Distributed Tracing: An Advanced Guide for DevOps & SREs
Learn how to implement distributed tracing effectively with this advanced guide for DevOps and SREs—optimize performance and troubleshoot faster.
Updates and recent posts about Gemini 3.. Link
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@anjali shared a link, 1 year, 3 months ago
Customer Marketing Manager, Last9
Full-Stack Observability: What It Is [Minus the Fluff]
Get a clear, no-nonsense look at full-stack observability—what it is, why it matters, and how it helps you stay on top of your systems.
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@angie shared a post, 1 year, 3 months ago
Product Marketing Analyst, manageengine
Why Application Performance Monitoring should be the apple of your eye?
Tired of daily struggles with IT visibility and performance issues? It's time to re-evaluate your monitoring strategies. Let's discuss solutions that can improve your IT performance and reduce daily headaches.
In today's competitive environment, managing IT effectively requires full-stack visibility. Juggling multiple screens and CLIs is no longer feasible. You need a capable application performance monitoring solution to gain a unified view of your IT environment, ensure high availability, and meet the demands of your users.
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@faun shared a link, 1 year, 3 months ago
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Microservice Integration Testing a Pain? Try Shadow Testing
Microservices teams often wrestle withunreliable integration tests, impeding progress. Entershadow testing—a savvy tactic where new services trot alongside current versions, processing the same traffic for a head-to-head comparison. This artful technique harnessesreal-world validationwithout botheri.. read more
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@faun shared a link, 1 year, 3 months ago
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How Core Git Developers Configure Git
Git's core developers advocate tweaking a few default settings to enrich functionality: they urge sorting branches by recent commits and upgrading the diff algorithm. Highlight settings involve renaming file detection and streamlined push behaviors, boosting Git's overall user experience... read more
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@faun shared a link, 1 year, 3 months ago
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Enhanced Monitoring Pipeline With Advanced RAG Optimizations
Observability fuels reliability in complex RAG systems, tracking and analyzing data flow meticulously. The pipeline incorporatesLiteral AI for end-to-end tracing, boosting performance insights.Effective security features encompass AES-256 encryption and role-based access control. Resource optimizati.. read more
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@faun shared a link, 1 year, 3 months ago
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Runtime Security Tools: A 2025 Guide to Protection & Top Solutions
Runtime security toolsclosely examine application behavior,network traffic, andsystem callsto uncover anomalies, bolstering defenses against cyber threats.Noteworthy solutionssuch as OPA, Falco, and Tetragon deliverreal-time monitoring and policy enforcementin cloud-native environments, sharpening s.. read more
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@faun shared a link, 1 year, 3 months ago
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Title Launch Observability at Netflix Scale
At Netflix, managing over a thousand global content launches each month involves ensuring the success and discoverability of each title. Understanding the challenges of title launch observability involves bridging the gap between tracking system metrics and metrics that matter to a title’s success. .. read more
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@faun shared a link, 1 year, 3 months ago
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Is an all-in-one database the future?
Purpose-built databases soar to address unique data needs, yielding convoluted, tangled infrastructures. Trying a one-size-fits-all database stumbles over performance hurdles, diverse data models, and optimization roadblocks... read more
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@faun shared a link, 1 year, 3 months ago
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Inside Facebook’s video delivery system
Facebook'svideo unificationinitiative has unified previously scattered systems into a single, streamlined framework, boosting content delivery for over abillion users. This consolidation grappled with intricatetrade-offsand posed formidabletechnical challengesto fine-tune video recommendation and in.. 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.
