"AutoMQ's cloud-native architecture enabled us to run Kafka consistently across AWS, GCP, and Alibaba Cloud. The diskless design eliminated our scaling bottlenecks and cut infrastructure costs in half."
Michael Zhang
VP of Cloud Platform Engineering
Bambu Lab
The Challenge
Bambu Lab operates a cloud-based 3D printing platform serving makers worldwide. As a Kubernetes-native company with multi-cloud deployments, they faced critical challenges with traditional Apache Kafka:
Insufficient Elasticity
The 3D printing cloud platform is built entirely on Kubernetes and deployed across multiple cloud providers. However, traditional Kafka's reliance on local disks and stateful brokers made it incompatible with cloud-native scaling patterns. True second-level auto-scaling remained impossible, creating operational friction in a containerized environment.
Fragmented Multi-Cloud Operations
Each cloud environment required different Kafka cluster configurations and operational procedures. Scaling, migration, and disaster recovery workflows couldn't be standardized, significantly increasing operational complexity and blocking the company's multi-cloud strategy.
Why AutoMQ
Bambu Lab chose AutoMQ for its true cloud-native architecture and multi-cloud consistency:
Diskless Compute-Storage Separation
AutoMQ's S3-based diskless architecture completely decouples compute from storage. Brokers are fully stateless, handling only computation while all data persists in object storage.
- Scaling no longer requires partition data migration, reducing operations from hours to seconds
- Dramatically improved cluster elasticity and stability
- Perfect fit for Kubernetes-native workload patterns
Kubernetes & Multi-Cloud Native
AutoMQ is purpose-built for Kubernetes and EKS, treating stateless brokers as standard cloud-native services that can be scheduled and scaled like any other workload.
- Single Kafka technology stack runs consistently across all cloud providers
- Unified monitoring, scaling, and incident response procedures
- Eliminated cloud-specific operational complexity
- Accelerated multi-cloud strategy execution
The AutoMQ engineering team worked alongside Bambu Lab's platform team to ensure seamless integration with their existing Kubernetes infrastructure and multi-cloud architecture.
The Results
Since adopting AutoMQ, Bambu Lab has achieved significant improvements in both operational efficiency and system reliability:
Key Metrics
Unified experience across AWS, GCP, Alibaba Cloud
Reduction in Kafka infrastructure costs
Scaling time vs. hours traditionally
Kafka API compatibility
Enhanced Stability
Operational tasks like node restarts, scaling operations, and version upgrades now have minimal impact on production workloads. The cluster runs more smoothly under high-concurrency IoT streaming scenarios.
Operational Efficiency
Scaling evolved from traditional Kafka's "lengthy data migration + high-risk operations" to AutoMQ's "standardized, automated second-level elasticity." Overall operational complexity and risk decreased significantly.
Beyond the numbers, AutoMQ enabled Bambu Lab to fully embrace their cloud-native and multi-cloud vision, treating Kafka as just another stateless microservice rather than a special stateful infrastructure component requiring dedicated operational expertise.
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