A Case For Cross-Domain Observability to Debug Performance Issues in Microservices
K, Ranjitha and Tammana, Praveen and Kannan, Pravein Govindan and et al, . (2022) A Case For Cross-Domain Observability to Debug Performance Issues in Microservices. In: 15th IEEE International Conference on Cloud Computing, CLOUD 2022, 10 July 2021 through 16 July 2021, Barcelona.
Text
CLOUD.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy |
Abstract
Many applications deployed in the cloud are usually refactored into small components called microservices that are deployed as containers in a Kubernetes environment. Such applications are deployed on a cluster of physical servers which are connected via the datacenter network.In such deployments, resources such as compute, memory, and network, are shared and hence some microservices (culprits) can misbehave and consume more resources. This interference among applications hosted on the same node leads to performance issues (e.g., high latency, packet loss) in the microservices (victims) followed by a delayed or low-quality response. Given the highly distributed and transient nature of the workloads, it's extremely challenging to debug performance issues. Especially, given the nature of existing monitoring tools, which collect traces and analyze them at individual points (network, host, etc) in a disaggregated manner.In this paper, we argue toward a case for a cross-domain (network & host) monitoring and debugging framework which could provide the end-to-end observability to debug performance issues of applications and pin-point the root-cause whether it is on the sender-host, receiver-host or the network. We present the design and provide preliminary implementation details using eBPF (extended Berkeley Packet Filter) to elucidate the feasibility of the system. © 2022 IEEE.
IITH Creators: |
|
||||
---|---|---|---|---|---|
Item Type: | Conference or Workshop Item (Paper) | ||||
Uncontrolled Keywords: | cloud; ebpf; microservices; Observability; performance | ||||
Subjects: | Computer science | ||||
Divisions: | Department of Computer Science & Engineering | ||||
Depositing User: | . LibTrainee 2021 | ||||
Date Deposited: | 20 Sep 2022 11:32 | ||||
Last Modified: | 20 Sep 2022 11:32 | ||||
URI: | http://raiithold.iith.ac.in/id/eprint/10638 | ||||
Publisher URL: | http://doi.org/10.1109/CLOUD55607.2022.00045 | ||||
Related URLs: |
Actions (login required)
View Item |
Statistics for this ePrint Item |