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Performance Characteristics of Traditional VMs vs Docker Containers dockercon14 June 9-10, 2014 San Francisco, CA Boden Russell ([email protected])

Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Slides presented @ dockercon14. Mostly a conglomeration of the KVM vs docker LXC deck and a few others

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Page 1: Performance characteristics of traditional v ms vs docker containers (dockercon14)

Performance Characteristics of Traditional VMs vs Docker Containers

dockercon14June 9-10, 2014San Francisco, CA

Boden Russell ([email protected])

Page 2: Performance characteristics of traditional v ms vs docker containers (dockercon14)

04/10/2023 2

Motivations: Computer Scientist

FamilyInnovationCreativityRevenue

Page 3: Performance characteristics of traditional v ms vs docker containers (dockercon14)

04/10/2023 3

Motivations: Enterprise

RevenueRevenueRevenueRevenue

Page 4: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Increasing Revenue: Do More With Less

Reduce Total Cost of Ownership (TCO) and increase Return On Investment (ROI)

Category Factors ScopeCAPEX

Hardware costs - VM density (consolidation ratio)- Soft device integration- Broad vendor compatibility

- Hypervisor- Cloud manager

Software licensing costs - Software purchase price- Support contracts

- Hypervisor- Cloud manager

OPEX

Disaster recovery - Hypervisor- Cloud manager

Upgrade / maintenance expenses - Hypervisor- Cloud manager

Power & cooling costs - Reduced HW footprint - Hypervisor- Cloud manager

Administration efficiency - Automated operations- Performance / response time

- Hypervisor- Cloud manager

Support & training costs - Hypervisor- Cloud manager

AGILITY

Application delivery time - Workflow complexity- Toolset costs- Skillset

- Hypervisor- Cloud manager

Planned / unplanned downtime - Hypervisor- Cloud manager

*Not a complete or extensive list

Page 5: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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About This Benchmark Use case perspective

– As an OpenStack Cloud user I want a Ubuntu based VM with MySQL… Why would I choose docker LXC vs a traditional hypervisor?

OpenStack “Cloudy” perspective– LXC vs. traditional VM from a Cloudy (OpenStack) perspective– VM operational times (boot, start, stop, snapshot)– Compute node resource usage (per VM penalty); density factor

Guest runtime perspective– CPU, memory, file I/O, MySQL OLTP, etc.

Why KVM?– Exceptional performance

DISCLAIMERSThe tests herein are semi-active litmus tests – no in depth tuning,

analysis, etc. More active testing is warranted. These results do not necessary reflect your workload or exact performance nor are they

guaranteed to be statistically sound.

Page 6: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Docker in OpenStack Havana

– Nova virt driver which integrates with docker REST API on backend– Glance translator to integrate docker images with Glance

Icehouse– Heat plugin for docker

Both options are still under development

nova-docker virt driver docker heat plugin

DockerInc::Docker::Container

(plugin)

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Benchmark Environment Topology @ SoftLayer

glance api / reg

nova api / cond / etc

keystone

rally

nova api / cond / etc

cinder api / sch / vol

docker lxc

dstat

controller compute node

glance api / reg

nova api / cond / etc

keystone

rally

nova api / cond / etc

cinder api / sch / vol

KVM

dstat

controller compute node

+Awesome!

+Awesome!

Page 8: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Benchmark SpecsSpec Controller Node (4CPU x 8G RAM) Compute Node (16CPU x 96G RAM)

Environment Bare Metal @ SoftLayer Bare Metal @ SoftLayer

Mother Board SuperMicro X8SIE-F Intel Xeon QuadCore SingleProc SATA [1Proc]

SuperMicro X8DTU-F_R2 Intel Xeon HexCore DualProc [2Proc]

CPU Intel Xeon-Lynnfield 3470-Quadcore [2.93GHz] (Intel Xeon-Westmere 5620-Quadcore [2.4GHz]) x 2

Memory (Kingston 4GB DDR3 2Rx8 4GB DDR3 2Rx8 [4GB]) x2 (Kingston 16GB DDR3 2Rx4 16GB DDR3 2Rx4 [16GB]) x 6

HDD (LOCAL) Digital WD Caviar RE3 WD5002ABYS [500GB]; SATAII Western Digital WD Caviar RE4 WD5003ABYX [500GB]; SATAII

NIC eth0/eth1 @ 100 Mbps eth0/eth1 @100 Mbps

Operating System Ubuntu 12.04 LTS 64bit Ubuntu 12.04 LTS 64bit

Kernel 3.5.0-48-generic 3.8.0-38-generic

IO Scheduler deadline deadline

Hypervisor tested NA - KVM 1.0 + virtio + KSM (memory deduplication)- docker 0.10.0 + go1.2.1 + commit dc9c28f + AUFS

OpenStack Trunk master via devstack Trunk master via devstack. Libvirt KVM nova driver / nova-docker virt driver

OpenStack Benchmark Client

OpenStack project rally NA

Metrics Collection NA dstat

Guest Benchmark Driver NA - Sysbench 0.4.12- mbw 1.1.1.-2- iibench (py)- netperf 2.5.0-1 - Blogbench 1.1- cpu_bench.py

VM Image NA - Scenario 1 (KVM): official ubuntu 12.04 image + mysql snapshotted and exported to qcow2 – 1080 MB

- Scenario 2 (docker): guillermo/mysql -- 381.5 MB

Hosted @

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STEADY STATE VM PACKING

OpenStack Cloudy Benchmark

Page 10: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing Benchmark scenario overview

– Pre-cache VM image on compute node prior to test– Boot 15 VM asynchronously in succession– Wait for 5 minutes (to achieve steady-state on the

compute node)– Delete all 15 VMs asynchronously in succession

Benchmark driver– cpu_bench.py

High level goals– Understand compute node characteristics under

steady-state conditions with 15 packed / active VMs

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 4702468

10121416

Benchmark Visualization

VMs

Time

Activ

e VM

s

Page 11: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing

1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161 171 181 191 201 211 221 231 241 251 261 271 281 291 301 311 3210

1020304050607080

Docker: Compute Node CPU (full test duration)

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 0.54

– 0.17

1 11 21 31 41 51 61 71 81 91 1011111211311411511611711811912012112212312412512612712812913013113213313410

1020304050607080

KVM: Compute Node CPU (full test duration)

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 7.64

– 1.4

Page 12: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204 2110

2

4

6

8

10

12

14

Docker: Compute Node Steady-State CPU (segment: 31s – 243s)

usrsys

Time (31s – 243s)

CPU

Usag

e In

Per

cent

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 197 204 2110

2

4

6

8

10

12

14

KVM: Compute Node Steady-State CPU (segment: 95s – 307s)

usrsys

Time (95s - 307s)

CPU

Usag

e In

Per

cent

Averages

– 0.2

– 0.03

Averages

– 1.91

– 0.36

31 seconds243 seconds

95 seconds307 seconds

Page 13: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 1061131201271341411481551621691761831901972042110

2

4

6

8

10

12

14

Docker / KVM: Compute Node Steady-State CPU (Segment Overlay)

docker-usrdocker-syskvm-usrkvm-sys

Time: KVM(95s - 307s) Docker(31s – 243s)

CPU

Usag

e In

Per

cent

docker: 31sKVM: 95s

docker: 243sKVM: 307s

Docker Averages

– 0.2

– 0.03

KVM Averages

– 1.91

– 0.36

Page 14: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing

1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181 193 205 217 229 241 253 265 277 289 301 313 325 3370.00E+00

1.00E+09

2.00E+09

3.00E+09

4.00E+09

5.00E+09

6.00E+09

7.00E+09

Docker / KVM: Compute Node Used Memory (Overlay)

kvmdocker

Axis Title

Mem

ory

Used

dockerDelta734 MBPer VM49 MB

KVMDelta4387 MBPer VM292 MB

Page 15: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Steady State Packing

1 11 21 31 41 51 61 71 81 91 1011111211311411511611711811912012112212312412512612712812913013113210

102030405060708090

100

Docker: Compute Node 1m Load Average (full test duration)

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.15 %

1 11 21 31 41 51 61 71 81 91 1011111211311411511611711811912012112212312412512612712812913013113213310

102030405060708090

100

KVM: Compute Node 1m Load Average (full test duration)

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

35.9 %

Page 16: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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SERIALLY BOOT 15 VMS

OpenStack Cloudy Benchmark

Page 17: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot Benchmark scenario overview

– Pre-cache VM image on compute node prior to test– Boot VM– Wait for VM to become ACTIVE– Repeat the above steps for a total of 15 VMs– Delete all VMs

Benchmark driver– OpenStack Rally

High level goals– Understand compute node characteristics under

sustained VM boots

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2002468

10121416

Benchmark Visualization

VMs

Time

Activ

e VM

s

Page 18: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot

docker KVM0

1

2

3

4

5

6

7

3.52911310196

5.78166244825

Average Server Boot Time

Series1

Tim

e In

Sec

onds

Page 19: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 7905

101520253035

Docker: Compute Node CPU

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 1.39

– 0.57

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 1250

5

10

15

20

25

30

35

KVM: Compute Node CPU Usage

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 13.45

– 2.23

Page 20: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 1260

5

10

15

20

25

30

35

Docker / KVM: Compute Node CPU (Unnormalized Overlay)

kvm-usrkvm-sysdocker-usrdocker-sys

Time

CPU

Usag

e In

Per

cent

Page 21: Performance characteristics of traditional v ms vs docker containers (dockercon14)

04/10/2023 21

Cloudy Performance: Serial VM Boot

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 510

5

10

15

20

25

f(x) = 0.00948850678733032 x + 1.00804392156863

f(x) = 0.358234479638009 x + 1.0632956862745

Docker / KVM: Serial VM Boot Usr CPU (segment: 8s - 58s)

docker(8-58)Linear (docker(8-58))kvm(8-58)Linear (kvm(8-58))

Time (8s - 58s)

Usr C

PU In

Per

cent

8 seconds 58 seconds

Page 22: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 1260.00E+00

5.00E+08

1.00E+09

1.50E+09

2.00E+09

2.50E+09

3.00E+09

3.50E+09

4.00E+09

4.50E+09

5.00E+09

Docker / KVM: Compute Node Memory Used (Unnormalized Overlay)

kvmdocker

Time

Mem

ory

Used

DockerDelta677 MBPer VM45 MB

KVMDelta2737 MBPer VM182 MB

Page 23: Performance characteristics of traditional v ms vs docker containers (dockercon14)

04/10/2023 23

Cloudy Performance: Serial VM Boot

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 650.00E+00

5.00E+08

1.00E+09

1.50E+09

2.00E+09

2.50E+09

3.00E+09

3.50E+09

f(x) = 11773408.1342657 x + 1449606116.43077

f(x) = 29765955.3118881 x + 1178597198.76923

Docker / KVM: Serial VM Boot Memory Usage (segment: 1s - 67s)

dockerLinear (docker)kvmLinear (kvm)

Time (1s - 67s)

Mem

ory

Usag

e

1 second 67 seconds

Page 24: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Boot

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 790

5

10

15

20

25

30

35

Docker: Compute Node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.25 %

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 12505

101520253035

KVM: Compute Node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

11.18 %

Page 25: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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SERIAL VM SOFT REBOOT

OpenStack Cloudy Benchmark

Page 26: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot Benchmark scenario overview

– Pre-cache VM image on compute node prior to test– Boot a VM & wait for it to become ACTIVE– Soft reboot the VM and wait for it to become ACTIVE

• Repeat reboot a total of 5 times– Delete VM– Repeat the above for a total of 5 VMs

Benchmark driver– OpenStack Rally

High level goals– Understand compute node characteristics under sustained VM reboots

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 550

1

2

3

4

5

6

Benchmark Visualization

Active VMs

Time

Activ

e VM

s

Page 27: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot

docker KVM0

20

40

60

80

100

120

140

2.57787958145

124.433238959

Average Server Reboot Time

Series1

Tim

e In

Sec

onds

Page 28: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot

docker KVM0

0.5

1

1.5

2

2.5

3

3.5

4

3.56758604053.47976005077

Average Server Delete Time

Series1

Tim

e In

Sec

onds

Page 29: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 1090123456789

10

Docker: Compute Node CPU

usrsys

Time

CPU

Usag

e In

Per

cent

3 129 255 381 507 633 759 885 1011113712631389151516411767189320192145227123972523264927752901302731530123456789

10

KVM: Compute Node CPU

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 0.69

– 0.26

Averages

– 0.84

– 0.18

Page 30: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 1090.00E+00

5.00E+08

1.00E+09

1.50E+09

2.00E+09

2.50E+09

Docker: Compute Node Used Memory

Memory

Time

Mem

ory

Used

Delta48 MB

3 143 283 423 563 703 843 983 1123126314031543168318231963210322432383252326632803294330830.00E+00

5.00E+08

1.00E+09

1.50E+09

2.00E+09

2.50E+09

KVM: Compute Node Used Memory

Memory

Time

Mem

ory

Used

Delta486 MB

Page 31: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Serial VM Reboot

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 1090

0.5

1

1.5

2

2.5

3

Docker: Compute Node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.4 %

3 129 255 381 507 633 759 885 1011113712631389151516411767189320192145227123972523264927752901302731530

0.5

1

1.5

2

2.5

3

KVM: Compute Node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.33 %

Page 32: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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SNAPSHOT VM TO IMAGE

OpenStack Cloudy Benchmark

Page 33: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Snapshot VM To Image Benchmark scenario overview

– Pre-cache VM image on compute node prior to test– Boot a VM– Wait for it to become ACTIVE– Snapshot the VM– Wait for image to become ACTIVE– Delete VM

Benchmark driver– OpenStack Rally

High level goals– Understand cloudy ops times from a user perspective

Page 34: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Snapshot VM To Image

docker KVM0

10

20

30

40

50

60

36.8875639439

48.0231380463

Average Snapshot Server Time

Series1

Tim

e In

Sec

onds

Page 35: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Snapshot VM To Image

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 650

1

2

3

4

5

6

7

Docker: Compute Node CPU

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 0.42

– 0.15

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 1130

1

2

3

4

5

6

7

KVM: Compute Node CPU

usrsys

Time

CPU

Usag

e In

Per

cent

Averages

– 1.46

– 1.0

Page 36: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Snapshot VM To Image

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 10110510911314800000001500000000152000000015400000001560000000158000000016000000001620000000164000000016600000001680000000

KVM: Compute Node Used Memory

Memory

Time

Mem

ory

Used

Delta114 MB

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 6516000000001610000000162000000016300000001640000000165000000016600000001670000000168000000016900000001700000000

Docker: Compute Node Memory Used

Memory

Time

Mem

ory

Used

Delta57 MB

Page 37: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloudy Performance: Snapshot VM To Image

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 650

0.020.040.060.08

0.10.120.14

Docker: Compute Node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.06 %

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 1130

0.10.20.30.40.50.60.70.80.9

KVM: Compute node 1m Load Average

1m

Time

1 M

inut

e Lo

ad A

vera

ge

Average

0.47 %

Page 38: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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GUEST PERFORMANCE BENCHMARKS

Guest VM Benchmark

Page 39: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: Network

docker KVM0

100

200

300

400

500

600

700

800

900

1000940.26 940.56

Network Throughput

Series1

Thro

ughp

ut In

10^

6 bi

ts/s

econ

d

Page 40: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: Near Bare Metal Performance

Typical docker LXC performance near par with bare metal

linpack performance @ 45000

0

50

100

150

200

250

vcpus

GF

lop

s

220.77Bare metal220.5

@32 vcpu

220.9@ 31 vcpu

MEMCPY DUMB MCBLOCK0

2000

4000

6000

8000

10000

12000

14000

Memory Benchmark Performance

Bare Metal (MiB/s)docker (MiB/s)KVM (MiB/s)

Memory Test

MiB

/s

Page 41: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: Block I/O

Tested with [standard] AUFS

Bare Metal docker0

100

200

300

400

500

600

700

800

900 845 822

Async I/Odd if=/dev/zero of=/tmp/d4g bs=4G count=1

Series1

MB/

s

Bare Metal docker0

102030405060708090

10090.1 87.2

Sync Data Writedd if=/dev/zero of=/tmp/d4g bs=4G count=1 oflag=dsync

Series1

MB/

s

Bare Metal docker0

102030405060708090

10089.2 89

Sync Data / Metadata Writedd if=/dev/zero of=/tmp/d4g bs=4G count=1 oflag=sync

Series1

MB/

s

Page 42: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: File I/O Random Read / Write

1 2 4 8 16 32 640

200

400

600

800

1000

1200

1400

1600

Sysbench Synchronous File I/O Random Read/Write @ R/W Ratio of 1.50

dockerKVM

Threads

Tota

l Tra

nsfe

rred

In K

b/se

c

Page 43: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: MySQL OLTP

1 2 4 8 16 32 640

2000

4000

6000

8000

10000

12000

14000

MySQL OLTP Random Transactional R/W (60s)

dockerKVM

Threads

Tota

l Tra

nsac

tions

Page 44: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Guest Ops: MySQL Indexed Insertion

100000 200000 300000 400000 500000 600000 700000 800000 900000 10000000

20

40

60

80

100

120

140

MySQL Indexed Insertion @ 100K Intervals

dockerkvm

Table Size In Rows

Seco

nds P

er 1

00K

Inse

rtion

Bat

ch

Page 45: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Cloud Management Impacts on docker LXC

docker cli nova-docker0

0.5

1

1.5

2

2.5

3

3.5

4

0.17

3.52911310196

Docker: Boot Container - CLI vs Nova Virt

Series1

Seco

nds

Cloud management often caps true ops performance of LXC

Page 46: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Ubuntu MySQL Image Size

docker kvm0

200

400

600

800

1000

1200

381.5

1080

Docker / KVM: Ubuntu MySQL

Series1

Size

In M

B

Out of the box JeOS images for docker are lightweight

Page 47: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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In Summary

Near bare metal performance in the guest Fast operations in the Cloud

– Often capped by Cloud management framework Reduced resource consumption (CPU, MEM) on the compute

node – greater density Out of the box smaller image footprint

Page 48: Performance characteristics of traditional v ms vs docker containers (dockercon14)

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Parting Thoughts: Ecosystem Synergy

Category Factors ScopeCAPEX

Hardware costs - VM density (consolidation ratio)- Soft device integration- Broad vendor compatibility

- Hypervisor- Cloud manager

Software licensing costs - Software purchase price- Support contracts

- Hypervisor- Cloud manager

OPEX

Disaster recovery - Hypervisor- Cloud manager

Upgrade / maintenance expenses - Hypervisor- Cloud manager

Power & cooling costs - Reduced HW footprint - Hypervisor- Cloud manager

Administration efficiency - Automated operations- Performance / response time

- Hypervisor- Cloud manager

Support & training costs - Hypervisor- Cloud manager

AGILITY

Application delivery time - Workflow complexity- Toolset costs- Skillset

- Hypervisor- Cloud manager

Planned / unplanned downtime - Hypervisor- Cloud manager

Displacement of enterprise players requires full stack solutions

*Not a complete or extensive list

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References & Related Links http://www.slideshare.net/BodenRussell/realizing-linux-containerslxc http://bodenr.blogspot.com/2014/05/kvm-and-docker-lxc-benchmarking-with.html https://www.docker.io/ http://sysbench.sourceforge.net/ http://dag.wiee.rs/home-made/dstat/ http://www.openstack.org/ https://wiki.openstack.org/wiki/Rally https://wiki.openstack.org/wiki/Docker http://devstack.org/ http://www.linux-kvm.org/page/Main_Page https://github.com/stackforge/nova-docker https://github.com/dotcloud/docker-registry http://www.netperf.org/netperf/ http://www.tokutek.com/products/iibench/ http://www.brendangregg.com/activebenchmarking.html http://wiki.openvz.org/Performance http://www.slideshare.net/jpetazzo/linux-containers-lxc-docker-and-security (images)

– http://www.publicdomainpictures.net/view-image.php?image=11972&picture=dollars– http://www.publicdomainpictures.net/view-image.php?image=1888&picture=zoom– http://www.publicdomainpictures.net/view-image.php?image=6059&picture=ge-building

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Thank You… Questions?