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@laura_garcia shared a post, 6 months, 2 weeks ago
Software Developer, RELIANOID

🚀 Strengthening Europe’s Cybersecurity in Space

Just in case you missed it last month: The European Space Agency (ESA) has launched its brand-new Cybersecurity Operations Center (C-SOC) to safeguard satellites, mission control systems, and digital assets against growing cyber threats. 🌍 In today’s space-driven world, initiatives like this — suppo..

ESA_Cybersecurity Operations Center
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@laura_garcia shared a post, 6 months, 2 weeks ago
Software Developer, RELIANOID

🔐 Cybersecurity Fundamentals: Defensive, Offensive & Hybrid Approaches 🔐

Cybersecurity isn’t just about deploying tools — it’s about knowing how and when to use the right strategies. Defensive security focuses on prevention with technologies like firewalls, antivirus, access control, and system hardening to reduce exposure. Offensive security takes the attacker’s perspec..

Cibersecurity concepts diagram RELIANOID
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@anjali shared a link, 6 months, 2 weeks ago
Customer Marketing Manager, Last9

What is APM Tracing?

Understand APM tracing to see how a request moves through services, helping you spot delays, errors, and bottlenecks quickly.

apm tracing
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@laura_garcia shared a post, 6 months, 2 weeks ago
Software Developer, RELIANOID

✨ In case you missed it ✨

DDoS attacks in 2025 are bigger, smarter, and easier to launch than ever before. From AI-driven attack strategies to IoT-based botnets, the threat landscape is evolving fast. Our latest blog explains what’s happening now — and how RELIANOID helps organizations stay resilient. 🔗 https://www.relianoid..

Blog DDoS Trends RELIANOID
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@laura_garcia shared a post, 6 months, 3 weeks ago
Software Developer, RELIANOID

SourceForge Favorite Award 🏆

We are proud to share that RELIANOID has been recognized with the SourceForge Favorite Award 🏆 This recognition is granted to only a handful of projects out of more than 500,000 open source projects hosted on SourceForge, based on downloads and user engagement. 👉 With nearly 20 million monthly users..

Sourceforge favorite RELIANOID
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@kkz7777 gave 🐾 to 🚀 RELIANOID is heading to Washington, DC! , 6 months, 3 weeks ago.
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@laura_garcia shared a post, 6 months, 3 weeks ago
Software Developer, RELIANOID

🚀 RELIANOID is heading to Washington, DC!

From September 9–12, 2025, we’ll be at the 16th Billington CyberSecurity Summit — the premier government cybersecurity event gathering 2,500+ leaders and innovators to shape the future of AI, Zero Trust, cloud security, and critical infrastructure protection. Meet our team and discover how RELIANOID..

billington cybersecurity summit washington event
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@idjuric660 shared a post, 6 months, 3 weeks ago
Technical Content Writer, Mailtrap

Send emails with v0 and Mailtrap

Vercel Mailtrap.io

Learn how to integrate Mailtrap with your v0 application to send transactional emails and manage contacts without writing complex code.

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@faun shared a link, 6 months, 3 weeks ago
FAUN.dev()

How Salesforce Delivers Reliable, Low-Latency AI Inference

Salesforce’s AI Metadata Service (AIMS) just got a serious speed boost. They rolled out a multi-layer cache—L1 on the client, L2 on the server—and cut inference latency from 400ms to under 1ms. That’s over 98% faster. But it’s not just about speed anymore. L2 keeps responses flowing even when the b.. read more  

How Salesforce Delivers Reliable, Low-Latency AI Inference
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@faun shared a link, 6 months, 3 weeks ago
FAUN.dev()

We Needed Better Cloud Storage for Python so We Built Obstore

Obstoreis a new stateless object store that skips fsspec-style caching and keeps its API tight and predictable across S3, GCS, and Azure. Sync and async both work. Under the hood? Fast, zero-copy Rust–Python interop. And on small concurrent async GETs, it reportedly crushes S3FS with up to9x better .. read more  

We Needed Better Cloud Storage for Python so We Built Obstore
BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).