Service Outage Report - 14th December 2024 to 13th January 2025

Dear valued customers,

We want to address the recent service interruption that affected our platform from December 15th, 2024 to January 13th, 2025. First and foremost, we sincerely apologize for the obvious inconvenience this would have caused to your veterinary practice operations over such a long period. While we got in touch with most of you through emails and phone calls and explained the situation, we find it fitting to issue a public apology here.

What Happened

During our scheduled infrastructure upgrade to implement advanced large language models (LLMs) for veterinary diagnostics, we encountered a critical issue with our data consistency layer. The new AI models required significantly more computational resources than anticipated, leading to severe database contention. This, combined with an unforeseen interaction between our caching layer and the new vector embeddings storage, caused a cascading failure across our microservices architecture.

The situation was further complicated by corrupted indexes in our vector database, which stored crucial embeddings for our AI models. What made this particularly challenging was that these embeddings were derived from encrypted sensitive health records of pets - including diagnostic images, lab results, and treatment histories. Our encryption architecture, which uses a combination of homomorphic encryption for AI processing and standard encryption for storage, meant that we couldn't simply rebuild the indexes. Each record needed to be carefully decrypted, validated, and re-encrypted while maintaining our strict compliance with veterinary data protection standards.

As a startup with a small team of just three engineers, this crisis stretched our resources to the absolute limit. While we had contingency plans for various scenarios, we hadn't anticipated a situation that would require simultaneous expertise in AI infrastructure, cryptography, and veterinary data compliance. The scope of the problem demanded specialized knowledge in multiple domains, but our financial constraints as an early-stage startup meant we couldn't immediately hire the additional experts we needed.

Actions Taken

Our small engineering team worked in shifts around the clock to address these complex issues, while also maintaining essential services for data access:

• Initiated a complete rebuild of our vector database indexes, requiring verification of over 50 million encrypted embeddings against our source documents - a process that took significantly longer due to the necessary decryption and re-encryption cycles
• Developed a custom data recovery tool that could handle our encrypted data format while maintaining HIPAA-style compliance for veterinary records
• Redesigned our entire data pipeline architecture to handle the increased load from the new AI models while maintaining encryption throughout the processing pipeline
• Implemented a new distributed caching system using Redis Cluster with encryption at rest to better handle the AI model's memory requirements
• Developed and deployed custom monitoring solutions for vector similarity search operations that could work with encrypted data
• Performed a thorough audit of all AI model interactions with our PostgreSQL database to optimize query patterns while maintaining our encryption guarantees
• Rebuilt our Kubernetes cluster with dedicated nodes for AI workloads and enhanced security measures

Improvements Made

This incident led to a complete overhaul of our infrastructure, achieved through careful resource allocation and strategic technical decisions:

• Migrated to a new vector database solution (Weaviate) with improved stability and native encryption support
• Implemented automatic failover using multi-region Kubernetes clusters with enhanced security measures
• Developed a custom load balancing solution specifically designed for encrypted AI workloads
• Added real-time monitoring of vector embedding quality and database performance metrics with encryption-aware health checks
• Established a new disaster recovery protocol with automated backup verification and encryption key rotation
• Created separate production environments for AI inference and training with isolated security boundaries

Moving Forward

While this outage was significantly longer than any we've experienced before, it has resulted in a much more robust and scalable system. Our new infrastructure can now handle 10x the previous load, with improved failover capabilities and better isolation between critical systems. We've also implemented a comprehensive testing framework that simulates high-load scenarios and potential failure modes, particularly focused on our encrypted data handling.

To prevent similar incidents, we've created a detailed incident response playbook specifically for AI-related issues and implemented automated canary deployments for all infrastructure changes.

As compensation for this extended outage, we will be providing:

• A three-month extension to all current subscriptions
• Priority access to our new AI features once they're released
• Dedicated support channels for the next 6 months
• Free access to our upcoming premium AI diagnostics module

Thank you for your continued trust in Cape.Vet.

- The Cape.Vet Team