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Weaponizing the AWS CLI for Persistence

Researchers pulled off a slick persistence trick usingAWS CLI aliases. They chained dynamic alias renaming with command execution to swipe credentials, without breaking expected CLI behavior. No red flags. Perfect fit forautomated environmentslike CI/CD pipelines. Backdoors, no AWS CLI tampering req.. read more  

Weaponizing the AWS CLI for Persistence
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Cloud Workload Threats - Runtime Attacks in 2026

Cloud-native breaches keep slipping through the cracks, not because no one’s watching, but because they’re watching the wrong things. Static checks and posture tools can’t catch what happens in motion. That’s where most attacks live now: at runtime. Think app-layer exploits, poisoned dependencies, s.. read more  

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21 Lessons From 14 Years at Google

A seasoned Google engineer drops 21 sharp principles for scaling engineering beyond just writing code. Think:clarity beats cleverness,users over egos,alignment over being “right.”The core message? Build systems humans can work with - especially under stress. Favorites: kill pointless work, treat pro.. read more  

21 Lessons From 14 Years at Google
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Azure Hybrid Benefit Audit Guide: Avoid the $50K Licensing Mistake (2025)

Azure just tightened the screws on Hybrid Benefit. Use it without the rightSoftware Assurance, botch yourlicense-to-core mapping, or skipdecommissioning proof, and you’re staring down $50K+ in penalties. To help dodge that landmine, Microsoft dropped a new guide. It covers pre-migration checks, audi.. read more  

Azure Hybrid Benefit Audit Guide: Avoid the $50K Licensing Mistake (2025)
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Terraform governing with OPA

When managing infrastructure with Terraform, enforcing tagging standards, instance type restrictions, preventing public exposure, enforcing regions, and other best practices are essential with Open Policy Agent (OPA). OPA evaluates Terraform plans before apply to ensure compliance with organization'.. read more  

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2025's most influential projects according to GitHub

GitHub

Universe 2025 highlighted a shift toward mature, developer-first open source projects that favor usability, sustainability, and real-world adoption over hype. From backend platforms and release tooling to browsers, graphics engines, and security baselines, the standout projects all share one trait: they are being actively used, maintained, and pushed forward by communities that know exactly what problems they are solving.

Open Source at Full Throttle: The Projects Setting the Pace in 2025
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Linus Torvalds Draws a Line on AI in the Linux Kernel but Embraces It in Personal Projects

Google Antigravity

Linus Torvalds argues that Linux kernel guidelines should treat AI like any other development tool, not as a special case, saying documentation cannot solve bad submissions. At the same time, he openly acknowledges using an AI coding tool in a personal project, signaling pragmatic acceptance of AI-assisted development outside core kernel policy.

Linus Torvalds vibe coding a side project
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OpenAI Goes All-In on Healthcare: ChatGPT Health for Consumers, and a Suite for Hospitals

ChatGPT GPT-5.2

OpenAI introduces ChatGPT for Healthcare, offering HIPAA-compliant AI tools to enhance healthcare delivery. The suite includes ChatGPT Health, designed to integrate health information with AI for improved user navigation.

OpenAI Goes All-In on Healthcare: ChatGPT Health for Consumers, and a Suite for Hospitals
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There Are Kernel Bugs in Your System That Won’t Be Found for 20 Years

The Linux Kernel

The analysis of Linux kernel bugs shows that some bugs remain undiscovered for over 20 years, with an average lifespan of 2.1 years. The study examined 125,183 bug-fix pairs and found that certain subsystems have longer bug lifetimes. A tool developed for the research identified 92% of historical bugs, and findings indicate that bug discovery has improved over time.

There Are Kernel Bugs in Your System That Won’t Be Found for 20 Years
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@kaptain shared an update, 3 months, 1 week ago
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Running Databases on Kubernetes Is Becoming the New Normal

Running databases on Kubernetes has moved from experimentation to standard practice, driven by platform maturity, cost pressures, and AI/ML demands. According to the 2025 Data on Kubernetes survey, organizations are now focused on operational excellence, with cost optimization, storage performance, and AI workloads shaping the next phase.

BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).