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@faun shared a link, 11 months, 2 weeks ago
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AWS’ EKS Kubernetes ‘Critical Security’ Flaw Exposes Credentials, Says Trend Micro

Trend Microblows the lid off Amazon's EKS snafu—misconfigured Kubernetes containers brazenly leaking AWS credentials. Cue privilege escalation chaos. AWS shrugs, hiding behind the "Shared Responsibility" mantra. Trend Micro, undeterred, sounds the alarm: secure those configurations, and embrace the .. read more  

AWS’ EKS Kubernetes ‘Critical Security’ Flaw Exposes Credentials, Says Trend Micro
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@faun shared a link, 11 months, 2 weeks ago
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GKE Data Cache, now GA, accelerates stateful apps

GKE Data Cachesupercharges PostgreSQL on GKE. Imagine squeezing out480% more transactions per secondand slashing latency by80%. It's like a balancing disk on steroids—Qdrant search gets a10xboost, even without cramming everything into memory. Impressive, right?.. read more  

GKE Data Cache, now GA, accelerates stateful apps
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@faun shared a link, 11 months, 2 weeks ago
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Amazon EKS Pod Identity streamlines cross account access

Amazon EKS Pod Identityjust got an upgrade. Now you can tap into cross-account access usingIAM role chaining. Forget intricate setups and tiresome code changes. Drop in source and target IAM roles, and let EKS juggle temp credentials at runtime. It's innovation doing a happy dance... read more  

Amazon EKS Pod Identity streamlines cross account access
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@faun shared a link, 11 months, 2 weeks ago
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How We Designed Model Runner and What’s Next

Docker's just unleashed a new gadget with Desktop4.40. Meet theModel Runner, your ticket to running AI models on your local machine. Imagine it as the Peacekeeper of container-host diplomacy. It’s powered byllama.cppand can ride GPUs like a pro skater. Oh, and it plays nice with theOpenAI API. Model.. read more  

How We Designed Model Runner and What’s Next
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@anjali shared a link, 11 months, 2 weeks ago
Customer Marketing Manager, Last9

11 Best Log Monitoring Tools for Developers in 2025

A technical comparison of 11 log monitoring tools developers use in 2025—features, trade-offs, pricing, and platform compatibility

Microservices logging
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@laura_garcia shared a post, 11 months, 2 weeks ago
Software Developer, RELIANOID

🚨 Industrial Cybersecurity: Are You Ready?

📘 We’ve published a Technical Guide to ISA/IEC 62443 Standards – your 5-minute roadmap to securing Industrial Automation and Control Systems (IACS). 🔐 ISA/IEC 62443 is the gold standard for industrial cybersecurity. From zones and conduits to secure development lifecycles, it addresses the full spec..

Knowledge base ISAIEC-62443 Industrial Cybersecurity Standards RELIANOID
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@laura_garcia shared a post, 11 months, 3 weeks ago
Software Developer, RELIANOID

💸 The Cost of Cyber Insecurity

The average data breach in 2024 costs $4.45M — over $10M in finance and healthcare. Cyber incidents = market value loss, sales drop, and reputation damage. But there’s good news: 💡 Invest $500K in security → avoid $2M in losses = 300% ROI 🧠 Microsegmentation users saw 152% ROI, saved $2.9M, cut staf..

Blog Cybersecurity ROI RELIANOID
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@anjali shared a link, 11 months, 3 weeks ago
Customer Marketing Manager, Last9

Prometheus Logging Explained for Developers

Understand how Prometheus logging captures structured metrics, improves query performance, and scales observability in production systems.

Prometheus_logging
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@anjali shared a link, 11 months, 3 weeks ago
Customer Marketing Manager, Last9

Docker Stop vs Kill: When to Use Each Command

docker stop gives containers time to shut down cleanly. docker kill doesn't—use it only when you need an immediate shutdown.

docker
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@ambertalavera shared a post, 11 months, 3 weeks ago
Abto Software

Optimizing Research Efficiency with Custom Lab Inventory Management Software Development

Discover how custom lab inventory management software enhances research efficiency with real-time tracking, RFID, cloud access, and AI-powered analytics. Learn from industry use cases and expert insights.

laboratory inventory management software
GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.