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google
cadvisor
Go2014–2025
google / cadvisor

cadvisor

Analyzes resource usage and performance characteristics of running containers.

10Distinct people
10Mentions
0Explicit recommenders
19.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Analyzes resource usage and performance characteristics of running containers.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:56:20 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year10 dated mentions

Observed mentions: 2014-06-10 17:28:45 UTC to 2025-12-13 22:44:40 UTC.

012342014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC413
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

1 sources
This script does nothing to solve that and actually exasperates problem of people over specing. It makes assumptions about pricing[0], when if you do need a peak of 8GB it would force you into launching and consuming that 8GB immediately, because it is just reading a current snapshot from /proc/$pid/status:VmSize [1] and says you are waisting memory if "request - actual usage (MiB)" [2] What if once a week you need to reconcile and need that 8GB, what if you only need 8GB once every 10 seconds? There script won't see that; so to be defensive you can't release that memory, or you will be 'wasting' resource despite that peek need. What if your program only uses 1GB, but you are working on a lot of parquet files, and with less ram you start to hit EBS IOPS limits or don't finish the nightly DW run because you have to hit disk vs working fro
Read the rest
m the buffer with headroom etc.. This is how bad metrics wreck corporate cultures, the ones in this case encourage overspending. If I use all that ram I will never hit the "top_offender" list[3] even if I cause 100 extra nodes to be launched. Without context, and far more complicated analytics "request - actual usage (MiB)" is meaningless, and trivial to game. What incentive except making sure that your pods request ~= RES 24x7x356 ~= OOM_KILL limits/2, to avoid being in the "top_offender" does this metric accomplish? Once your skip's-skip's-skip sees some consultant labeled you as a "top_offender" despite your transient memory needs etc... how do you work that through? How do you "prove" that against a team gaming the metric? Also as a developer you don't have control over the clusters placement decisions, nor typically directly choosing the machine types. So blaming the platform user on the platform teams' inappropriate choice of instance types, while shutting down many chances of collaboration by blaming the platform user typically also isn't a very productive path. Minimizing cloud spend is a very challenging problem, which typically depends on collaboration more than anything else. The point is that these scripts are not providing a valid metric, and absolutely presenting that metric in a hostile way. It could be changed to help a discovery process, but absolutely will not in the current form. [0] https://github.com/WozzHQ/wozz/blob/main/scripts/wozz-audit.... [1] https://github.com/google/cadvisor/blob/master/cmd/internal/... [2] https://github.com/WozzHQ/wozz/blob/main/scripts/wozz-audit.... [3] https://github.com/WozzHQ/wozz/blob/main/scripts/wozz-audit....
In Show HN: I audited 500 K8s pods. Java wastes ~48% RAM, Go ~18%

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