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@bergerx started using tool Kubectl , 4 weeks, 2 days ago.
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@bergerx started using tool Go , 4 weeks, 2 days ago.
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@faun shared a link, 1 month ago

Going down the rabbit hole of Postgres 18 features by Tudor Golubenco

PostgreSQL 18 just hit stable. Big swing! Async IO infrastructureis in. That means lower overhead, tighter storage control, and less CPU getting chewed up by I/O. Adddirect IO, and the database starts flexing beyond traditional bottlenecks. OAuth 2.0? Native now. No hacks needed. UUIDv7? Built-in su..

Going down the rabbit hole of Postgres 18 features by Tudor Golubenco
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@faun shared a link, 1 month ago

I'm Building a Browser for Reverse Engineers

A researcher rolled their ownChromium forkwith a customDevTools Protocol (CDP) domain- not for fun, but to surgically probe browser internals. It reaches into Canvas, WebGL, and other trickier APIs, dodging the usual sandbox and spoofing all the bot blockers they'd rather you leave alone. It injects..

I'm Building a Browser for Reverse Engineers
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@faun shared a link, 1 month ago

Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization

Advanced PostgreSQL tuning gets real results: composite indexes and CTEs can cut query latency hard when slicing huge datasets. AddLATERALjoins and indexed subqueries into the mix, and you’ve got a top-N query pattern that holds up—even when hammering long ID lists...

Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization
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@faun shared a link, 1 month ago

Development gets better with Age

A longtime AWS insider, Werner Vogels, breaks down the shift from slow-and-steady software growth to the generative AI rocket ride. Capabilities soared. Guardrails? Not so much. No docs, no handrails - just launch and learn. AWS didn’t chase the hype. It pulled a classic AWS move: doubled down on B2..

Development gets better with Age
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@faun shared a link, 1 month ago

Inside Husky’s query engine: Real-time access to 100 trillion events

SteamPipe just gutted its real-time storage engine and rebuilt it inRust. Expect faster performance and better scaling. Now runs oncolumnar storage, ships withvectorized queries, and rolls anobject store-backed WAL. Serious firepower for time series data. System shift:Another sign that high-throughp..

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@faun shared a link, 1 month ago

walrus: ingesting data at memory speeds

Walrusis a lock-free, single-nodeWrite Ahead Log in Rustthat rips through a million ops/sec and moves 1 GB/s of write bandwidth - on bare-metal, nothing fancy. It leans on mmap-backed sparse files, atomic counters, and zero-copy reads to get there. Each topic gets its own line of 10MB memory-mapped ..

walrus: ingesting data at memory speeds
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@faun shared a link, 1 month ago

OpenAI Agent Builder: A Complete Guide to Building AI Workflows Without Code

OpenAI’sAgent Builderdrops the guardrails. It’s a no-code, drag-and-drop playground for building, testing, and shipping AI workflows - logic flows straight from your brain to the screen. Tweak interfaces inWidget Studio. Plug into real systems with theAgents SDK. Just one catch: it’s locked behind P..

Grafana Mimir is an open-source distributed time-series database developed by Grafana Labs, designed to store and query Prometheus metrics at massive scale. It provides a horizontally scalable, multi-tenant, and highly available backend that enables organizations to run Prometheus monitoring with virtually unlimited retention and capacity.

Mimir is built for modern observability stacks, offering features like query sharding, data compaction, object storage integration (S3, GCS, Azure Blob), and efficient deduplication for high cardinality workloads. It’s compatible with the Prometheus remote_write and remote_read APIs, making it easy to integrate into existing Prometheus ecosystems.

As part of the Grafana open observability suite, Mimir can be deployed independently or alongside Loki (for logs) and Tempo (for traces) to build a complete, scalable observability platform.