Evidence map›Paper›PMID 35909833›Full record

ArticleComputational intelligence and neuroscience2022

AIOps Architecture in Data Center Site Infrastructure Monitoring.

Wei Dong

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Wei DongIBM, Shenzhen 518000, China.ORCID https://orcid.org/0000-0002-6902-5367

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIOps (artificial intelligence for IT operations) has been growing rapidly in recent years. However, it can be seen that the vast majority of AIOps applications are implemented in the IT domain. In contrast, there are few applications in the data center infrastructure domain. Many real-world practices show that a working architecture or algorithm cannot be directly replicated from other domains due to completely different business scenarios and different data characteristics. In this paper, an AIOps architecture for the data center infrastructure monitoring domain is presented. A proven working architecture is given in terms of core modules, such as technical architecture, machine learning algorithms, big data, and business applications, and details are designed in practice. This paper focuses on the technical part and not on each part of the architecture work. In other words, NFRs (nonfunctional requirements), such as performance, availability, manageability, and security, will not be discussed in this paper.

Indexed as

Artificial IntelligenceBig DataAlgorithmsMachine Learning

Identifiers

PMID35909833
PMCPMC9328990

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.