Date: Fri, 29 Mar 2024 02:37:48 +0000 (UTC)
Message-ID: <1025243092.130448.1711679868127@aws-us-west-2-onap-confluence-1.web.codeaurora.org>
Subject: Exported From Confluence
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Introd=
uction
OOF-HAS is an policy-driven placement optimizing service (o=
r homing service) that allows ONAP to deploy services automatically across =
multiple sites and multiple clouds. It enables placement based on a wide va=
riety of policy constraints including capacity, location, platform capabili=
ties, and other service specific constraints.
HAS is a distributed resource broker that enables automated policy-drive=
n optimized placement of services on a global heterogeneous platform using =
ONAP. Given a set of service components (based on SO decomposition flows) a=
nd requirements for placing these components (driven by policies), HAS find=
s optimal resources (cloud regions or existing service instances) to home these service components such that it meets all the se=
rvice requirements. HAS is architected as an extensible homing service that=
can accommodate a growing set of homing objectives, policy constraints, da=
ta sources and placement algorithms. It is also service-agnostic by design =
and can easily onboard new services with minimal effort. Therefore, HA=
S naturally extends to a general policy-driven optimizing placement platfor=
m for wider range of services, e.g., DCAE micro-services, ECOMP control loo=
ps, server capacity, etc. Finally, HAS provides an traceable mechanism for =
what-if analysis which is critical for ease of understanding a homing recom=
mendation and resolving infeasibility scenarios.
HAS in Service Instantiation workflows
Below is an illustration of HAS interactions with other ONAP components =
to enable Policy driven homing. The homing policy constraints have been exp=
anded (and categorized) to highlight the range of constraints that could be=
provided to HAS for determining the homing solution. The figure also shows=
how HAS uses a plugin-based approach to allow an extensible set of constra=
ints and data models.
More information on how homing constraints are specified can be found at=
OOF-HAS Ho=
ming Specification Guide, and a sample homing template has been drawn u=
p for residential vCPE Ho=
ming Use Case.
HAS Architec=
ture (R2)
HAS is implemented based on an active/active high availability architect=
ure (HAS - Active-Active High Availab=
ility Architecture), where each component of HAS can scale horizontally=
independent of the others. This also allows HAS to have highly scalable hy=
brid deployment architectures (OOF Beijing R2 OOM Deployment Planning).
L=
ifecycle of a Homing request in HAS
Use cases
A sample heuristic greedy algorithm of HAS
Guide to writing Homing Specifications
HAS is service agnostic by design and the OOF-HAS Homing Specification Guide ca=
n help create homing specifications for new services.
Triaging=
Homing decisions
Triaging HAS homin=
g decisions
HAS Developer =
guide
The HAS Developer Guide=
will give more information on how to deploy HAS, and contributing=
to the HAS code.
Beijing=
Release Artifacts:
https://nexus.onap.org/content/repositories/releases/=
org/onap/optf/has/optf-has-conductor/1.1.1/ (binaries)
<=
a href=3D"https://nexus.onap.org/content/repositories/releases/org/onap/opt=
f/osdf/optf-osdf/1.1.1/" class=3D"external-link" rel=3D"nofollow">htt=
ps://nexus.onap.org/content/repositories/releases/org/onap/opt=
f/osdf/optf-osdf/1.1.1/ (binaries)
nexus3.onap.org:10001/onap/optf-has:1.1.1=
(docker image)
nexus3.onap.org:10001/o=
nap/optf-osdf:1.1.1 (docker image)
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------=_Part_130447_470114999.1711679868124--