Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.23707 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913156733861888 |
|---|---|
| author | Dehigama, Dilina Jesalpura, Shyam Schall, David Katsarakis, Antonios Kogias, Marios Kumar, Rakesh Grot, Boris |
| author_facet | Dehigama, Dilina Jesalpura, Shyam Schall, David Katsarakis, Antonios Kogias, Marios Kumar, Rakesh Grot, Boris |
| contents | Online services strive to maintain application responsiveness even when the traffic is unpredictable and fluctuating. Today's online services are commonly deployed as chains of microservices, each microservice packaged as one or more containers inside virtual machines (VMs). While performant and affordable when the load is steady, VM-based deployments are known to be slow to scale when the load spikes, resulting in degraded performance for end-users of the service. To avoid such performance degradations, service providers can over-provision their deployments; however, such a strategy is costly and inefficient, leaving resources under-utilized for extended periods.
To address the challenge of unpredictable load spikes, we propose Flare, a hybrid microservice architecture that combines VMs with serverless computing. Flare utilizes VMs to cost-effectively handle steady workloads and leverages serverless elasticity to absorb traffic spikes. When a spike occurs, Flare detects which specific service(s) are overloaded and shifts the excess load of only those services to serverless, thus minimizing the cost overhead. Flare seamlessly integrates into existing auto-scaling and serverless infrastructure, requiring minimal changes to the control plane and no modifications to the application. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_23707 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Flare: Leveraging Serverless Elasticity to Absorb Microservice Load Spikes Dehigama, Dilina Jesalpura, Shyam Schall, David Katsarakis, Antonios Kogias, Marios Kumar, Rakesh Grot, Boris Distributed, Parallel, and Cluster Computing Online services strive to maintain application responsiveness even when the traffic is unpredictable and fluctuating. Today's online services are commonly deployed as chains of microservices, each microservice packaged as one or more containers inside virtual machines (VMs). While performant and affordable when the load is steady, VM-based deployments are known to be slow to scale when the load spikes, resulting in degraded performance for end-users of the service. To avoid such performance degradations, service providers can over-provision their deployments; however, such a strategy is costly and inefficient, leaving resources under-utilized for extended periods. To address the challenge of unpredictable load spikes, we propose Flare, a hybrid microservice architecture that combines VMs with serverless computing. Flare utilizes VMs to cost-effectively handle steady workloads and leverages serverless elasticity to absorb traffic spikes. When a spike occurs, Flare detects which specific service(s) are overloaded and shifts the excess load of only those services to serverless, thus minimizing the cost overhead. Flare seamlessly integrates into existing auto-scaling and serverless infrastructure, requiring minimal changes to the control plane and no modifications to the application. |
| title | Flare: Leveraging Serverless Elasticity to Absorb Microservice Load Spikes |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2605.23707 |