The Best Programmers I Know
Top devsprefer official docs overStack Overflow. They savor tools thoroughly, not dabbling. Fearless with code, they untangle complexity, and always chase knowledge. Generosity? That's their natural habitat... read more
Updates and recent posts about Gemini 3.. Link
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@faun shared a link, 1 year, 2 months ago
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Optimizing network footprint in serverless applications
AWS Serverless app developers canchop network footprint by 80%using gzip compression, defying Lambda's 6 MB payload ceiling. Sleek tricks like tapping intoAmazon S3 for hefty payloadsand fine-tuningAPI Gateway with binaryMediaTypeshelp devs sidestep payload constraints, shedding network latency and .. read more
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@laura_garcia shared a post, 1 year, 2 months ago
Software Developer, RELIANOID
Is your industrial network truly secure?
The rise of IIoT devices, AI systems, and increased cyber threats are reshaping how industrial environments must defend themselves. One of the most effective strategies?Microsegmentation. Our latest Knowledge Base article breaks down: The core principles ofdefense-in-depthfor industrial networks ..
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@anjali shared a link, 1 year, 2 months ago
Customer Marketing Manager, Last9
Histogram Buckets in Prometheus Made Simple
Learn how Prometheus histogram buckets work, why they matter, and how to fine-tune them for better observability and smarter alerting.
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@faun shared a link, 1 year, 2 months ago
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BPF or How I Learned to Stop Worrying and Love the Kernel
eBPFlets you safely unleashcustom C programsinside the Linux kernel. No more messing with kernel modules or courting system crashes. Think of it as your eagle-eyed watchman for events. Thanks toCompile Once, Run Everywhere (Co-Re), you streamline the operation, keeping your kernel as panic-proof as .. read more
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@faun shared a link, 1 year, 2 months ago
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The future of Kubernetes networking: Cilium and other CNIs with Kubernetes
Canonicalshifts into high gear withCiliumas Kubernetes' main CNI. This isn't just an upgrade—it’s a blitz usingeBPFto inject high-octane performance, cutting-edge security, and snappy service mesh action. Sure,Calicoboosts policy talk withBGPandVXLAN, andFlannelkeeps things straightforward. But let’.. read more
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@faun shared a link, 1 year, 2 months ago
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Calico Open Source 3.30: Exploring the Goldmane API for custom Kubernetes Network Observability
Calico v3.30introducesGoldmane, a gRPC API that digs deep into Kubernetes network guts. It lets you brew custom analytics potions and hook up to SIEM without getting shackled by vendors. Meanwhile,Whisker—the snazzy GUI—has you gliding through flow navigation and untangling security policies like a .. read more
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@faun shared a link, 1 year, 2 months ago
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Multi-Cluster Orchestrator for cross-region Kubernetes workloads
Multi-Cluster Orchestratorslices through multi-cluster deployments like a hot knife through butter. Ideal for AI/ML champs and GitOps mavens itching for optimized resource allocation and snappier deployment workflows... read more
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@faun shared a link, 1 year, 2 months ago
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How to add Kubernetes-powered leader election to your Go apps
k8s.io/client-go/tools/leaderelectionturns any Kubernetes app into a leader with a snap of your fingers. But there's a catch—brace yourself for possible twin leaders. It's the Wild West of leadership where balance hangs by a thread... read more
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@faun shared a link, 1 year, 2 months ago
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KubeCon Europe: How Kubernetes Handles 6G, LLMs and Deep Space
Kuberneteswrangles with the chaos of infrastructure stretching across continents, but the community's already crafting clever fixes... read more
At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.
Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.
Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.
