DEV Community: Joseph

🚀 [Weekly Top 10] BBC Tech Leadership, Grab TechDocs, GitHub for Beginners

Joseph — Tue, 11 Mar 2025 12:13:08 +0000

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Weekly Tech | Mar 10, 2025 | 10 Contents

Things I have learned about Tech Leadership
TechDocs at Grab: Cultivating a culture of quality documentation
GitHub for Beginners: How to get started with GitHub Copilot
Rain: A key-value store for Strava’s scale
Container orchestration: Docker Swarm vs Kubernetes
Standardizing UX at Scale: How Agoda Developed Its Experience Principles
How We Transformed Payment Rule Management with Git as a Database
Video: How to run dependency audits with GitHub Copilot
A case for QLC SSDs in the data center
Building a Spark observability product with StarRocks: Real-time and historical performance analysis

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1. Things I have learned about Tech Leadership

BBC Product & Technology - Medium

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This is recommended for anyone considering a role in tech leadership.

📄 Summary

Leadership involves empowering team members rather than micromanaging them.

Collective decision-making fosters motivation and better ideas than a top-down approach.

Building trust and maintaining good relationships are crucial for effective influence and team dynamics.

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2. TechDocs at Grab: Cultivating a culture of quality documentation

Grab Tech

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This is recommended for anyone looking to improve their organization's documentation culture.

📄 Summary

The TechDocs team at Grab implemented a Docs-as-Code approach to integrate documentation into engineering workflows, fostering a culture of quality documentation.

Key steps included assessing current processes, establishing clear policies, empowering teams with tools, and tracking metrics to celebrate successes.

Training and workshops were introduced to enhance writing skills and collaboration, while ongoing feedback loops were established to continuously improve documentation practices.

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3. GitHub for Beginners: How to get started with GitHub Copilot

The GitHub Blog

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This guide is essential for anyone looking to enhance their coding efficiency with AI assistance.

📄 Summary

GitHub Copilot is an AI pair programmer that helps users write code faster and is compatible with various IDEs.

The installation process varies by IDE, with detailed steps provided for both VS Code and JetBrains IDEs.

Users can utilize features like code completion and Copilot Chat to gain insights and improve their coding tasks.

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4. Rain: A key-value store for Strava’s scale

strava-engineering - Medium

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This is recommended for those looking to understand efficient data management at scale.

📄 Summary

Rain is a key-value store designed to handle large, immutable datasets efficiently, improving deployment times and reducing memory usage.

It leverages Apache Spark for data processing and allows for seamless updates and schema changes without service redeployment.

The system incorporates multiple caching layers to optimize data retrieval and supports local development environments for faster iteration.

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5. Container orchestration: Docker Swarm vs Kubernetes

Credera Engineering - Medium

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This article is essential for anyone deciding between Docker Swarm and Kubernetes for container orchestration.

📄 Summary

It outlines the strengths and weaknesses of both Docker Swarm and Kubernetes, helping users choose based on their project's complexity and scale.

Docker Swarm is highlighted for its simplicity, low resource overhead, and faster deployment, making it suitable for smaller environments.

Kubernetes is presented as the more robust option for large-scale applications, offering advanced features and extensive community support, albeit with a steeper learning curve.

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6. Standardizing UX at Scale: How Agoda Developed Its Experience Principles

Agoda Engineering - Medium

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This article is essential for understanding how to create a standardized UX framework in a global context.

📄 Summary

Agoda developed Experience Principles to ensure consistency and usability across its products, addressing the challenge of defining 'good UX'.

The principles were created through industry benchmarking, brainstorming workshops, and stakeholder alignment, focusing on intuitive design, trust, and inclusivity.

Integrating these principles into the design process has led to improved design quality, reduced UX issues, and a more collaborative environment.

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7. How We Transformed Payment Rule Management with Git as a Database

Agoda Engineering - Medium

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This article is highly beneficial for teams looking to improve their payment rule management processes.

📄 Summary

Agoda's Payment team faced challenges with traditional database management due to the complexity and risk of errors in modifying payment rules.

They implemented Git as a database, leveraging its version control, auditability, and structured review workflows to enhance rule management.

The new system allows for user-friendly management of rules, automated validation, and safer deployments, significantly improving efficiency and scalability.

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8. Video: How to run dependency audits with GitHub Copilot

The GitHub Blog

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This guide is essential for developers struggling with manual dependency management.

📄 Summary

It highlights the limitations of manual dependency audits, such as being error-prone and time-consuming.

The article provides a step-by-step approach to automate dependency management using GitHub Copilot, GitHub Actions, and Dependabot.

It emphasizes the benefits of automation, including improved security, reduced manual effort, and better documentation of dependency issues.

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9. A case for QLC SSDs in the data center

Engineering at Meta

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This is recommended for those exploring innovative storage solutions in data centers.

📄 Summary

QLC flash technology offers a balance between HDDs and TLC SSDs, providing higher density and improved power efficiency.

The adoption of QLC is expected to enhance server and rack-level byte densification while lowering acquisition and power costs.

Meta is actively integrating QLC storage into its data centers, recognizing its potential for optimizing storage cost, performance, and power efficiency.

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10. Building a Spark observability product with StarRocks: Real-time and historical performance analysis

Grab Tech

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This article is highly beneficial for those looking to enhance their Spark observability tools.

📄 Summary

It discusses the transition from a fragmented observability system to a unified platform using StarRocks, addressing previous limitations.

The new architecture simplifies data ingestion and management, allowing for real-time and historical performance analysis of Spark jobs.

Key features include materialised views for improved query performance, dynamic partitioning for efficient data management, and a comprehensive web application for user-friendly access.

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This is a newsletter operated by newtler. ‘newtler’ is a social-based content reader service that allows you to receive new posts from any media of your choice, not just tech blogs, all in one place! 😎

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🚀 [Weekly Top 10] Petabyte Scale, Netflix Impressions, Grab AI

Joseph — Thu, 27 Feb 2025 12:14:21 +0000

✅ Get a briefing on the latest articles from top tech blogs worldwide, along with concise summaries.

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Weekly Top 10 | Feb 25, 2025 | 10 Contents

The Quest to Understand Metric Movements
AI enhancements to Adaptive Acceptance
Searching for the cause of hung tasks in the Linux kernel
Data Quality at Petabyte Scale: Building Trust in the Data Lifecycle
Estimating Incremental Lift in Customer Value (Delta CV) using Synthetic Control
Introducing Impressions at Netflix
Protecting user data through source code analysis at scale
Revenue Automation Series: Building Revenue Data Pipeline
Grab AI Gateway: Connecting Grabbers to Multiple GenAI Providers
How to debug code with GitHub Copilot

1. The Quest to Understand Metric Movements

Stories by Pinterest Engineering on Medium

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This resource is valuable for anyone trying to understand fluctuations in key metrics.

📄 Summary

It outlines three approaches for root-cause analysis of metric movements: Slice and Dice, General Similarity, and Experiment Effects.

The Slice and Dice method involves breaking down metrics into segments to identify significant contributors to changes.

General Similarity examines correlations between metrics to find related movements, while Experiment Effects analyzes the impact of A/B tests on metrics.

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2. AI enhancements to Adaptive Acceptance

Stripe Blog

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This is recommended for online businesses struggling with false declines in transactions.

📄 Summary

False declines cost US online retailers an estimated $81 billion in lost sales, highlighting the importance of addressing this issue.

Adaptive Acceptance utilizes advanced AI to optimize payment requests and recover falsely declined transactions, achieving a 70% increase in precision.

Recent improvements in model training efficiency allow for rapid updates, enabling the system to adapt to emerging patterns in transaction data.

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3. Searching for the cause of hung tasks in the Linux kernel

The Cloudflare Blog

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This post is valuable for understanding and troubleshooting hung task warnings in Linux.

📄 Summary

It explains the hung task warning, its causes, and the significance of the TASK_UNINTERRUPTIBLE state.

The Linux kernel uses a special thread, khungtaskd, to monitor processes in the D state and log warnings based on configurable thresholds.

Real-world examples illustrate how to identify the root causes of hung tasks, emphasizing the importance of analyzing stack traces and system metrics.

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4. Data Quality at Petabyte Scale: Building Trust in the Data Lifecycle

Glassdoor Engineering Blog - Medium

📣️ newtler Comments

This article is essential for organizations aiming to enhance their data quality practices.

📄 Summary

It emphasizes the importance of a proactive approach to data quality, shifting responsibility to data producers.

The implementation of data contracts and static code analysis helps prevent data issues before they reach production.

Real-time monitoring and anomaly detection further ensure data integrity and reliability throughout the data lifecycle.

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5. Estimating Incremental Lift in Customer Value (Delta CV) using Synthetic Control

The PayPal Technology Blog - Medium

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This is valuable for understanding how user actions impact customer value at PayPal.

📄 Summary

Delta CV measures the incremental profit margin from product adoption or user actions over the first year.

The methodology involves causal inference and synthetic control to compare adopters with non-adopters based on transactional features.

Delta CV provides insights into user engagement and the cumulative effects of product adoptions, while also highlighting potential biases and limitations in the estimation process.

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6. Introducing Impressions at Netflix

Netflix TechBlog - Medium

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This article is valuable for understanding how Netflix enhances user experience through impression tracking.

📄 Summary

Impression history is crucial for personalized recommendations, frequency capping, and monitoring new content interactions.

The architecture involves a Source-of-Truth dataset that processes raw impression events using Apache Kafka and Iceberg for real-time and historical data management.

Future improvements focus on schema management for raw events, automating performance tuning, and enhancing data quality alerts to ensure data integrity.

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7. Protecting user data through source code analysis at scale

Engineering at Meta

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This information is crucial for understanding how Meta combats unauthorized scraping.

📄 Summary

Meta's Anti-Scraping team uses static analysis tools to detect potential scraping vectors across its platforms.

The tools track data flow from user-controlled parameters to returned data, identifying vulnerabilities that scrapers could exploit.

While static analysis helps mitigate scraping risks, it cannot catch all issues due to the complexity of unauthorized scraping methods.

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8. Revenue Automation Series: Building Revenue Data Pipeline

Yelp Engineering and Product Blog

📣️ newtler Comments

This article is essential for understanding the complexities of automating revenue recognition processes.

📄 Summary

It outlines the journey of building a Revenue Data Pipeline to integrate with a Revenue Recognition SaaS solution, enhancing efficiency.

The article discusses the challenges faced in translating ambiguous business requirements into engineering-friendly terms and the solutions implemented.

It highlights the technical choices made for data processing and the use of Spark ETL to manage complex data transformations effectively.

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9. Grab AI Gateway: Connecting Grabbers to Multiple GenAI Providers

Grab Tech

📣️ newtler Comments

This is essential for anyone looking to leverage Generative AI technologies effectively.

📄 Summary

Grab AI Gateway provides centralized access to multiple AI providers, simplifying authentication and resource management.

It enables experimentation with various AI models while minimizing costs through a shared capacity pool.

The gateway ensures compliance with privacy standards through thorough auditing and offers a unified API interface for ease of use.

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10. How to debug code with GitHub Copilot

The GitHub Blog

📣️ newtler Comments

This guide is essential for developers looking to enhance their debugging process with AI assistance.

📄 Summary

GitHub Copilot can streamline debugging by providing real-time suggestions, analyzing code, and generating test cases.

It offers various features such as interactive assistance in Copilot Chat, contextual help in IDEs, and support for pull requests.

Best practices include providing clear context, refining prompts, and using slash commands to optimize the debugging workflow.

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