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@kala shared a link, 3 weeks, 1 day ago
FAUN.dev()

AI agents are starting to eat SaaS

AI coding agents are eating the lunch of low-complexity SaaS. Teams with a bit of dev muscle are skipping subscription logins and spinning up dashboards, pipelines, even decks, using Claude, Gemini, whoever’s fastest that day. Build vs. buy? Tilting back toward build. The kicker: build now takes min.. read more  

AI agents are starting to eat SaaS
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@kala shared a link, 3 weeks, 1 day ago
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Everything to know about Google Gemini’s most recent AI updates

Google jammed a full no-code AI workshop into Gemini. The browser now bakes inOpal, a drag-and-drop app builder with a shiny newvisual editor. You can chain prompts, preview apps, and feed it text, voice, or images, without touching code. They also dropped theGemini 3 Flash model, built for dual rea.. read more  

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@devopslinks shared a link, 3 weeks, 1 day ago
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From Static Rate Limiting to Adaptive Traffic Management in Airbnb’s Key-Value Store

Airbnb just rewired Mussel, its key-value store, with a smarter, layered QoS system. Out go the rigid QPS caps. In comeresource-aware rate control,criticality-based load shedding, andreal-time hot-key mitigation. Dispatchers now speak the language of backend cost -rows, bytes, latency - not just raw.. read more  

From Static Rate Limiting to Adaptive Traffic Management in Airbnb’s Key-Value Store
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@devopslinks shared a link, 3 weeks, 1 day ago
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Agent-Driven SRE Investigations: A Practical Deep Dive into Multi-Agent Incident Response

A sandboxed setup dropped multiple Claude-powered agents into Docker containers to run a full incident response drill. Each agent played a role: probing Kubernetes clusters, sniffing out root causes, and shipping remediation PRs straight to GitHub. Out of 7 test incidents, they nailed the diagnoses .. read more  

Agent-Driven SRE Investigations: A Practical Deep Dive into Multi-Agent Incident Response
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@devopslinks shared a link, 3 weeks, 1 day ago
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async dns

A developer went digging for safer async DNS incurlafterpthread_cancelstarted breaking things. Threadless, callback-free options took the spotlight.OpenBSD’sasrquickly stood out, clean event loop integration, no threads, no drama. Beat outc-areson portability and design clarity... read more  

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@devopslinks shared a link, 3 weeks, 1 day ago
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How We Saved 70% of CPU and 60% of Memory in Refinery’s Go Code, No Rust Required.

Refinery 3.0 cuts CPU by 70% and slashes RAM by 60%. The trick: selective field extraction from serialized spans. No full deserialization. Fewer heap allocations. Way less waste. It also recycles buffers, handles metrics smarter, and is gearing up to parallelize its core decision loop... read more  

How We Saved 70% of CPU and 60% of Memory in Refinery’s Go Code, No Rust Required.
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@kaptain shared an update, 3 weeks, 1 day ago
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Docker Brings Production-Grade Hardened Images to Developers at No Cost

Docker

Docker has launched Docker Hardened Images, a secure and minimal set of production-ready images. These images are now freely available to developers.

Docker Brings Production-Grade Hardened Images to Developers at No Cost
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@anjali shared a link, 3 weeks, 1 day ago
Customer Marketing Manager, Last9

OTel Updates: OpenTelemetry Deprecates Zipkin Exporters

OpenTelemetry deprecates Zipkin exporters in favor of native OTLP support. Migration paths and timeline through December 2026.

depreciating_zipkin
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@kaptain shared an update, 3 weeks, 1 day ago
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Argo CD 3.2.2 Improves Secret Management, Retry Safety, and Auth Checks

Kubernetes Argo CD

ArgoCD v3.2.2 has been released, featuring a new addition, two enhancements, and a bug fix. This update aims to improve the overall functionality and reliability of the platform.

Argo CD 3.2.2 Improves Secret Management, Retry Safety, and Auth Checks
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@devopslinks shared an update, 3 weeks, 2 days ago
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Rust Confirmed for Linux Kernel: Experiment Concludes Successfully

Rust GNU/Linux The Linux Kernel UNIX

The Rust experiment in the Linux kernel concludes, confirming its suitability and permanence in kernel development, with Rust now used in production and supported by major Linux distributions.

Rust Confirmed for Linux Kernel: Experiment Concludes Successfully
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.