A GCP Outage Reignited the Multi-Cloud Debate: Is It Worth the Pain?

When a major cloud provider like Google Cloud Platform (GCP) experiences an outage, the immediate impact is service disruption. But beyond the frantic debugging and status page refreshing, these events often trigger crucial conversations about system architecture and resilience. A recent discussion following a GCP outage did just that, offering a wealth of practical insights for engineers and technical leaders.

The incident began with scattered reports of services timing out on Cloud Run and high latency on Firebase Firestore, primarily in us-east1. Reports quickly expanded to include issues with Google Login, the YouTube API, and general slowness in the EU and Brazil. A common frustration was that the official GCP status page remained "all green" long after problems began, reinforcing the need for independent monitoring.

The Great Resilience Debate: Multi-Cloud vs. Multi-Region

The outage naturally led to a debate on the best strategy for high availability. Is going multi-cloud the ultimate answer?

One perspective strongly advocated for multi-cloud architecture over multi-region, arguing that anything less is "availability theater," especially given recent large-scale outages. The core idea is that relying on a single vendor, even across different regions, leaves you vulnerable to systemic, cloud-wide failures like a bad configuration push.

However, several experienced engineers pushed back with a more pragmatic view, detailing the significant trade-offs of a multi-cloud approach:

• Operational Complexity: Managing infrastructure-as-code (IaC) across different cloud providers is significantly more complex. It requires broader team knowledge and introduces more potential points of failure.
• High Egress Costs: Cloud providers famously charge high fees for data leaving their network. In a multi-cloud setup where data is constantly synced or served across providers, these egress costs can become exorbitant. While solutions like AWS Direct Connect or Google's Direct Interconnect exist, they come with their own high costs and complexity.
• Lowest Common Denominator: To maintain compatibility, development teams must often build for the lowest common denominator of features available on all chosen clouds. This means forgoing powerful, managed, and provider-specific services that could otherwise accelerate development.

A Pragmatic Path to Resilience

A particularly insightful comment came from a former PagerDuty engineer who shared that even their organization, for whom reliability is the core product, moved away from multi-cloud. The immense overhead did not justify the marginal gains in availability. Instead, they found a single-cloud, multi-region strategy provided sufficient reliability.

The consensus among many was a tiered approach to resilience:

1. Start with Multi-AZ: For most applications, designing a system to be resilient across multiple Availability Zones (AZs) within a single region is the most effective first step. It's relatively easy to implement and protects against the most common failures (like hardware issues in a single data center).
2. Consider Multi-Region: If your availability requirements demand it, expanding to a multi-region architecture is the next logical step. This is more complex, introducing challenges around data replication and latency, but protects against region-wide events.
3. Reserve Multi-Cloud for Extreme Cases: A full multi-cloud architecture should be reserved for services where availability is a paramount business requirement and the organization has the resources, talent, and budget to manage the immense associated costs and complexity.