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@sanjayjoshi gave 🐾 to How To Make a Fast Dynamic Language Interpreter , 2 days, 22 hours ago.
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@laura_garcia shared a post, 3 days, 19 hours ago
Software Developer, RELIANOID

𝗛𝗮𝗰𝗸 𝗦𝗽𝗮𝗰𝗲 𝗖𝗼𝗻 𝟮𝟬𝟮𝟲

🚀 𝗛𝗮𝗰𝗸 𝗦𝗽𝗮𝗰𝗲 𝗖𝗼𝗻 𝟮𝟬𝟮𝟲 📍 Kennedy Space Center 📅 May 6–9, 2026 𝙒𝙝𝙚𝙧𝙚 𝙘𝙮𝙗𝙚𝙧𝙨𝙚𝙘𝙪𝙧𝙞𝙩𝙮 𝙢𝙚𝙚𝙩𝙨 𝙨𝙥𝙖𝙘𝙚 𝙞𝙣𝙣𝙤𝙫𝙖𝙩𝙞𝙤𝙣. Hack Space Con is not your typical event — it’s where cybersecurity, aerospace, and advanced technologies converge to shape the future of security beyond Earth. 🔍 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗲𝘅𝗽𝗲𝗰𝘁: - Hands-on techn..

HACKSPACECON2026_florida_RELIANOID
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@varbear shared a link, 3 days, 19 hours ago
FAUN.dev()

A Couple Million Lines of Haskell: Production Engineering at Mercury

Mercury runs ~2M lines ofHaskellin production. They choseTemporalto replace cron and DB-backed state machines. Durable workflows replace brittle coordination. They open-sourced aHaskellSDK forTemporal, wired inOpenTelemetryhooks, and pushed records-of-functions plus domain-error types... read more  

A Couple Million Lines of Haskell: Production Engineering at Mercury
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@varbear shared a link, 3 days, 19 hours ago
FAUN.dev()

How To Make a Fast Dynamic Language Interpreter

Zef's AST-walking interpreter posts a 16.6× speed-up. The gains come from surgical changes:64-bit tagged values,AST node & RMW specialization,symbol hash-consing,inline caches, and a shapedobject model. Developers built it onFil-C++and later ported it toYolo-C++. The Yolo build adds ~4x speed, at th.. read more  

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@varbear shared a link, 3 days, 19 hours ago
FAUN.dev()

Agentic Coding is a Trap

AI-driven coding agents are the hot new trend, but beware of the trade-offs: increased complexity, skills atrophy, vendor lock-in, and fluctuating costs. Only skilled developers can spot issues in the vast lines of generated code, but paradoxically, AI tools are impacting critical thinking skills ne.. read more  

Agentic Coding is a Trap
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@varbear shared a link, 3 days, 19 hours ago
FAUN.dev()

How We Reduced Median Memory Estimation Error by 99%, With the Help of AI

The compaction pipeline at Mixpanel ran into memory estimation issues causing OOMKills. By implementing AI-assisted analysis, they were able to reduce median estimation errorby 99%, leading to a significant improvement in memory estimation accuracy. Through thorough analysis and exploration of alter.. read more  

How We Reduced Median Memory Estimation Error by 99%, With the Help of AI
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@varbear shared a link, 3 days, 19 hours ago
FAUN.dev()

When upserts don't update but still write: Debugging Postgres performance at scale

The Datadog team introduced a new upsert query to track inactive hosts, but it unexpectedly increased disk writes and WAL syncs due to row locking. By digging into Postgres's Write-Ahead Logging (WAL) and rewriting the query using a Common Table Expression (CTE), they avoided unnecessary overhead an.. read more  

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@kaptain shared a link, 3 days, 19 hours ago
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From Ingress NGINX to Higress: migrating 60+ resources in 30 minutes with AI

With the March 2026 retirement ofIngress NGINX, teams face an urgent compliance mandate. They must replace unpatched controllers. EnterHigress. Built onEnvoyandIstio. It unifies LLM protocols, enforces token rate limits, caches prompts, hostsMCP, and usesxDSfor zero-downtime. AnAI agentpaired withhi.. read more  

From Ingress NGINX to Higress: migrating 60+ resources in 30 minutes with AI
Pelagia is a Kubernetes controller that provides all-in-one management for Ceph clusters installed by Rook. It delivers two main features:

Aggregates all Rook Custom Resources (CRs) into a single CephDeployment resource, simplifying the management of Ceph clusters.
Provides automated lifecycle management (LCM) of Rook Ceph OSD nodes for bare-metal clusters. Automated LCM is managed by the special CephOsdRemoveTask resource.

It is designed to simplify the management of Ceph clusters in Kubernetes installed by Rook.

Being solid Rook users, we had dozens of Rook CRs to manage. Thus, one day we decided to create a single resource that would aggregate all Rook CRs and deliver a smoother LCM experience. This is how Pelagia was born.

It supports almost all Rook CRs API, including CephCluster, CephBlockPool, CephFilesystem, CephObjectStore, and others, aggregating them into a single specification. We continuously work on improving Pelagia's API, adding new features, and enhancing existing ones.

Pelagia collects Ceph cluster state and all Rook CRs statuses into single CephDeploymentHealth CR. This resource highlights of Ceph cluster and Rook APIs issues, if any.

Another important thing we implemented in Pelagia is the automated lifecycle management of Rook Ceph OSD nodes for bare-metal clusters. This feature is delivered by the CephOsdRemoveTask resource, which automates the process of removing OSD disks and nodes from the cluster. We are using this feature in our everyday day-2 operations routine.