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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 How to Connect Google Colab to Runpod
Building for resilience: Runpod’s response to the AWS us-...
Mo King · 2026-02-18 · via Runpod Blog.

Last week on Monday, AWS experienced a significant outage affecting multiple services in the us-east-1 region. The disruption impacted thousands of sites and millions of users across the internet, and Runpod was certainly not immune to these effects.

During the outage, Runpod console availability was impacted as our upstream provider, Vercel, depended on this region. Serverless endpoints continued to receive requests but couldn’t process them due to the impact on our worker management microservice. Users experienced issues with Pod provisioning and access, while others encountered extended delay times throughout the platform. Our payment processing system was also impacted during this period, and we took steps after the fact to ensure customers were not charged for resources that they could not utilize.

Understanding our dependencies

Some customers questioned why Runpod was impacted by an AWS outage at all. While Runpod has over 40 data centers designed for AI application development and deployment, we leverage AWS infrastructure to host critical portions of our control plane. This architecture has enabled us to scale our web application effectively, but it also means that AWS availability directly impacts our platform's operational status.

But we want to underline the fact that Runpod's GPU compute resources remain entirely independent from our control plane. Pod workloads remained operational during the AWS outage, and even when the Runpod UI was unavailable, your Pods, endpoints, and clusters remained intact and secure. Once connectivity was restored, these resources returned to their normal operational state within without data loss or configuration changes. Similarly for Serverless, as soon as the coordination microservice was back online, workers could resume processing requests as normal.

Immediate infrastructure improvements

Following the outage, our engineering team immediately began implementing critical redundancies for our infrastructure. Within 72 hours of the incident, Runpod's engineering team deployed our core services across multiple AWS regions, and if AWS suffers another outage like this, our platform is prepared to failover to a healthy region to stay online.

We also enhanced our Serverless platform's resilience to control plane disruptions. If necessary, workers can now use their cached configurations, allowing them to continue accepting and processing requests for an extended period, even if the central service is unavailable. When connection is restored, the workers’ distributed state automatically synchronizes back up with the control plane. This distribution of state reduces the blast radius risk if AWS or any other core internet service suffers another outage.

Our roadmap to resilience

This outage was a painful lesson for us, but a valuable one. While we’re proud of our core design, which separates your compute resources from the control plane to keep your workloads safe, we are far from satisfied. Our long-term roadmap includes transitioning to a partitioned multi-region deployment hosted entirely on Runpod's own provider network, with automated load balancing and failover capabilities.

While we cannot prevent external infrastructure failures, we are committed to building a platform that remains resilient throughout such events. We appreciate your patience during last week’s disruption and we’ll continue providing updates on our progress.

Author profile: Mo King