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@faun shared a link, 9 months ago
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How Freshworks optimized server provisioning using Karpenter

Freshworks optimized AWS EKS with Karpenter to handle diverse instance types, reduce costs, and achieve seamless node provisioning, disruptions, and terminations with minimal impact to service availability and resource utilization... read more  

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Container monitoring demystified: Real challenges and what actually works

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Discover the real challenges of container monitoring from ephemeral workloads to hybrid cloud complexity and learn practical solutions using tools like Prometheus, OpenTelemetry, and Applications Manager.

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@laura_garcia shared a post, 9 months ago
Software Developer, RELIANOID

🌐 DDoS in 2025: Bigger, Smarter, and More Dangerous

DDoS attacks in 2025 are more frequent, complex, and accessible than ever—some reaching beyond 3 Tbps. From AI-driven traffic patterns to IoT botnets and multi-vector campaigns, the threat is real. Critical infrastructure, cloud APIs, and even elections are under fire. 🔐 At RELIANOID, we fight back ..

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@shallin02 shared a post, 9 months ago
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Is your docker setup actually performing well?

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Learn why Docker container monitoring is essential for performance, stability, and cost control. Discover must-watch metrics and explore tools like Applications Manager for real-time insights and smart alerts.

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@laura_garcia shared a post, 9 months ago
Software Developer, RELIANOID

Digital Certificates 101

From SSL to code signing, email encryption to client authentication — digital certificates secure our digital world. They’re powered byPKIand issued by trustedCertificate Authorities, forming a chain of trust browsers and systems rely on every day. Want to explore the types (DV, OV, EV, Wildcard, SA..

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@arshadmas shared a post, 9 months, 1 week ago
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Challenges in real user monitoring (RUM) and how to overcome them

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Real user monitoring (RUM) plays a crucial role in understanding how users truly experience your website or application. By capturing actual interaction data, RUM uncovers performance bottlenecks and usability issues that might otherwise go unnoticed. But like any monitoring approach, RUM comes with..

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SMTP vs Email API Explained & Compared: Find Out What Method Developers Should Use

A vinyl record and Spotify both get your favorite jams playing, but the way they do it couldn’t be more different. The same applies toSMTPandemail APIwhen it comes to sending emails. SMTP is the underlying protocol that has powered email for decades, while an API is an interface designed to interact..

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Functional programming languages: a blazingly fast face-off

Learn how Clojure, Elixir, Haskell, and Scala handle complex software challenges. See practical uses and find which language suits your project best.

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@laura_garcia shared a post, 9 months, 1 week ago
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🎯 Black Hat USA 2025 is approaching!

📅 August 2–7, 2025 | 📍 Mandalay Bay, Las Vegas We’re excited to join thousands of cybersecurity professionals for six days of cutting-edge Trainings, Briefings, and live tool demos. RELIANOID will be there, showcasing our latest high-performance load balancing and proxy solutions—built for the most ..

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Auto-Instrument Your Applications Using OTel Injector

Automatically instrument your apps on Linux with the OTel Injector, no code changes, minimal setup, and support for Java, Node.js, Python, and .NET.

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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.