[
https://issues.apache.org/jira/browse/GSOC-291?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Daan updated GSOC-291:
----------------------
Description:
Apache CloudStack currently relies on traditional monitoring tools, which may
lack deep visibility into kernel-level events and networking performance. This
project aims to integrate *eBPF-based monitoring* into CloudStack to provide
lightweight, real-time performance analysis and security auditing.
h2. Benefits to CloudStack
* {*}Improved observability{*}: Gain fine-grained insights into VM performance
metrics.
* {*}Lower overhead{*}: eBPF runs in the kernel and avoids the performance
penalties of user-space monitoring tools.
* {*}Enhanced security auditing{*}: Detect and log anomalies in system
behavior.
h2. Deliverables
* Implement eBPF programs to track:
** VM CPU usage
** Memory consumption
** Disk I/O metrics
** Network traffic analysis
* Develop a CloudStack-compatible API or CLI for retrieving eBPF-generated
insights.
* Provide visualization support using Prometheus/Grafana.
* Write documentation for setup and usage.
h2. Expected Outcome
A robust eBPF-based monitoring solution integrated into CloudStack, offering
real-time performance insights with minimal overhead.
ref. cloudstack issue: [https://github.com/apache/cloudstack/issues/10415]
This project is marked as part-time, but the scope can be extended to
full-time. This depends largely on whether the full amount of metrics to track
is implemented or only one, as a proof of concept.
was:
Apache CloudStack currently relies on traditional monitoring tools, which may
lack deep visibility into kernel-level events and networking performance. This
project aims to integrate *eBPF-based monitoring* into CloudStack to provide
lightweight, real-time performance analysis and security auditing.
h2. Benefits to CloudStack
* {*}Improved observability{*}: Gain fine-grained insights into VM performance
metrics.
* {*}Lower overhead{*}: eBPF runs in the kernel and avoids the performance
penalties of user-space monitoring tools.
* {*}Enhanced security auditing{*}: Detect and log anomalies in system
behavior.
h2. Deliverables
* Implement eBPF programs to track:
** VM CPU usage
** Memory consumption
** Disk I/O metrics
** Network traffic analysis
* Develop a CloudStack-compatible API or CLI for retrieving eBPF-generated
insights.
* Provide visualization support using Prometheus/Grafana.
* Write documentation for setup and usage.
h2. Expected Outcome
A robust eBPF-based monitoring solution integrated into CloudStack, offering
real-time performance insights with minimal overhead.
ref. cloudstack issue: https://github.com/apache/cloudstack/issues/10415
> Enhancing CloudStack Monitoring with eBPF
> -----------------------------------------
>
> Key: GSOC-291
> URL: https://issues.apache.org/jira/browse/GSOC-291
> Project: Comdev GSOC
> Issue Type: Improvement
> Reporter: Daan
> Priority: Major
> Labels: CloudStack, gsoc, gsoc2025, mentor, part-time
>
> Apache CloudStack currently relies on traditional monitoring tools, which may
> lack deep visibility into kernel-level events and networking performance.
> This project aims to integrate *eBPF-based monitoring* into CloudStack to
> provide lightweight, real-time performance analysis and security auditing.
> h2. Benefits to CloudStack
> * {*}Improved observability{*}: Gain fine-grained insights into VM
> performance metrics.
> * {*}Lower overhead{*}: eBPF runs in the kernel and avoids the performance
> penalties of user-space monitoring tools.
> * {*}Enhanced security auditing{*}: Detect and log anomalies in system
> behavior.
> h2. Deliverables
> * Implement eBPF programs to track:
> ** VM CPU usage
> ** Memory consumption
> ** Disk I/O metrics
> ** Network traffic analysis
> * Develop a CloudStack-compatible API or CLI for retrieving eBPF-generated
> insights.
> * Provide visualization support using Prometheus/Grafana.
> * Write documentation for setup and usage.
> h2. Expected Outcome
> A robust eBPF-based monitoring solution integrated into CloudStack, offering
> real-time performance insights with minimal overhead.
> ref. cloudstack issue: [https://github.com/apache/cloudstack/issues/10415]
>
> This project is marked as part-time, but the scope can be extended to
> full-time. This depends largely on whether the full amount of metrics to
> track is implemented or only one, as a proof of concept.
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