Image Credit: Dev

How to Create a Vertical Dotted Line with CSS

Creating a vertical dotted line using CSS can enhance webpage layout and guide users' eyes effectively.
CSS provides flexibility in adjusting color, spacing, and responsiveness without the need for additional image files.
Two efficient methods to create a vertical dotted line are using the border property and utilizing a linear-gradient background.
It's crucial to consider responsive design and test across different viewports to ensure the visual appeal of the vertical dotted line.

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13 Likes

Medium

341

Image Credit: Medium

Why User Consent in Data Collection Matters for Privacy

Data collection involves gathering user information to enhance services, tailor experiences, and serve ads, impacting privacy.
Consent is crucial in data collection, requiring clear permission before using individual information and should be transparent.
Bad consent practices include instances like smart glasses capturing data without explicit consent, raising privacy concerns.
Governments are implementing laws to regulate data harvesting, but companies still find ways to bypass them, emphasizing the need for user awareness and responsible practices.

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Dev

163

Image Credit: Dev

Day 2/200 (Full Stack)

Today's progress: Learned HTML tags including heading, anchor, image, bold, italic, underline, paragraph, big, small, hr, subscript, superscript, pre.
Heading tags: h1 to h6 for different sizes.
Anchor tag used for links: text.
Image tag for adding images: .
Tags like bold, italic, underline, paragraph, big, small, hr, subscript, superscript, and pre were also covered.

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