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Runpod Blog.

DeepSeek V4 in the wild, and how to run it on Runpod New Runpod datacenter now live: AP-IN-1 Track GPU spend across your team with Cost Centers The GPU supply supercycle is here. Here’s what AI builders need to know. Community Spotlight: One-click AI image and video generation on Runpod with SwarmUI | Runpod Blog Community Spotlight: LoRA Pilot Data Prep to Inference Introducing the Runpod Assistant: Manage Your Cloud GPU Resources with Natural Language OpenAI's Parameter Golf: Train the Best Language Model That Fits in 16MB on Runpod LLM inference optimization: techniques that actually reduce latency and cost Pruna P-Video and Vidu Q3 public endpoints now available on Runpod Runpod brand spelling guide Quickstart - Runpod Documentation The AI market looks nothing like the narrative Training StyleGAN3 with Vision-Aided GAN on Runpod KoboldAI – The Other Roleplay Front End, And Why You May Want to Use It How to Connect Cursor to LLM Pods on Runpod for Seamless AI Dev Community Spotlight: How AnonAI Scaled Its Private Chatbot Platform with Runpod Prompt Scheduling with Disco Diffusion on Runpod Runpod's Latest Innovation: Dockerless CLI for Streamlined AI Development Run Your Own AI from Your iPhone Using Runpod Introducing Flash: Run GPU workloads on Runpod Serverless: No Docker required Use Claude Code with your own model on Runpod: No Anthropic account required Avoid Errors by Selecting the Proper Resources for Your Pod What hackers built on Runpod at TreeHacks 2026 Easily Back Up and Restore Your Pod with Cloud Sync + Backblaze B2 The Complete Guide to GPU Requirements for LLM Fine-Tuning AI Guides, Tutorials & GPU Infrastructure Insights | Runpod Your first Claude Code project within Runpod: a complete setup guide 10 billion Serverless requests and counting Building for resilience: Runpod’s response to the AWS us-east-1 outage How to Connect Google Colab to Runpod Founder Series #1: The Runpod Origin Story AMD MI300X vs. NVIDIA H100: Mixtral 8x7B Inference Benchmark How to Run the FLUX Image Generator with ComfyUI on Runpod Run Llama 3.1 405B with Ollama on Runpod: Step-by-Step Deployment How to Run FLUX Image Generator with Runpod (No Coding Needed) How to Use 65B+ Language Models on Runpod Deploy Llama 3.1 with vLLM on Runpod Serverless: Fast, Scalable Inference in Minutes Open Source Video & LLM Roundup: The Best of What’s New Run vLLM on Runpod Serverless: Deploy Open Source LLMs in Minutes Introduction to vLLM and PagedAttention New update to Github integration: release rollback! | Runpod Blog A note to the developers who built Runpod with us Deploy ComfyUI as a Serverless API Endpoint Setting up Slurm on Runpod Clusters: A Technical Guide Building an OCR System Using Runpod Serverless From No-Code to Pro: Optimizing Mistral-7B on Runpod for Power Users Lessons While Using Generative Language and Audio For Practical Use Cases Runpod RoundUp 3 – AI Music and Stock Sound Effect Creation New Navigational Changes To Runpod UI Use alpha_value To Blast Through Context Limits in LLaMa-2 Models Runpod Roundup 5 – Visual/Language Comprehension, Code-Focused LLMs, and Bias Detection Runpod is Proud to Sponsor the StockDory Chess Engine Runpod Roundup 4 – Open Source LLM Evaluators, 3D Scene Reconstruction, Vector Search Meta and Microsoft Release Llama 2 as Open Source SuperHot 8k Token Context Models Are Here For Text Generation How to Manage Funding Your Runpod Account How to Run a "Hello World" on Runpod Serverless Runpod AI field notes: December 2025 Faster GitHub Builds: Major Performance Improvements to Our Automated Integration Partnering with Defined AI to Bridge the Data Wealth Gap How to Run Serverless AI and ML Workloads on Runpod How to fine-tune a model using Axolotl Transcribe and translate audio files with Faster Whisper Runpod Achieves SOC 2 Type II Certification: Continuing Our Compliance Journey Orchestrating GPU workloads on Runpod with dstack Exploring Runpod Serverless: Create Workers From Templates DeepSeek V3.1: A Technical Analysis of Key Changes from V3-0324 Deep Cogito Releases Suite of LLMs Trained with Iterative Policy Improvement Wan 2.2 Releases With a Plethora Of New Features Iterative Refinement Chains with Small Language Models The New Runpod.io: Clearer, Faster, Built for What’s Next Introducing Clusters: On-Demand Multi-Node AI Compute Run DeepSeek R1 on Just 480GB of VRAM How Do I Transfer Data Into My Runpod? Spot vs. On-Demand Instances: What’s the Difference? Deploy GitHub Repos to Runpod with One Click Run GGUF Quantized Models Easily with KoboldCPP on Runpod How to Work with GGUF Quantizations in KoboldCPP Introducing Better Forge: Spin Up Stable Diffusion Pods Faster Supercharge Your LLMs with SGLang: Boost Performance and Customization Mastering Serverless Scaling on Runpod: Optimize Performance and Reduce Costs RAG vs. Fine-Tuning: Which Is Best for Your LLM? Run Larger LLMs on Runpod Serverless Than Ever Before – Llama-3 70B (and beyond!) 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Encrypted Volumes on Runpod: Protect Your Data at Rest
Zhen Lu · 2026-01-20 · via Runpod Blog.

Encrypted Volumes on Runpod: Protect Your Data at Rest

At Runpod, we're always looking to offer more value to our clients. One of the things we take seriously is security. To this end, we have implemented the ability to encrypt your persistent volumes.

Runpod now offers encrypted volumes! This means that you have the option to choose your level of data security!

There are several benefits to using encrypted volumes:

  • Your data will be more secure from cyber criminals and hackers.
  • Encrypted volumes can help prevent data breaches.
  • Your data will be more resistant to malware and other malicious software.

There are also some drawbacks to using encrypted volumes:

  • Encrypted volumes can dramatically reduce performance.
  • They can also be more difficult to manage and troubleshoot.

You can enable volume encryption by checking the "Encrypt Volume" checkbox during deploy.

Runpod deployment form for an RTX A6000 with Encrypt Volume checked and the Runpod PyTorch template selected

Note that you can only do this during the deploy step. You cannot change encryption options after the pod is already deployed. We will handle the encryption keys for you if you deploy through the web platform. If you would prefer to choose your own encryption key, you can deploy using the API.

If you have sensitive data that you need to protect, we recommend using encrypted volumes. However, if you do not have sensitive data or if you are unwilling to trade performance for security, we recommend using non-encrypted volumes.

If you have any questions about encrypted volumes or any other features of Runpod, please contact us through Discord, chat, or email. We would be happy to help!

Author profile: Zhen Lu

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