In this lesson, you will learn how to isolate the specific resource consumption footprint of individual tenants sharing a single Linux container host using kernel-level observability.
When multiple tenants share a host, standard top or ps outputs often blur the lines between workloads. To truly understand the footprint of an individual tenant, we must move beyond process IDs and correlate resource usage with control groups (cgroups).
Tracking Cgroup-Specific Footprints
In a multi-tenant environment, the kernel tracks resource boundaries via cgroups. To analyze the footprint, we use eBPF programs to attach probes to scheduler events or memory allocation functions, filtering them by the cgroup_id. By mapping these kernel events to a specific tenant’s cgroup path, you can isolate exactly how much CPU time or memory pressure a specific tenant is exerting on the shared host.
For instance, you can trace task migration or page faults while restricting the output to a specific cgroup hierarchy:
SEC("tracepoint/sched/sched_switch")
int trace_sched_switch(struct trace_event_raw_sched_switch *ctx) {
u64 cgroup_id = bpf_get_current_cgroup_id();
// Only capture data if the event belongs to our target tenant
if (cgroup_id != TARGET_TENANT_ID)
return 0;
// Record resource consumption event
// ...
return 0;
}
Challenges of Shared Resources
The primary difficulty in multi-tenancy is "noisy neighbor" interference at the hardware level—specifically L3 cache contention and memory bandwidth saturation. While cgroups limit the amount of resources, they don't always explain the performance degradation caused by shared hardware buffers.
To solve this, we correlate our per-tenant telemetry with hardware performance counters (PMUs). By using perf events scoped to cgroups, we can determine if Tenant A's intensive memory operations are stalling Tenant B's CPU execution pipeline, even if both are within their allocated cgroup limits. When observing this data, always look for high "cache miss" rates that correlate strictly with the activation periods of one specific tenant; this is your smoking gun for architectural resource contention in a shared environment.
Key Takeaway: Effective multi-tenant isolation requires mapping low-level kernel events to specific cgroup identifiers to distinguish between legitimate resource usage and cross-tenant performance interference.