Building Zonal Resiliency for Etsy’s Kafka Cluster: Part 1 – A Guide by Etsy Engineering
Introduction:
In 2018, Etsy made the decision to migrate to Google Cloud Platform, choosing it as their provider. They embarked on a major redesign to host their Kafka brokers on Google’s managed Kubernetes (GKE) in order to benefit from features like on-demand capacity scaling and multi-zone/region resilience. As Etsy’s Kafka cluster grew in importance, they realized the limitations of their initial architecture that operated in a single availability zone. They needed a more resilient design to prevent outages and data loss. This post discusses how Etsy achieved zero downtime and successfully migrated their Kafka cluster to a multi-zone design, ensuring zonal resilience. They also share their optimization plans to address increased inter-zone network costs.
Full Article: Building Zonal Resiliency for Etsy’s Kafka Cluster: Part 1 – A Guide by Etsy Engineering
Etsy Successfully Migrates Kafka Cluster to Google Cloud’s Multizone Architecture for Improved Resilience and Cost Optimization
In 2018, Etsy made the decision to migrate to the cloud using Google Cloud Platform as its provider. This migration involved a major redesign, including hosting their Kafka brokers and clients on Google’s managed Kubernetes (GKE). Over time, Etsy realized the need for increased resilience and began implementing a multizone architecture for their Kafka cluster.
The Challenges of a Single-Zone Architecture
Initially, Etsy operated their Kafka cluster in a single availability zone to save on costs. However, this approach posed limitations and vulnerabilities. A Kafka outage could result in stale search results, negatively impacting buyers, sellers, and Etsy’s revenue. To address these concerns, Etsy decided to reevaluate their architecture.
Designing a Multizone Architecture for Kafka
After thorough research and experimentation, Etsy developed a plan to make their Kafka cluster resilient to zonal failures. The goal was to ensure zero downtime during the migration process. The new design involved running Kafka brokers in three different zones within the GKE cluster. Kubernetes Pod Topology Spread Constraints were applied to evenly distribute the brokers across zones. Additionally, topic partition replicas were evenly distributed based on the zone where the broker was running.
Ensuring Zero Downtime During Migration
One of the main challenges during the migration was moving the broker Pods to their correct zones without causing downtime or data loss. The disks and PVCs (Persistent Volume Claims) for the pods were zonal resources, which meant they could only be accessed locally. To overcome this challenge, Etsy utilized Google’s disk snapshotting feature. The process involved creating a base snapshot of the broker disk while it was still running, halting the broker, creating a final snapshot, creating a new disk from the final snapshot in the correct zone, deleting the original disk, recreating the StatefulSet, and waiting for the cluster health to return to normal. This process was repeated for each broker.
Relocating Topic Partitions
Unlike broker relocation, Kafka does not provide automatic partition relocation. Etsy had to manually relocate topic partitions to ensure an even distribution across all zones. This involved generating a list of partitions needing relocation, generating a new partition assignment plan in JSON form, and applying the partition assignments using the Kafka CLI tool. The data migration was throttled to prevent overwhelming the cluster and ensure a successful migration.
Testing and Validation in Production
In 2021, Etsy had the opportunity to test and validate their multizone Kafka design during a company-wide initiative to understand zonal resilience. They brought down an entire zone, a third of the Kafka cluster, in a production environment. The impact was minimal and temporary, as client requests automatically switched to still-available brokers.
Cost Optimization and Conclusion
Etsy initially believed that the cost increase from implementing a multizone architecture would be minimal. By eliminating regional disks and relying on Kafka’s inter-zone replication, they were able to optimize costs. The successful migration of their Kafka cluster to a multizone architecture has provided Etsy with increased resilience and minimized the risk of downtime and data loss.
Overall, Etsy’s experience with migrating their Kafka cluster to Google Cloud’s multizone architecture showcases the importance of resilience, cost optimization, and careful planning in ensuring a smooth and successful migration to the cloud.
Summary: Building Zonal Resiliency for Etsy’s Kafka Cluster: Part 1 – A Guide by Etsy Engineering
In 2018, Etsy made the decision to migrate to the Google Cloud Platform, which required a major redesign to host their Kafka brokers. As their Kafka cluster grew in importance and limitations of manual zone evacuation became apparent, they developed a design to make the cluster resilient to zonal failures. The new design involved running Kafka brokers in three different zones and distributing topic partition replicas evenly. They successfully migrated the Kafka cluster without data loss or downtime using Google’s disk snapshotting feature. The design was put to the test during a company-wide initiative and proved to be resilient. Although there was a cost increase, it was minimal compared to the benefits gained.
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