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Demonstrating 100 Gbps in and out of the public Clouds
Igor Sfiligoi - University of California San Diego - isfiligoi@sdsc.edu
Most of the Cloud costs were covered by credits issued by Amazon, Microsoft and Google.
This work was partially funded by US National Science Foundation (NSF) under grants OAC-1941481, MPS-1148698, OAC-1841530, OPP-1600823, OAC-19044, and OAC-1826967.
Like it or not, public Clouds are gaining popularity
• Especially great for prototyping
• But great for compute spikes
and urgent compute activities, too
• When choosing which resources to use (and pay for)
knowing what to expect out of them is important
• The compute part of public Cloud resources is well documented
• The networking is instead hardly documented at all
• Yet networking can make a big difference
when doing distributed computing
Funding agencies are taking notice
• See NSF E-CAS award(s) as an example
• SDSC Expanse has Cloud explicitly mentioned
• NSF-funded CloudBank
• IceCube’s Cloud runs funded by an EAGER award
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 200 400 600 800 1000 1200 1400
Gbps
Number of compute instances
AWS
Azure
GCP
AWS Azure GCP
Asia – US West 100 Gbps 110 Gbps 940 Gbps
US East – West 440 Gbps 190 Gbps 1060 Gbps
EU – US East 460 Gbps 185 Gbps 980 Gbps
Peak Throughput observed between regions
of a single public Cloud provider
Peak Throughput observed in
a single public Cloud provider region
Networking inside
public Cloud providers plentiful
• Over 1 Tbps in a single region
• 100 Gbps to 1 Tbps between regions
Importing data into public Clouds
to feed compute instances
• Using multiplee parallel clients
• 100 Gbps doable on
production infrastructure
• Demonstrated with both storage
in the Pacific Research Platform and
at University of Wisconsin – Madison
ThroughputinBytespersecond
ThroughputinBytespersecond
Fetching data from public Clouds
• Fetching from their Object Storage
using multiple parallel clients
• 100 Gbps doable on
production infrastructure
(PRP using 20 nodes)
• Over 500 Gbps feeding
Cloud instances running
in multiple providers
AWS Azure GCP
US West 100 Gbps 120 Gbps 110 Gbps
US Central 100 Gbps 120 Gbps 110 Gbps
ThroughputinBytespersecond
Networking is a billed commodity
•$50/TB – $120/TB egress
• $20/TB - $90/TB data movement
between Cloud regions
• Ingress free
Fetching data from
Cloud storage
Charges on an account
used for benchmarking
Compute
and ingress
15% network waiver for
compute intensive workloads

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Demonstrating 100 Gbps in and out of the public Clouds

  • 1. Demonstrating 100 Gbps in and out of the public Clouds Igor Sfiligoi - University of California San Diego - isfiligoi@sdsc.edu Most of the Cloud costs were covered by credits issued by Amazon, Microsoft and Google. This work was partially funded by US National Science Foundation (NSF) under grants OAC-1941481, MPS-1148698, OAC-1841530, OPP-1600823, OAC-19044, and OAC-1826967. Like it or not, public Clouds are gaining popularity • Especially great for prototyping • But great for compute spikes and urgent compute activities, too • When choosing which resources to use (and pay for) knowing what to expect out of them is important • The compute part of public Cloud resources is well documented • The networking is instead hardly documented at all • Yet networking can make a big difference when doing distributed computing Funding agencies are taking notice • See NSF E-CAS award(s) as an example • SDSC Expanse has Cloud explicitly mentioned • NSF-funded CloudBank • IceCube’s Cloud runs funded by an EAGER award 0 200 400 600 800 1000 1200 1400 1600 1800 2000 0 200 400 600 800 1000 1200 1400 Gbps Number of compute instances AWS Azure GCP AWS Azure GCP Asia – US West 100 Gbps 110 Gbps 940 Gbps US East – West 440 Gbps 190 Gbps 1060 Gbps EU – US East 460 Gbps 185 Gbps 980 Gbps Peak Throughput observed between regions of a single public Cloud provider Peak Throughput observed in a single public Cloud provider region Networking inside public Cloud providers plentiful • Over 1 Tbps in a single region • 100 Gbps to 1 Tbps between regions Importing data into public Clouds to feed compute instances • Using multiplee parallel clients • 100 Gbps doable on production infrastructure • Demonstrated with both storage in the Pacific Research Platform and at University of Wisconsin – Madison ThroughputinBytespersecond ThroughputinBytespersecond Fetching data from public Clouds • Fetching from their Object Storage using multiple parallel clients • 100 Gbps doable on production infrastructure (PRP using 20 nodes) • Over 500 Gbps feeding Cloud instances running in multiple providers AWS Azure GCP US West 100 Gbps 120 Gbps 110 Gbps US Central 100 Gbps 120 Gbps 110 Gbps ThroughputinBytespersecond Networking is a billed commodity •$50/TB – $120/TB egress • $20/TB - $90/TB data movement between Cloud regions • Ingress free Fetching data from Cloud storage Charges on an account used for benchmarking Compute and ingress 15% network waiver for compute intensive workloads