INDIGO-DATACLOUD DAVIDE SALOMONI, INFN- CNAF - INDIGO-DATACLOUD PROJECT COORDINATOR - EUROPEAN SPACE POLICY INSTITUTE
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
INDIGO-‐DataCloud
Better
Software
for
Better
Science.
RIA-‐653549
Davide Salomoni,
INFN-‐CNAF
INDIGO-‐DataCloud Project
Coordinator
davide.salomoni@cnaf.infn.it
ESA-‐ESPI
Workshop
Frascati,
7/7/2017
INDIGO-‐DataCloud
• An
H2020
project
approved
in
January
2015
in
the
EINFRA-‐1-‐2014
call
• 11.1M€,
30
months
(from
April
2015
to
September
2017)
• Who:
26
European
partners
in
11
European
countries
• Coordination
by
the
Italian
National
Institute
for
Nuclear
Physics
(INFN)
• Including
developers
of
distributed
software,
industrial
partners,
research
institutes,
universities,
e-‐infrastructures
• What:
develop
an
open
source
Cloud
platform for
computing
and
data
(“DataCloud”)
tailored
to
science
but
applicable
to
other
domains
as
well.
• For:
multi-‐disciplinary
scientific
communities
• E.g.
structural
biology,
earth
science,
physics,
bioinformatics,
cultural
heritage,
astrophysics,
life
science,
climatology
• Where:
deployable
on
hybrid
(public
or
private)
Cloud
infrastructures
• INDIGO
=
INtegrating
Distributed
data
Infrastructures
for
Global
ExplOitation
• Why:
answer
to
the
technological
needs
of
scientists
seeking
to
easily
exploit
distributed
Cloud/Grid
compute
and
data
resources.
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 2
INDIGO-‐DataCloud’s Vision
• INDIGO: Scientific
Users
1. Develops
open,
interoperable
Adopt,
Use
solutions
for
scientific
data.
2. Supports
open
science organizing
INDIGO
Advanced
Components
and
Solutions
the
European
data
space.
3. Enables
collaborations across
Deployed
on
diverse
scientific
communities
worldwide. D1.8,
General
Architecture Private
or
Commercial Publicly
funded
e-‐infrastructures
• INDIGO
offers
its D2.1
and
Clouds
(Public,
PCP-‐based,
(EGI,
EUDAT,
GEANT,
PRACE,
RI,
• architecture, D2.4,
community
etc.) etc.)
• analysis, requirements
• expertise INDIGO’s
34
Exploiting
• and
software
components deliverables
(so
far)
Datasets,
Resources
• as
a
concrete
step
toward
the
The
INDIGO-‐
definition
and
implementation
of
DataCloud To
produce
a
European
Open
Science
Cloud
Service
Catalogue
and
Data
Infrastructure. Scientific
Results
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 3
The
INDIGO
Services
• We
recently
released
our
second
and
final
major
software
release,
called
ElectricIndigo
• Fact
sheet
(https://www.indigo-‐
datacloud.eu/service-‐component):
• 40
modular
components,
distributed
via
170
software
packages,
50
ready-‐to-‐use
Docker
containers
• Supported
operating
systems:
CentOS
7,
Ubuntu
16.04
• Supported
cloud
frameworks:
OpenStack
Newton,
OpenNebula 5.x
(plus
connection
to
Amazon,
Azure)
• Download
it
from
the
INDIGO-‐DataCloud
Software
Repository:
http://repo.indigo-‐
datacloud.eu/index.html
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 4
How
does
this
fit
in
a
global
context?
• We
recognize
that
value
for
users
(and
hence,
our
main
focus)
is
at
the
upper
layers,
not
in
the
bare
bone
e-‐infrastructural
services.
• But
we
also
provide
ways
to
optimize
e-‐
infrastructural
services
for
resource
providers
• So,
we
abstract
from
underlying
IaaS
technologies and
offer
flexibility
in
choosing
e-‐infra
providers,
resources
and
capabilities…
• …
giving
users
the
possibility
to
easily
express
and
implement
requirements
for
their
applications through
enabling
services
and
components.
• This
is
a
movement
that
goes
well
beyond
the
”S”
of
Science in
a
EOSC.
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 5
INDIGO
in
support
to
communities
(some
real
apps
integrating
INDIGO
components)
• LifeWatch:
algae
bloom
modeling • Automated
deployment
of
an
Ophidia
big
data
analytics
cluster
• RNA
sequencing
with
TRUFA
• INDIGO
at
the
Central
Institute
for
the
Union
• Deploying
an
elastic,
complex
cluster
on
the
Catalogue
of
Italian
Libraries
and
Cloud
with
INDIGO
components Bibliographic
Information
• Cloudified services
for
molecular
dynamics • EGI
and
INDIGO
integration
• A
distributed
archive
system
for
the
• ELIXIR-‐ITALY:
developing
a
Galaxy
instance
Cherenkov
Telescope
Array
(CTA) provider
platform
• The
Large
Binocular
Telescope
(LBT)
• Multidisciplinary
Oceanic
Information
distributed
archive System
• INDIGO’s
Ophidia
for
astronomical
images
• Deploy
a
Zenodo-‐based
repository
in
the
calibration cloud
using
Marathon
• Launching
POWERFIT
and
DISVIS
VMs
on
the
• On-‐demand
analysis
and
big
data
EGI
FedCloud using
INDIGO
tools infrastructures
for
the
CMS
LHC
experiment
• POWERFIT
and
DISVIS
web
portals:
• Theoretical
physics
on
HPC
clusters
using
harnessing
GPGPUs
on
the
Grid
using
INDIGO
udocker
INDIGO
udocker
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 6
INDIGO in support to maintenance and evolution • How can INDIGO be sustained and evolved? 1. Collaboration with commercial providers 2. Collaboration with existing projects and initiatives 3. Submission of new projects Davide Salomoni ESA-‐ESPI Workshop, 7/7/2017 7
Some
collaborations
with
commercial
providers
• See
https://developer.ibm.com/opentech/2017/05/18/cloud-‐
computing-‐better-‐science-‐recap-‐egi-‐conference-‐indigo-‐datacloud-‐
summit-‐2017/ for
a
summary
of
the
INDIGO
Summit
2017
by
Dr
Sahdev Zala of
IBM
• With
some
details
about
the
ongoing
collaboration
between
IBM
and
INDIGO-‐
DataCloud
• See
https://indico.egi.eu/indico/event/3249/session/48/contribution/98/
material/slides/0.pdf for
info
on
the
integration
of
INDIGO
tools
into
the
Open
Telekom
Cloud
portfolio,
the
public
cloud
offering
of
T-‐
Systems
(a
Deutsche
Telekom
unit)
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 8
Davide Salomoni ESA-‐ESPI Workshop, 7/7/2017 9
Collaboration
with
existing
projects,
infrastructures
and
initiatives
• There
are
ongoing
discussions
and
collaborations
with
several
actors,
belonging
to
many
areas
– for
example:
• European
Space
Agency
&
ASI
(typically
for
exploitation
/
distribution
/
analysis
of
Copernicus
data)
• Smart
City
projects
• Rationalization
of
Public
Administrations
• HelixNebula ScienceCloud (Pre-‐Commercial
Procurement)
• EU-‐wide
HPC-‐Big
Data
Integration
(IPCEI)
• EGI
(also
an
INDIGO-‐DataCloud partner)
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 10Submission of new European projects • In the last round of the H2020 calls (March-‐April 2017), at least 5 proposals were submitted that included key INDIGO components or their possible evolutions. • We still do not know how many of these proposals will be approved, but it is interesting to note that there is a very significant interest and request for solutions that originate from INDIGO. If results are there, stakeholder engagement is strong, if ideas, requirements, architectures are valid, this interest will eventually find ways to be supported. Davide Salomoni ESA-‐ESPI Workshop, 7/7/2017 11
INDIGO & EOSC in production: >= TRL8 • For example, several INDIGO solutions and activities are in the EOSC-‐ hub proposal (a proposal jointly prepared by EGI, EUDAT and INDIGO-‐ DataCloud) • With INDIGO components such as Identity and Access Management, Token Translation, Virtual filesystems (Onedata), Advanced IaaS Services, the Infrastructure Manager, the INDIGO PaaS and its orchestrator, web front-‐end services, user-‐level containers • And with training, support, technical coordination, external liaison, stakeholder engagement, policy contributions. Davide Salomoni ESA-‐ESPI Workshop, 7/7/2017 12
INDIGO
&
EOSC
in
evolution:
<
TRL8
• For
example,
novel
features evolving
INDIGO
components
are
a
key
part
of
several
proposals
to
the
EINFRA-‐21-‐2017
(eXtreme-‐DataCloud and
DEEP-‐
Hybrid
DataCloud)
and
ICT-‐16-‐2017
calls:
• Intelligent
dataset
distribution
and
data
lifecycle
management
• Smart
caching
• Orchestrating
Computing
Workflows
based
on
policy
driven
or
adaptive
data
movements
• Flexible
metadata
management
for
big
data
sets
• Access
to
bare-‐metal
resources
on
the
Cloud
• PaaS-‐Level
access
to
HPC
resources
• Extensions
to
the
INDIGO
Orchestrator
for
hybrid
IaaS
deployments
and
scale
out
to
3rd
party
clouds
• Extensions
to
the
INDIGO
Virtual
Router
Appliance
• Real-‐time,
streaming-‐based
data
ingestion
and
processing
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 13INDIGO
and
External
Projects:
Components
and
Patches
Merged
in
Upstream
Open
Source
Projects
• OpenStack
(https://www.openstack.org) • TOSCA
adaptor
for
JSAGA
• Nova
Docker (http://software.in2p3.fr/jsaga/dev/)
• Heat • OCCI
implementation
for
OpenStack
• OpenID-‐Connect
for
Keystone (https://github.com/openstack/ooi)
• Pre-‐emptible
instances
support
(under
discussion) • Extended
AWS
support
for
rOCCI in
OpenNebula.
Python
and
Java
libraries
for
OCCI
• OpenNebula (http://opennebula.org) support.
• OneDock
• CDMI
and
QoS extensions
for
dCache
• Infrastructure
Manager
(https://www.dcache.org)
(http://www.grycap.upv.es/im/index.php) • Workflow
interface
extensions
for
Ophidia
• Clues
(http://ophidia.cmcc.it)
(http://www.grycap.upv.es/clues/eng/index.p
hp) • OpenID
Connect
Java
implementation
for
dCache (https://www.dcache.org)
• Onedata (https://onedata.org)
• MitreID (https://mitreid.org/) and
OpenID
Connect
(http://openid.net/connect/) libraries
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 14EGI
services for
EO
data
exploitation
• The
new
EO
satellites
generates
large
amounts
of
data
not
easily
integrated
into
processing
chains
outside
the
ground
segment.
• EGI
services
can
improve
the
discovery,
retrieval
and
processing
capabilities
of
EO
data:
ü capabilities
for
big
data
management
ü virtualised access
to
Cloud Compute geographically
Data
Hub
distributed
data
(EGI
Data
Hub)
ü computing
necessary
to
Online
Storage manage
large
volumes
of
Data
Transfer
different
data
types
7/6/17 15EGI
services for
EO
data
exploitation
• The
new
EO
satellites
generates
large
amounts
of
data
not
easily
integrated
into
processing
chains
outside
the
ground
segment.
• EGI
services
can
improve
the
discovery,
retrieval
and
processing
capabilities
of
EO
data:
ü capabilities
Advanced
IaaSfor
big
data
management
Network
virtualization
Advanced
Orchestration
ü virtualised access
to
PaaS
Standard
interfaces
support
Cloud Compute geographically
Containers
Orchestration Data
Hub
distributed
data
(EGI
Data
Hub)
ü computing
necessary
to
Online
Storage manage
large
volumes
of
Data
Transfer
different
data
types
7/6/17 16EGI
services for
EO
data
exploitation
• The
new
EO
satellites
generates
large
amounts
of
data
not
easily
integrated
into
processing
chains
outside
the
ground
segment.
• EGI
services
can
improve
the
discovery,
retrieval
and
processing
capabilities
of
EO
data:
OneData
ü capabilities
for
big
data
management
ü virtualised access
to
Cloud Compute geographically
Data
Hub
distributed
data
(EGI
Data
Hub)
ü computing
necessary
to
Online
Storage manage
large
volumes
of
Data
Transfer
different
data
types
7/6/17 17EGI
services to
accelerate
the
development of
EO
exploitation platforms
Well
established
e-‐Infrastructure
services
as
a
set
of
reusable
components
to
solve
common
problems:
• AAI
and
single
sign-‐on CheckIn
• Service
Monitoring ARGO
• Accounting
infrastructure APEL
• Configuration Database GOCDB
• Operational Tools Operations
Portal,
Security
tools,
etc.
• Collaboration
tools Wiki,
Doc
repo,
Agenda
mgmt system,
etc.
EO
Platform
developers
can
focus
on
their
core
tasks!
7/6/17 18Reflections
on
some
of
the
suggested
themes
• How
infrastructure
contributes
to
make
possible
new
services
and
applications?
• à INDIGO
contributes
by
producing
enabling
technologies directly
requested
by
both
providers
and
users,
that
can
be
deployed
on
ANY
infrastructure
to
produce
new,
high-‐value
services
or
applications.
• Exponential
technologies:
more
a
software
or
a
hardware
race?
How
value
chain
will
be
affected?
• à For
us
it
is
definitely
more
software,
intended
as
final
artifacts
and
resource
exploitation.
The
value
chain
is
represented
by
the
inverted
triangle
shown
earlier.
The
traditional
hardware
race
per
se
is
lost,
at
least
for
big
initiatives
such
as
HL-‐LHC.
• How
can
we
best
incentivize
data
sharing
between
entities?
• à First,
make
it
doable
/
easy
to
do,
considering
also
issues
such
as
data
lifecycle,
replication,
quality
of
service.
• How
can
we
most
effectively
integrate
modern
and
legacy
data
infrastructures?
• à Through
open
solutions,
the
use
of
de
facto
or
de
jure
standards,
and
state-‐of-‐the-‐art
but
still
production-‐level
solutions.
• To
what
extent
are
consolidation
and
integration
of
existing
services
necessary
to
achieve
the
necessary
infrastructure?
• à They
are
absolutely
necessary,
if
we
want
to
effectively
use
all
the
resources
that
are
there.
We
assume
that
we
MUST
be
able
to
utilize
these
resources
before
looking
/
asking
for
new
infrastructures.
• What
would
you
consider
to
be
the
most
crucial
next
steps
and
milestones
in
the
successful
implementation
of
the
programs?
• Be
pragmatic
and
do
not
spend
too
much
time
discussing
first
principles.
Get
the
relevant
actors
around
the
same
table,
start
from
concrete
requirements
and
use
cases,
and
seek
implementers
/
implementations
able
to:
• Scale
out
• Run
in
multiple,
heterogeneous,
hybrid
infrastructures
• Clearly
show
the
benefits
of
the
proposed
vs.
legacy
/
proprietary
/
ad-‐hoc
solutions
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 19Conclusions
• In
just
24
months,
the
INDIGO-‐DataCloud project
has
realized
a
comprehensive
involvement
of
many
Research
Communities
and
providers for
the
definition
and
tracking
of
requirements.
• We
identified
technology
gaps linked
to
several
concrete
use
cases
in
multiple
fields,
defined,
published
and
implemented
the
overall
INDIGO
architecture.
• After
early
demonstrations
and
beta
software
previews,
we
produced
two
major
software
versions
and
9
minor
updates,
releasing
40
open
modular
components.
We
did
that
exploiting
key
European
know-‐how,
reusing
and
extending
open
source
software,
and
contributing
to
upstream
projects.
We
established
software
development
and
management
processes,
and
defined
development
and
pre-‐
production
distributed
testbeds.
• Production
deployment
of
many
applications
making
use
of
the
INDIGO
software
is
well
underway,
and
INDIGO
components
have
been
proposed
for
production
use
in
big
infrastructures,
commercial
companies,
external
projects.
• Several
opportunities
for
further
exploitation
of
INDIGO
components
are
being
explored
and
implemented,
in
the
context
of
the
EOSC
and
beyond.
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 20Thank
you
https://www.indigo-‐datacloud.eu
Better
Software
for
Better
Science.
@indigodatacloud www.indigo-‐datacloud.eu https://www.facebook.com/indigodatacloud/
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 21Backup slides Davide Salomoni ESA-ESPI Workshop, 7/7/2017 22
The
INDIGO
added
value
• INDIGO,
driven
by
scientific
communities,
has
been
developing
a
comprehensive
open
source
Cloud
architecture,
which
provides
many
new
functionalities
and
services
previously
unavailable
in
open
source
and
in
some
cases
also
in
proprietary
Cloud
offerings.
• These
functionalities
abstract
from
underlying
IaaS
technologies through
the
consistent
use
of
both
de
jure
and
de
facto
standards.
This
allows
interoperability
with
hybrid
(public/private)
infrastructures.
• After
beta
testing
and
demos
shown
as
early
as
November
2015,
we
released
our
first
major
software
release
(MidnightBlue)
in
August
2016,
9
software
updates
in
the
following
months,
and
our
second
and
final
major
release
(ElectricIndigo)
in
April
2017.
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 23Release
Timeline
Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan
INDIGO-‐1 Full
updates
Standard
updates
Security
updates
INDIGO-‐2 Full
updates
Standard
updates
Security
updates
Release
Date End
of
Full
Updates End
of
Standard
End
of
Security
Updates Updates
&
EOL
INDIGO-‐1
MidnightBlue 08/08/2016 31/01/2017 31/03/2017 31/05/2017
INDIGO-‐2
ElectricIndigo 14/04/2017 30/09/2017 30/11/2017 31/01/2018 24
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017ElectricIndigo
Four
main
“solution
blocks”:
• Data
Center
Solutions
• Data
/
Storage
Solutions
• Automated
Solutions
• User-‐Oriented
Solutions
And
“common
solutions”:
• Authentication
and
Authorization
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 25ElectricIndigo:
Application-‐level
Interfaces
for
Cloud
Providers
and
Automated
Service
Composition
• Easily
port
applications
to
public
and
private
Clouds using
open
programmable
interfaces,
user-‐level
containers,
and
standards-‐based
languages
to
automate
definition,
composition
and
instantiation
of
complex
set-‐ups.
• Typical
questions:
How
can
I
run
my
application
on
Cloud
provider
X?
What
if
I
want
to
use
Docker
but
my
provider
does
not
support
it
(e.g.
also
on
HPC
systems)?
How
do
I
automate
the
creation
and
management
over
public
or
private
Clouds
of
dynamic
clusters
running
multiple
services?
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 26ElectricIndigo:
Flexible
Identity
and
Access
Management
• Manage
access
and
policies
to
distributed
resources using
multiple
methods
such
as
OpenID-‐Connect,
SAML,
X.509 digital
certificates,
through
programmable
interfaces
and
web
front-‐
ends.
• Typical
questions:
How
can
I
manage
access
to
distributed
resources
by
users,
identified
through
diverse
methods?
(e.g.
Google
ID,
digital
certificates)
How
should
I
modify
/
write
my
apps
to
benefit
from
that?
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 27ElectricIndigo:
Data
Management
and
Data
Analytics
Solutions
• Distribute
and
access
data through
multiple
providers
via
virtual
file
systems
and
automated
replication
and
caching,
exploiting
scalable,
high-‐
performance
data
mining
and
analytics.
• Typical
questions:
How
can
I
automatically
replicate
datasets
to
multiple
sites?
Can
I
transparently
access
my
distributed
datasets
from
my
app?
Can
I
cache
the
most
accessed
data,
so
that
it’s
close
to
where
users
need
it?
How
do
I
instantiate
clusters
and
databases
for
big
data
analysis?
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 28ElectricIndigo:
Programmable
Web
Portals,
Mobile
Applications
• Create
and
interface
web
portals
or
mobile
apps,
exploiting
distributed
data
as
well
as
compute
resources located
in
public
and
private
Cloud
infrastructures.
• Typical
questions:
How
can
I
easily
provide
my
app
with
a
pluggable,
extensible
web
front-‐end?
Can
this
front-‐end
interface
with
all
the
features
provided
by
INDIGO?
How
can
I
write
an
INDIGO-‐
enabled
app
for
Android
or
iOS?
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 29ElectricIndigo:
Enhanced
and
Scalable
Services
for
Data
Centers
and
Resource
Providers
• Increase
the
efficiency
of
existing
Cloud
infrastructures based
on
OpenStack
or
OpenNebula through
advanced
scheduling,
flexible
cloud
/
batch
management,
network
orchestration and
interfacing
of
high-‐level
Cloud
services
to
existing
storage
systems.
• Typical
questions:
How
can
my
cloud
data
centers
provide
flexible
and
fair
scheduling
policies
for
access
to
resources?
How
do
I
balance
traditional
vs.
cloud
resources
in
my
data
center?
How
do
I
connect
novel
INDIGO
features
to
my
existing
systems?
How
can
I
manage
storage
Quality
of
Service?
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 30WP6 Services
High-‐level
view
of
the
GUI
Admin
Portlets
User
Portlets
Mobile Apps
Ophidpia
plugin
Other
INDIGO
architecture
Clients
LONI plugin Science SG Mon
Data Workflow Open Mobile
Taverna,
Gateways
Analitics Portlets Toolkit Kepler plugin Support
Future Gateway Portal Mobile clients Workflows services
Future Gateway REST API
Future Gateway Engine
JSAGA/JSAGA Adaptors
REST/CDMI/Wedbav/posix/Gridftp
OIDC TOSCA
Kubernetes Cluster
Onedata Dynafed
PaaS Data Services
FTS
Orchestrator
QoS/SLA
This
is
the
INDIGO-‐DataCloud
Accounting
IAM
Service
TOSCA Monitoring
WP5
General
Architecture* Infrastructure
Manager
CloudProvider
Ranker Services
TOSCA S3/CDMI/Posix/Webdav
GridFTP
Mesos
Aut. Scaling Mesos
Cluster
Service Cluster
Storage
Native IaaS API Service
QoS Support
Heat/IM
Non-INDIGO
Smart Identity
IaaS Scheduling
Spot Istances
Armonization
*:
see
details
in
http://arxiv.org/abs/1603.09536 or
in
https://www.indigo-‐datacloud.eu/documents-‐deliverables Native
Docker Local
WP4 Services
Repository
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 31INDIGO
Software
Development
Flow
Development
T3.4
T3.1
Software
T3.2
Software
Exploitation
WP4
WP5
WP6
quality
release
and
assurance maintenance
Development Integration Preview External
infrastructure infrastructure infrastructure Service
Providers
T3.3
Pilot
services
software
delivery
WP2 Users
software
deployment
Application Production
software
use Use-‐cases 3232
work
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017The
INDIGO
Development
and
Integration
Infrastructure
DESY
-‐ dCache
PSNC
-‐ Indigokepler
CESNET -‐ indigo-‐omt
-‐ rOCCI
KIT
-‐ CDMI-‐QoS Cyfronet
-‐ TTS -‐ Onedata
CERN
IFCA/CSIC -‐ Kubernetes
-‐ OOI -‐ Magnun
-‐ OPIE
CNAF/INFN
-‐ IAM
LIP/INCD -‐ Oneprovider INFN
Bari
-‐ OpenNebula:
ONEDock -‐ Kubernetes
-‐ Nova-‐Docker -‐ Mesos
-‐ FutureGateway UPV -‐ Chronos
-‐ IM
-‐ CLUES
-‐ TOSCA
33
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017The
INDIGO
Pilot
Preview
Testbed
DESY
-‐ CDMI-‐QoS
-‐ dCache
-‐ OneData
Demos
are
performed
in
the
preview
testbed KIT INFN-‐Padova
-‐ Synergy
-‐ CDMI-‐QOS
-‐ OneData -‐ OOI
LIP/INCD
-‐ OOI IFCA/SIC
-‐ IAM
connector -‐ ooi
CNAF/INFN
-‐ Nova-‐Docker -‐ IAM
connector
-‐ IAM
-‐ OS
Identity
Authentication
-‐ nova-‐docker
-‐ OneData
library -‐ OS
Identity
Authentication
library
-‐ CDMI-‐QoS
-‐ ONEDock -‐ java-‐syncrepos
-‐ Orchestrator
-‐ rOCCI
server
-‐ CloudProviderRanker
-‐ TTS
-‐ Zabbix-‐wrapper
-‐ Java-‐syncrepos
-‐ SLAManager
-‐ Cloud-‐info-‐provider
-‐ CMDB
-‐ IM
-‐ OneData
-‐ FG
API
server
-‐ FG
Portal INFN-‐Bari
-‐ LiferayIAM -‐ CDMI-‐QoS
-‐ Indigo
Kepler UPV -‐ OneData
-‐ Ophidia -‐ IM -‐ Kubernetes:
-‐ Marathon
-‐ Chronos
-‐ Mesos
Davide
Salomoni ESA-‐ESPI
Workshop,
7/7/2017 34Resource
requirements
for
LHC
200
GRID
150 ATLAS
CMS
LHCb
100 ALICE
50
0 500,0
Run
1 Run
2 Run
3 Run
4
400,0
CMS
Computing
power
needs
for
LHC
300,0
ATLAS
200,0 ALICE
100,0 LHCb
0,0
Run
1 Run
2 Run
3 Run
4
Storage
needs
for
LHCYou can also read
