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@devopslinks shared a link, 4 months ago
FAUN.dev()

Datacenters in space are a terrible, horrible, no good idea.

A former NASA engineer - now a Google Cloud AI infra alum - rips apart the idea of building GPU datacenters in orbit. His verdict: space is a terrible server rack. Power delivery? A nightmare. Heat dissipation? Worse in a vacuum. Radiation? Frying time. Even a 200kW solar rig (think ISS-sized) could.. read more  

Datacenters in space are a terrible, horrible, no good idea.
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@devopslinks shared a link, 4 months ago
FAUN.dev()

Designing a Scalable Serverless Contact System with AWS and Terraform

TravelEase Inc., a growing travel company, significantly improved customer inquiries handling by replacing a basic mailto: link with a modular, serverless, cloud-native system managed with Terraform. This new system automated message validation, processing, storage, and notifications using Lambda fu.. read more  

News FAUN.dev() Team
@devopslinks shared an update, 4 months ago
FAUN.dev()

2025 Internet Trends: Explosive AI Crawling Growth and the Rise of 30+ Tbps DDoS Attacks

In 2025, Internet growth was driven less by humans and more by AI, with AI crawling and user-triggered access surging while post-quantum encryption secured over half of human web traffic. Security risks intensified as record-breaking DDoS attacks topped 30 Tbps and government-imposed shutdowns accounted for nearly half of major global outages.

2025 Internet Trends: Explosive AI Crawling Growth and the Rise of 30+ Tbps DDoS Attacks
News FAUN.dev() Team
@kala shared an update, 4 months ago
FAUN.dev()

Meta Acquires Autonomous AI Startup Manus for $3B

Manus AI

Meta has acquired Manus AI for $3 billion, integrating its autonomous AI agents into Meta's products. Manus will continue operations and expand services under Meta, excluding China due to the removal of Chinese ownership.

Manus AI
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@kala added a new tool Manus AI , 4 months ago.
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@laura_garcia shared a post, 4 months ago
Software Developer, RELIANOID

What is Load Balancing in DigitalOcean? ⚖️

A quick 3-minute read on how traffic is distributed across Droplets to improve performance, scalability, and availability—and how RELIANOID enhances it with advanced monitoring, security, and flexibility. 👉 Smart traffic distribution. High availability. Seamless scaling. #LoadBalancing#DigitalOcean#..

Knowledge base Load Balancing in DigitalOcean  RELIANOID
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@viktoriiagolovtseva shared a post, 4 months, 1 week ago

Jira Action Items Functionality

Jira Action Items are a new feature introduced in Jira to help teams track small tasks inside a work item (issue) without needing to create subtasks. Instead of breaking out additional tickets for quick to-dos or follow-ups, you can now add lightweight checklists directly into rich text fields like ..

Zrzut ekranu 2026-01-02 152946
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@laura_garcia shared a post, 4 months, 1 week ago
Software Developer, RELIANOID

What is AWS (Amazon Web Services)?

AWS is a global public cloud platform that lets you run compute, storage, networking, databases, and more on demand, pay-as-you-go, and at scale across multiple Regions and Availability Zones. 👉 Build resilient architectures 👉 Automate everything with APIs & IaC 👉 Scale securely and globally in minu..

Knowledge base Why Deploy RELIANOID Load Balancer on AWS
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@viktoriiagolovtseva shared a post, 4 months, 1 week ago

Vendor Payment Template for Jira

Vendor Payments Take Too Much Time And There Is a Way Out of the Vicious Cycle

Zrzut ekranu 2026-01-02 142203
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@laura_garcia shared a post, 4 months, 1 week ago
Software Developer, RELIANOID

✨ Thank You, 2025 — What a Year for RELIANOID! ✨

As the year comes to a close, we want to take a moment to look back and saythank youto everyone who has been part of RELIANOID’s journey in 2025. This year has been all aboutgrowth, innovation, and community: 🚀Product & Technology - Continued evolution ofRELIANOID Enterprise Edition, delivering high..

carrusel1
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.