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@faun shared a link, 3 months, 2 weeks ago

How AI data integration transforms your data stack

AI data integration obliterates manual ETL chores. It handlesschema mapping,transformation,anomaly detection. Deployments sprint ahead. Machine learning models digest structured, semi-structured, unstructured formats. They forge real-time pipelines bristling withgovernanceandsecurity. Infra shift:A..

How AI data integration transforms your data stack
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@faun shared a link, 3 months, 2 weeks ago

AI Coding Tools Underperform in Field Study with Experienced Developers

METRran an randomized controlled trial  (RCT) with 16 open-source devs. They tackled real-world code tasks usingClaude 3.5andCursor Pro. The pitch:40%speed boost. Reality:19%slowdown. A deep dive into 246 screen recordings laid bare friction in prompting, vetting suggestions, and merging code. That ..

AI Coding Tools Underperform in Field Study with Experienced Developers
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@faun shared a link, 3 months, 2 weeks ago

The Evolution of AI Job Orchestration: The AI-Native Control Plane & Orchestration that Finally Works for ML

SkyPilot spins an AI-native control plane on Neocloud Kubernetes. It binds GPU pools across clouds into one resilient grid. Teams define ML jobs in a single YAML. SkyPilot drives gang scheduling, SSH/Jupyter access, and multi-cluster compute. It does auto failover and cost-smart scheduling. Infra s..

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@faun shared a link, 3 months, 2 weeks ago

Microsoft Copilot Rooted to Gain Unauthorized Root Access to its Backend System

April 2025 Copilot Enterprise update slipped in aJupyter sandbox. It snuck in aPATH-poisonable pgrepat root’s entrypoint. Attackers could hijack that forroot execution.Eye Securityflagged the hole in April. By July 25, 2025, Microsoft patched this moderate bug. No data exfiltration reported. Why it..

Microsoft Copilot Rooted to Gain Unauthorized Root Access to its Backend System
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@faun shared a link, 3 months, 2 weeks ago

From Raw Data to Model Serving: A Blueprint for the AI/ML Lifecycle with

Post maps out aKubeflow Pipelinesworkflow onSpark,Feast, andKServe. It tackles fraud detection end-to-end: data prep, feature store, live inference. It turns infra into code, ensures feature parity in train and serve, and registers ONNX models in theKubeflow Model Registry...

From Raw Data to Model Serving: A Blueprint for the AI/ML Lifecycle with
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@faun shared a link, 3 months, 2 weeks ago

Self-hosting Trigger.dev v4 using Docker

Trigger.dev v4 sharpens self-hosting. It pins everything toDocker Compose. It bakesregistryandobject storagein. It chops YAML bloat. Env-var docs unify configs. Resource caps lock down security. Scaling? Spin up more worker containers...

Self-hosting Trigger.dev v4 using Docker
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@faun shared a link, 3 months, 2 weeks ago

How Zapier runs isolated tasks on AWS Lambda and upgrades functions at scale

Zapier snaps each customer Zap into its ownAWS Lambda, cradled inside leanFirecracker microVMs. It wrangles 100k+ functions under anEKScontrol plane and inventory DB. When runtimes retire, Zapier swings into action: a set ofTerraform modulespaired with a customLambda canary tool. Traffic trickles in..

How Zapier runs isolated tasks on AWS Lambda and upgrades functions at scale
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@faun shared a link, 3 months, 2 weeks ago

What Is IDOR? Finding and Preventing Insecure Direct Object References in AWS APIs

Attackers swap predictable IDs. They slip intoAWS APIs,Lambda functions, internal tools. Fuzzers likeffufflag sneaky HTTP 200s.Burp Intruderbubbles up 404 probes.CloudWatchlogs trace every call. Random UUIDs seal ID gaps...

What Is IDOR? Finding and Preventing Insecure Direct Object References in AWS APIs
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@faun shared a link, 3 months, 2 weeks ago

The Cybersecurity Blind Spot in DevOps Pipelines

DevOps pipelines serve as superhighways for cybercriminals to target with credential leaks, supply chain infiltration, misconfigurations, and dependency vulnerabilities. Security must evolve with development to combat these sophisticated attacks...

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@faun shared a link, 3 months, 2 weeks ago

How GitHub engineers tackle platform problems

Product engineersare like builders ofGundam models, construcing the final product, whileplatform engineerssupply the tools needed to build these kits. Understanding theGundam analogyhelps differentiate engineering roles at GitHub...

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.