The Tool Desk
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Use repeated Linux CPU samples to find out whether a slowdown comes from a busy process, a local CPU limit, I/O wait, or CPU time unavailable to your virtual machine. Guest-level metrics can reveal signs of host contention, but they cannot identify a particular neighboring tenant. If the pattern persists, preserve timestamped evidence and ask your hosting provider to investigate.
Collect samples while the slowdown is happening
Record the time users observe latency alongside command output and relevant application measurements. A single snapshot may capture a brief spike; repeated interval samples help distinguish one from sustained pressure. The commands below show live or interval measurements. To review an incident later, retain their output through your existing logging or monitoring setup.
Inspect the overall system and busiest processes with top
Run top during the incident. It provides a dynamic view of system summaries and processes. Check the CPU-state summary, then sort the process list by CPU to identify candidates. Use its per-CPU display if an aggregate average might hide one saturated core. Process CPU percentages are measured over the elapsed time since the last screen update; depending on display mode, a multithreaded process can exceed 100%.
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Measure CPU states over time with vmstat
Run vmstat 1 for repeated one-second reports, or choose an interval and count suited to the incident. Its first report is an average since boot; subsequent reports reflect the specified interval. Read these fields separately:
us: time running user-space code.sy: time running kernel code.id: idle time.wa: time idle while I/O is outstanding.st: virtual CPU time unavailable while the hypervisor services another virtual processor.
High I/O wait is not the same as a CPU-intensive process: it describes idle time while I/O is outstanding. Likewise, steal time is distinct from time the guest spends executing user or system code. The vmstat manual documents its report fields and interval behavior.
Check individual CPUs with mpstat
If pressure may be concentrated on one processor, run mpstat -P ALL 1. It reports per-processor activity as well as global averages, including %steal. The command is provided by the sysstat package, so it may need to be installed for your distribution. See the mpstat manual for options and field definitions.
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Separate guest workload from local CPU throttling
Investigate processes before blaming a neighbor
If a process repeatedly uses CPU, inspect its command, user and threads, then relate it to the service or workload it belongs to. Thread-level and per-CPU views can help when a multithreaded application or uneven CPU pressure makes a process-level snapshot misleading. A guest-visible process is something you can investigate directly; a neighbor’s processes are not.
Check cgroup usage, limits and ancestry
For the affected service or container, check its cgroup membership and the relevant counters. On cgroup v2 systems, cpu.stat reports CPU usage and, when the CPU controller is enabled, fair-scheduler bandwidth fields such as nr_throttled and throttled_usec. cpu.stat.local can report throttling on the cgroup’s own runqueues, including effects inherited from ancestor bandwidth limits. Availability and interpretation depend on the active cgroup setup and controller configuration.
Usage counters record CPU time consumed; throttling counters describe effects of a bandwidth limit. Check configured limits and parent groups before interpreting throttling as competition from another tenant. Cgroups are hierarchical: a limit higher in the tree can affect a workload even if its own cgroup has no local limit. The cgroups(7) manual describes the hierarchy and resource controls, while the Linux kernel’s cgroup v2 documentation describes its interfaces.
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Interpret steal time as a clue, not a diagnosis
Linux tools expose st or %steal for virtualized environments. A persistent increase that coincides with reported latency is evidence that the guest is not receiving some virtual CPU time. It is a reasonable reason to ask the provider to examine the host, particularly after guest-local process use and cgroup throttling have been considered.
Steal time does not name the process, customer or virtual machine using the host. It also does not prove that a noisy neighbor caused every incident in which it appears. AWS documents one provider-specific way to collect guest CPU stolen time as cpu_time_steal in its CloudWatch agent metric documentation; that example is not required for the Linux command-line workflow.
Know what controls you can use
Cgroups organize processes hierarchically and can account for or limit resources. Linux cpusets constrain the CPUs and memory nodes available to a task group. These controls can help an administrator manage workloads under their control, but they do not reveal or control another hosting customer’s processes.
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Kubernetes placement guidance is a separate case, not a remedy available to every shared-hosting customer. For example, AWS EKS guidance discusses CPU requests and node taints and tolerations for workload placement in that environment; those controls should not be generalized to ordinary shared hosting.
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If repeated samples show persistent steal time during a latency window and guest-local usage or throttling does not account for it, send the provider a concise incident record. Include:
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vmstatormpstatsamples covering both normal operation and the slowdown, with the relevantwaandstor%stealfields visible. - The times users reported latency and any relevant application metrics.
- Instance details and, if applicable, cgroup usage, throttling counters and configured limits for the affected workload.
Ask whether the provider sees host contention, whether your plan has a CPU cap or burst policy, and what allocation or isolation options are available. Guest-level measurements cannot establish what the provider will find on the host, so treat its investigation and plan terms as matters to verify directly.
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Compare hosting options if the allocation is the issue
If the provider’s response points to an allocation or isolation problem, compare plans using the actual terms relevant to your workload rather than relying on labels alone:
- What CPU allocation is documented, and is it shared, capped, burstable or dedicated?
- What does the provider say it will investigate or report when customers raise a contention concern?
- What isolation does the plan provide for the workload you run?
- What are the price and migration costs of changing plans or providers?
Verify current plan details with the provider; the terms and available isolation options vary.
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