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@laura_garcia shared a post, 3 weeks, 5 days ago
Software Developer, RELIANOID

🚗🔒 Automotive Cybersecurity: Connected Cars, Connected Risks

Modern vehicles are no longer just machines — they’re connected devices storing data, running AI-driven assistants, and linked to vast supply chains. But with innovation comes new threats: from remote car hacking to ransomware attacks targeting manufacturing lines. Recent incidents — like the cybera..

Blog_Automotive Cybersecurity_relianoid
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@laura_garcia shared a post, 3 weeks, 6 days ago
Software Developer, RELIANOID

Huge thanks to Design Tech Solutions for publishing an article about RELIANOID! 📰 🤩

They explore how the RELIANOID Load Balancer enhances maritime cybersecurity, helping secure connected vessels, ports, and critical infrastructure. Read the full article here: https://www.relianoid.com/about-us/relianoid-related-articles/ #MaritimeCybersecurity#CyberSecurity#ConnectedShipping#LoadBa..

design tech solutions Article
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@anjali shared a link, 3 weeks, 6 days ago
Customer Marketing Manager, Last9

7 Observability Solutions for Full-Fidelity Telemetry

A quick guide to how seven leading observability tools support full-fidelity telemetry and the architectural choices behind them.

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@varbear shared a link, 4 weeks ago
FAUN.dev()

We are replacing OOP with something worse

Object-oriented programming didn’t die - it evolved. Now it lives in the guts of infrastructure. Services talk through strict interfaces, crossing process and network lines like pros. Classes and objects? They're nowOpenAPI schemas,Docker containers, andKubernetes clusters- same old encapsulation ga.. read more  

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@varbear shared a link, 4 weeks ago
FAUN.dev()

Why is Zig so Cool?

Zig bringscross-compilationandC interoperabilityto the forefront - no extra setup, no toolchain fuss. It builds across architectures, links with C code like it was born to, and skips headers entirely. Its real flex?Compile-time execution, sharperror handling, and azero-fat runtime. All wrapped in a .. read more  

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@varbear shared a link, 4 weeks ago
FAUN.dev()

How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago

“Ghost in the Shell” turned 30 this week. Still hits hard. Back in 1989, it dropped cyberpunk bombs that would take the real world decades to catch up with: government-grade AI hackers, behavior-based intrusion detection, malware tailored for humans, and remote code attribution that vanishes into th.. read more  

How the classic anime 'Ghost in the Shell' predicted the future of cybersecurity 30 years ago
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@varbear shared a link, 4 weeks ago
FAUN.dev()

Programming Languages in the Age of AI Agents

GitHub Copilot and friends tend to shine in languages with rich static types - think Rust or Scala. Why? The compiler does the heavy lifting. It flags mistakes fast, keeps structure tight, and gives the AI sharper signals to riff on. But drop that agent into a sprawling legacy repo, and cracks show... read more  

Programming Languages in the Age of AI Agents
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@varbear shared a link, 4 weeks ago
FAUN.dev()

The (lazy) Git UI You Didn't Know You Need

Lazygit is a snappy terminal Git UI that’s picking up steam - and for good reason. It streamlines common tasks like staging, rebasing, and patching without dragging you through clunky menus. The interface sticks close to native Git commands but adds just enough structure to reduce context switches a.. read more  

The (lazy) Git UI You Didn't Know You Need
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@varbear shared a link, 4 weeks ago
FAUN.dev()

Your URL Is Your State

Modern frontend apps love to complicate state. But they keep forgetting the URL - shareable, dependency-free, and built for the job. This piece breaks down how a well-structured URL can capture UI state, track history, and make bookmarking effortless. NolocalStorage. No cookies. No bloated global st.. read more  

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@varbear shared a link, 4 weeks ago
FAUN.dev()

ChatGPT as My Coding Mentor: How I Learned React and Next.js as a Junior Developer

A junior dev leveled up their React and Next.js chops just by writing better prompts. Big wins came from getting specific - like stating their skill level, asking for analogies, and stacking questions to unpack how Next.js splits client and server. Trend to watch:Prompting is a core dev skill for an.. read more  

ChatGPT as My Coding Mentor: How I Learned React and Next.js as a Junior Developer
Grafana Tempo is a distributed tracing backend built for massive scale and low operational overhead. Unlike traditional tracing systems that depend on complex databases, Tempo uses object storage—such as S3, GCS, or Azure Blob Storage—to store trace data, making it highly cost-effective and resilient. Tempo is part of the Grafana observability stack and integrates natively with Grafana, Prometheus, and Loki, enabling unified visualization and correlation across metrics, logs, and traces.

Technically, Tempo supports ingestion from major tracing protocols including Jaeger, Zipkin, OpenCensus, and OpenTelemetry, ensuring easy interoperability. It features TraceQL, a domain-specific query language for traces inspired by PromQL and LogQL, allowing developers to perform targeted searches and complex trace-based analytics. The newer TraceQL Metrics capability even lets users derive metrics directly from trace data, bridging the gap between tracing and performance analysis.

Tempo’s Traces Drilldown UI further enhances usability by providing intuitive, queryless analysis of latency, errors, and performance bottlenecks. Combined with the tempo-cli and tempo-vulture tools, it delivers a full suite for trace collection, verification, and debugging.

Built in Go and following OpenTelemetry standards, Grafana Tempo is ideal for organizations seeking scalable, vendor-neutral distributed tracing to power observability at cloud scale.