Updates and recent posts about Magika..

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@laura_garcia shared a post, 1 week, 2 days ago

Software Developer, RELIANOID

RELIANOID at CII Delhi International Technology Summit 2025

16–17 December 2025 - New Delhi, India Our team continues a packed December schedule, and we’re excited to add another key event: the CII Delhi International Technology Summit 2025. Focused on “Accelerating the Techade”, this summit brings together industry, government, and research leaders to shape..

CII Delhi International Technology Summit relianoid

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@anjali shared a link, 1 week, 2 days ago

Customer Marketing Manager, Last9

OTel Updates: OpenTelemetry Proposes Changes to Stability, Releases, and Semantic Conventions

OpenTelemetry proposes stability changes: stable-by-default distributions, decoupled instrumentation, and epoch releases for production deployments.

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@laura_garcia shared a post, 1 week, 3 days ago

Software Developer, RELIANOID

deploy the RELIANOID Load Balancer Community Edition v7 on Azure using Terraform

🚀 New Technical Guide Available! You can now deploy the RELIANOID Load Balancer Community Edition v7 on Azure using Terraform in just a few minutes: ✔️ Install prerequisites (Terraform, Azure CLI, SSH keys) ✔️ Use the official Terraform module from the Registry ✔️ Automatically provision all Azure r..

terraform_relianoid_community_azure_img2

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@pixel_og started using tool Thanos , 1 week, 3 days ago.

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@pixel_og started using tool Terraform , 1 week, 3 days ago.

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@pixel_og started using tool Talos Linux , 1 week, 3 days ago.

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@pixel_og started using tool Python , 1 week, 3 days ago.

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@pixel_og started using tool Prometheus , 1 week, 3 days ago.

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@pixel_og started using tool OpenTofu , 1 week, 3 days ago.

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@pixel_og started using tool NixOs , 1 week, 3 days ago.

Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response

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