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Scaling Autonomous Site Reliability Engineering: Architecture, Orchestration, and Validation for a 90,000+ Server Fle

Cloudways scaled from a bootstrapped startup to a leading managed PHP hosting service, encountering challenges with growing support load. Early on, Cloudways recognized the opportunity to implement an AI-based SRE agent to reduce the burden on support teams and provide faster diagnosis and resolutio.. read more ย 

Scaling Autonomous Site Reliability Engineering: Architecture, Orchestration, and Validation for a 90,000+ Server Fle
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@laura_garcia shared a post, 1ย month, 2ย weeks ago
Software Developer, RELIANOID

๐˜—๐˜ฐ๐˜ด๐˜ต-๐˜˜๐˜ถ๐˜ข๐˜ฏ๐˜ต๐˜ถ๐˜ฎ ๐˜Š๐˜ณ๐˜บ๐˜ฑ๐˜ต๐˜ฐ๐˜จ๐˜ณ๐˜ข๐˜ฑ๐˜ฉ๐˜บ: Preparing for ๐˜๐—ต๐—ฒ ๐—ก๐—ฒ๐˜…๐˜ ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐—˜๐—ฟ๐—ฎ

๐Ÿš€ ๐˜—๐˜ฐ๐˜ด๐˜ต-๐˜˜๐˜ถ๐˜ข๐˜ฏ๐˜ต๐˜ถ๐˜ฎ ๐˜Š๐˜ณ๐˜บ๐˜ฑ๐˜ต๐˜ฐ๐˜จ๐˜ณ๐˜ข๐˜ฑ๐˜ฉ๐˜บ: Preparing for ๐˜๐—ต๐—ฒ ๐—ก๐—ฒ๐˜…๐˜ ๐—–๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐—˜๐—ฟ๐—ฎ Quantum computers are approaching, and with them comes a threat to traditional encryption like RSA and ECC. At ๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐——, weโ€™re taking action now to ensure your infrastructure stays secure in a post-quantum world. How weโ€™re prepar..

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@eon01 shared a post, 1ย month, 2ย weeks ago
Founder, FAUN.dev

16 Things Anthropic Didn't Want You to Know About Claude Code

Claude Code

Earlier today (March 31, 2026), Anthropic accidentally shipped the full source code of Claude Code inside an npm package. The 512,000 lines of TypeScript have since been picked apart by the developer community, and what's inside is more revealing than anyone expected.

Claude Code Leaked
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@kala shared an update, 1ย month, 2ย weeks ago
FAUN.dev()

Anthropic Accidentally Leaks Claude Code's Entire Source Code via npm

#Claude ...ย  #Claude ...ย  #NPMย  #Anthrop...ย  #AIย 
Claude Code

Anthropic shipped a source map file inside the latest npm release of Claude Code - and with it, the full source code of its flagship AI coding CLI. The leak exposed 512,000 lines of TypeScript across 1,900 files, 43 built-in tools, 44 feature flags, 26 hidden slash commands, and over 120 secret environment variables. It is one of the most detailed accidental exposures of a commercial AI product's internals to date.

Claude Code leaked source
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@himanshu shared a post, 1ย month, 2ย weeks ago

What if your backend is failing but your UI looks perfectly fine?

Struggling with hidden bugs? Learn how application programming interface testing ensures accurate data flow, security, and performance.

api testing
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@cubeapm shared a post, 1ย month, 2ย weeks ago

How OpenTelemetry Helps Teams Change Observability Backends Without Re-Instrumenting Everything

1. OpenTelemetry reduces backend coupling by standardizing how telemetry is generated, described, transported, and processed before it reaches any observability platform.

2. The biggest migration advantage comes from using OpenTelemetry APIs and SDKs, OTLP, and the Collector, which make telemetry pipelines more portable across backends.

3. The Collector is the operational pivot point because it can receive, process, and export telemetry to one or more destinations from a centralized control layer.

4. OpenTelemetry does not eliminate backend migration work, since teams still need to validate dashboards, alerts, queries, retention rules, and other backend-specific workflows.

5. The safest migration approach is incremental: standardize telemetry first, validate both old and new backends, then cut over gradually.

How OpenTelemetry Helps Teams Change Observability Backends Without Re-Instrumenting Everything
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@laura_garcia shared a post, 1ย month, 2ย weeks ago
Software Developer, RELIANOID

๐—๐—ฎ๐—ฝ๐—ฎ๐—ป ๐—œ๐—ง & ๐——๐—ซ ๐—ช๐—ฒ๐—ฒ๐—ธ!

๐Ÿš€ ๐—›๐—ฒ๐—ฎ๐—ฑ๐—ถ๐—ป๐—ด ๐˜๐—ผ ๐—ง๐—ผ๐—ธ๐˜†๐—ผ ๐—ณ๐—ผ๐—ฟ ๐—๐—ฎ๐—ฝ๐—ฎ๐—ป ๐—œ๐—ง & ๐——๐—ซ ๐—ช๐—ฒ๐—ฒ๐—ธ! ๐—ฅ๐—˜๐—Ÿ๐—œ๐—”๐—ก๐—ข๐—œ๐—— will be at the 23rd Information Security Expo Spring 2026 from April 8โ€“10 at Tokyo Big Sight โ€“ ๐—๐—ฎ๐—ฝ๐—ฎ๐—ปโ€™๐˜€ ๐—น๐—ฎ๐—ฟ๐—ด๐—ฒ๐˜€๐˜ ๐˜€๐—ต๐—ผ๐˜„๐—ฐ๐—ฎ๐˜€๐—ฒ ๐—ณ๐—ผ๐—ฟ ๐—ฐ๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐˜€๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป๐˜€. Come see how our advanced ADC and secure application delivery solutions help protect critical infr..

japan it dx week april 26 relianoid
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@laura_garcia shared a post, 1ย month, 2ย weeks ago
Software Developer, RELIANOID

Maritime Cybersecurity Is Still Too Weak โ€“ And the Risks Are Growing

๐Ÿšข Maritime Cybersecurity Is Still Too Weak โ€“ And the Risks Are Growing As ships become smarter, greener, and more connected, their cyber defenses remain worryingly outdated. ๐Ÿ“‰ Over 80% of shipowners have faced cyberattacks in the past 3 years ๐Ÿ’ธ Average cost per attack: $3.1 million ๐ŸŽฃ Phishing causes..

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@pramod_kumar_0820 shared a link, 1ย month, 2ย weeks ago
Software Engineer, Teknospire

Java 26 Released ๐Ÿš€: Whatโ€™s New, What Matters & Why Itโ€™s Faster Than Ever

Java 26 (March 2026) is out, and while itโ€™s not a headline-heavy release, it brings meaningful improvements where it counts โ€” performance, networking, and concurrency.

Some notable updates:

๐ŸŒ HTTP/3 support (QUIC-based, lower latency, better reliability)

๐Ÿงต Structured Concurrency (Preview) for safer multithreading

โšก JVM & GC optimizations improving startup and runtime performance

๐Ÿง  Continued evolution of pattern matching

๐Ÿงช Vector API (Incubator) for high-performance workloads

This release is less about flashy features and more about incremental improvements that impact real-world systems.

java_26_released_version
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@mmaksimovic shared a link, 1ย month, 2ย weeks ago

Monitoring Your App Without Running Your Own Prometheus Stack

When to use Prometheus and when to look for other solutions.

Monitoring Your App Without Running Your Own Prometheus Stack
AIStor is an enterprise-grade, high-performance object storage platform built for modern data workloads such as AI, machine learning, analytics, and large-scale data lakes. It is designed to handle massive datasets with predictable performance, operational simplicity, and hyperscale efficiency, while remaining fully compatible with the Amazon S3 API. AIStor is offered under a commercial license as a subscription-based product.

At its core, AIStor is a software-defined, distributed object store that runs on commodity hardware or in containerized environments like Kubernetes. Rather than being limited to traditional file or block interfaces, it exposes object storage semantics that scale from petabytes to exabytes within a single namespace, enabling consistent, flat addressing of vast datasets. It is engineered to sustain very high throughput and concurrency, with examples of multi-TiB/s read performance on optimized clusters.

AIStor is optimized specifically for AI and data-intensive workloads, where throughput, low latency, and horizontal scalability are critical. It integrates broadly with modern AI and analytics tools, including frameworks such as TensorFlow, PyTorch, Spark, and Iceberg-style table engines, making it suitable as the foundational storage layer for pipelines that demand both performance and consistency.

Security and enterprise readiness are central to AIStorโ€™s design. It includes capabilities like encryption, replication, erasure coding, identity and access controls, immutability, lifecycle management, and operational observability, which are important for mission-critical deployments that must meet compliance and data protection requirements.

AIStor is positioned as a platform that unifies diverse data workloads โ€” from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets โ€” within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.