Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Seagull: An Infrastructure for Load Prediction and Optimized Resource
  Allocation   Microsoft Azure is dedicated to guarantee high quality of service to its
customers, in particular, during periods of high customer activity, while
controlling cost. We employ a Data Science (DS) driven solution to predict user
load and leverage these predictions to optimize resource allocation. To this
end, we built the Seagull infrastructure that processes per-server telemetry,
validates the data, trains and deploys ML models. The models are used to
predict customer load per server (24h into the future), and optimize service
operations. Seagull continually re-evaluates accuracy of predictions, fallback
to previously known good models and triggers alerts as appropriate. We deployed
this infrastructure in production for PostgreSQL and MySQL servers across all
Azure regions, and applied it to the problem of scheduling server backups
during low-load time. This minimizes interference with user-induced load and
improves customer experience.

33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph