Paper Citation Record · LEDGER

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2505.21559.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.21559 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:56:51.324782Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T11:57:24.591538Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-15T11:59:59.409656Z

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy30
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fdc01208-2a75-457b-800c-0de9aec91dd1 · outbound

This paper cites Cloud container technologies: A state-of-the-art review,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Cloud container technologies: A state-of-the-art review,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.679936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2968bc47-c0f8-408a-aaf2-e2b468c8f2e8 · outbound

This paper cites Adaptive ai-based auto- scaling for kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Adaptive ai-based auto- scaling for kubernetes,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.587949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6a121b56-f1fe-4548-b14b-fb9b6894d20e · outbound

This paper cites Borg, omega, and kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Borg, omega, and kubernetes,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.486218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 606f3170-7eb5-498d-b255-316b69d876a9 · outbound

This paper cites Kubernetes auto-scaling: Yoyo attack vulnerability and mitigation,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Kubernetes auto-scaling: Yoyo attack vulnerability and mitigation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.403114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2843154b-fcb3-46f1-bad5-8b7f9c0a7928 · outbound

This paper cites Reinforcement learning-based application autoscaling in the cloud: A survey,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Reinforcement learning-based application autoscaling in the cloud: A survey,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.315374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e8e5972-2054-4a30-b007-47d51fc87678 · outbound

This paper cites Scaling up multi- agent reinforcement learning: An extensive survey on scalability issues,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Scaling up multi- agent reinforcement learning: An extensive survey on scalability issues,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.184870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e6651a05-e248-414c-ae9e-22840194875c · outbound

This paper cites Shoham and K.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Shoham and K

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:55.064919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fcda8e57-e9a7-4dfc-98bb-2e2f79662c85 · outbound

This paper cites Applications of intelligent agents,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Applications of intelligent agents,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.917690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 88b664ce-8fd9-4533-8538-b6b75b9aa811 · outbound

This paper cites Kott and M.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Kott and M

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.777867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 43335e63-00b3-4d1b-a497-fef5e5df126a · outbound

This paper cites A marl-based approach for easing mas organization engineering,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework A marl-based approach for easing mas organization engineering,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.665735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1e8c8046-8584-4842-a180-fd5f59dd8e5f · outbound

This paper cites AW ARE: Automate workload autoscaling with reinforcement learning in production cloud systems,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework AW ARE: Automate workload autoscaling with reinforcement learning in production cloud systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.555717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ad00b130-1c00-49b0-9540-2839622495c6 · outbound

This paper cites gym-hpa: Efficient auto-scaling via reinforcement learning for complex microservice-based applications in kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework gym-hpa: Efficient auto-scaling via reinforcement learning for complex microservice-based applications in kubernetes,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.429468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a101eae6-e0ee-4d91-99ef-9038f1bc1b30 · outbound

This paper cites Horizontal and vertical scaling of container-based applications using reinforcement learning,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Horizontal and vertical scaling of container-based applications using reinforcement learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.251218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e5b29a21-fdbe-4d5c-8df0-9b204e62c246 · outbound

This paper cites Development of qos-aware agents with reinforcement learning for autoscaling of microservices on the cloud,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Development of qos-aware agents with reinforcement learning for autoscaling of microservices on the cloud,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:54.075505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ab5bdf6e-f06e-40d2-88ad-056bdabe3a9e · outbound

This paper cites Ahpa: Adaptive horizontal pod autoscaling systems on alibaba cloud container service for kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Ahpa: Adaptive horizontal pod autoscaling systems on alibaba cloud container service for kubernetes,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.965020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 30c4c8f5-8bad-4a6f-a528-39ff07a04ed7 · outbound

This paper cites Kosmos: Vertical and horizontal resource autoscaling for kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Kosmos: Vertical and horizontal resource autoscaling for kubernetes,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.856623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56836034-69df-4a0e-aeac-f9eb3e36dad3 · outbound

This paper cites Copa: A combined autoscaling method for kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Copa: A combined autoscaling method for kubernetes,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.771051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a6e77a06-b7fd-47c3-8c4f-4f479da742cc · outbound

This paper cites Kubernetes scheduling: Taxonomy, ongoing issues and challenges,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Kubernetes scheduling: Taxonomy, ongoing issues and challenges,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.668723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 24037f17-cef0-4573-b66a-1fc729a50420 · outbound

This paper cites A survey of autoscaling in kubernetes,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework A survey of autoscaling in kubernetes,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.570268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7c26350b-f50f-4145-9619-9607d10528f3 · outbound

This paper cites Prometheus - monitoring system and time series database,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Prometheus - monitoring system and time series database,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.471803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bb05b4d3-ca2e-4e98-b9f7-ecee955a60b5 · outbound

This paper cites Stochastic games,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Stochastic games,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.364072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 59b31c94-06ee-4d9c-820b-2e84b2e5ad20 · outbound

This paper cites The action spaces in openai gym,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework The action spaces in openai gym,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.281920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0db0ff1c-63c3-40f8-917c-16736d54fd6e · outbound

This paper cites Pettingzoo: Gym for multi-agent reinforcement learning,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Pettingzoo: Gym for multi-agent reinforcement learning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:53.072376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e52e7ca6-9a22-4a08-970b-16370230556b · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework The surprising effectiveness of ppo in cooperative multi-agent games,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:52.880926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0979c23b-9d45-4e26-8af2-06afb611a97e · outbound

This paper cites Optuna: A next-generation hyperparameter op- timization framework,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Optuna: A next-generation hyperparameter op- timization framework,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:52.644719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 847ede24-e0c6-43b5-937f-f62a424c46c0 · outbound

This paper cites Using dynamic time warping to find patterns in time series,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Using dynamic time warping to find patterns in time series,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:52.395523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7fffb3d0-8171-40e7-a58f-baa036babba7 · outbound

This paper cites Moise+: Towards a structural, functional, and deontic model for multi-agent organizations,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Moise+: Towards a structural, functional, and deontic model for multi-agent organizations,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:52.136973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d7fc8d0f-0dfa-4a5a-9d74-689cdf89ab42 · outbound

This paper cites an unresolved cited work.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:56:52.005033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b3a0306f-cf90-4729-9c22-6ed909395bfe · outbound

This paper cites Autonomous Intelligent Cyber-defense Agent (AICA) Reference Architecture. Release 2.0.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Autonomous Intelligent Cyber-defense Agent (AICA) Reference Architecture. Release 2.0

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:56:51.453390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2e27bc0-f5b9-4685-8194-0579706c417a · outbound

This paper cites Deep reinforcement learning based smart mitigation of ddos flooding in software-defined networks,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Deep reinforcement learning based smart mitigation of ddos flooding in software-defined networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:51.871328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ea386e9-915a-4a33-af00-feacc6b8fdd7 · outbound

This paper cites Shahrad, Resource-efficient Management of Large-scale Public Cloud Systems.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework Shahrad, Resource-efficient Management of Large-scale Public Cloud Systems

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:51.680568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fe7552f1-f81c-4d86-b0fa-1ddc54ace788 · outbound

This paper cites A comprehensive survey on container resource allocation approaches in cloud computing: State-of-the-art and research challenges,.

Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework A comprehensive survey on container resource allocation approaches in cloud computing: State-of-the-art and research challenges,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:56:51.574151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation e867186d-89ec-44d4-8842-f5dab9cd45e4 · inbound

AGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes Scheduling cites this paper.

AGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes Scheduling Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:59:59.411958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.