HCLOUD: RESOURCE-EFFICIENT PROVISIONING IN SHARED CLOUD SYSTEMS
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1 HCLOUD: RESOURCE-EFFICIENT PROVISIONING IN SHARED CLOUD SYSTEMS Christina Delimitrou 1 and Christos Kozyrakis 2 1 Stanford/Cornell University, 2 Stanford University/EPFL ASPLOS April 5 th 2016
2 Executive Summary Problem: cloud provisioning is difficult Many resource offerings à resource/cost inefficiencies Interference from other users à performance jitter HCloud: resource-efficient public cloud provisioning User provides resource reservations performance goals Automatic selection of instance type and configuration Adjust allocations between reserved and on-demand High utilization and low performance jitter 2
3 Motivation 3
4 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12
5 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11
6 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2
7 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small Cost, predictability, availability, flexibility, spin-up overheads, retention time, load fluctuation, external load, sensitivity to interference, A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2
8 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge t2.nano t2.micro t2.small t2.medium t2.large m4.large m4.xlarge m4.2xlarge m4.4xlarge m4.10xlarge m3.medium m3.large m3.xlarge m3.2xlarge c4.large c4.xlarge c4.2xlarge c4.4xlarge c4.8xlarge c3.large c3.xlarge c3.2xlarge c3.4xlarge c3.8xlarge r3.large r3.xlarge n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small n1-standard-1 n1-standard-2 n1-standard-4 n1-standard-8 n1-standard-16 n1-standard-32 n1-highmem-2 n1-highmem-4 n1-highmem-8 n1-highmem-16 n1-highmem-32 n1-highcpu-2 n1-highcpu-4 n1-highcpu-8 n1-highcpu-16 n1-highcpu-32 f1-micro g1-small A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2 A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 D1 D2 D3 D4 D11 D12 D13 D14 D1 v2 D2 v2 D3 v2 D4 v2 D5 v2 D11 v2
9 Cloud Provisioning Goals Determine appropriate instance size/type Determine appropriate instance configuration Dynamically adjust allocation decisions at runtime 9
10 Cloud Provisioning Scenarios Batch analytics, latency-critical applications, and scientific workloads in all scenarios Batch: 50% Latency: 40% Scientific: 10% 10
11 Provisioning Baselines All reserved (SR): 16vCPU instances on GCE, no external load Predictable performance, high cost, low flexibility lications provisioned for peak requirements All on-demand: Largest instances (OdF): only 16vCPU instances Mixed instances (OdM): mix of large and smaller instances Interference, low cost, high flexibility Resource management: Least-loaded scheduler 11
12 Extracting Resource Preferences Heterogeneity Combinations 1,000,000,000 Interference Resources per server Resource ratio 1,000,000 Number of servers lication params 1, servers 40 apps 100 servers 300 apps 1000 servers 1200 apps Systems Exhaustive characterization is infeasible 12
13 Quasar Overview [ASPLOS 14] User QoS Scheduler Resource preferences Cluster Profiling Data mining 13
14 Quasar Overview [ASPLOS 14] Scheduler User Resource preferences Greedy scheduler Cluster Profiling Data mining Resource selection 14
15 Quasar Overview [ASPLOS 14] Scheduler User Resource preferences Greedy scheduler Cluster Profiling Data mining Resource selection 15
16 Quasar Overview [ASPLOS 14] Scheduler User Resource preferences Greedy scheduler Cluster Profiling [5-30sec] Data mining [20msec] Resource selection [50msec-2sec] 16
17 Evaluation 17
18 Evaluation 18
19 Cloud Provisioning Goals Determine appropriate instance size/type Determine appropriate instance configuration Dynamically adjust allocation decisions at runtime 19
20 Hybrid Cloud Resource Allocation Insight: Combine reserved and on-demand resources Challenge: Separate applications between reserved (~private) and on-demand (public) resources 20
21 Hybrid Allocation Policies Perf. norm to Isolation (%) Reserved Resources HF HM P1 P2 P3 P4 P5 P6 P7 P8 Perf. norm to Isolation (%) On-Demand Resources HF HM P1 P2 P3 P4 P5 P6 P7 P8 Account for application interference sensitivity 21
22 Hybrid Allocation Policies Perf. norm to Isolation (%) Perf. norm to Isolation (%) Reserved Resources HF HM P1 P1 P2 P2 P3 P4 P5 P6 P7 P8 Perf. norm to Isolation (%) On-Demand Resources HF HM P1 P2 P3 P4 P5 P6 P7 P8 Account for application interference sensitivity Do not overload reserved resources 22
23 Hybrid Allocation Policies Perf. norm to Isolation (%) Perf. norm to Isolation (%) Reserved Resources HF HM P1 P1 P2 P2 P3 P3 P4 P4 P5 P5 P6 P6 P7 P7 P8 P8 Perf. norm to Isolation (%) On-Demand Resources HF HM P1 P2 P3 P4 P5 P6 P7 P8 Account for application interference sensitivity Do not overload reserved resources Dynamic decisions (e.g., utilization limits) 23
24 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically 24
25 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically 25
26 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically 26
27 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically (feedback loop on queue length) 27
28 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically (feedback loop on queue length) What signals a sensitive job? 28
29 HCloud Reserved On-demand Insights: Account for interference sensitivity Set load limits dynamically What signals a sensitive job? 29
30 Hybrid Allocation Policies Perf. norm to Isolation (%) Perf. norm to Isolation (%) Reserved Resources HF HF HM P1 P1 P2 P2 P3 P3 P4 P4 P5 P5 P6 P6 P7 P7 P8 P8 Perf. norm to Isolation (%) On-Demand Resources HF HM P1 P2 P3 P4 P5 P6 P7 P8 Account for application interference sensitivity Do not overload reserved resources Dynamic decisions (e.g., utilization limits) 30
31 Evaluation 31
32 Cloud Provisioning Goals Determine appropriate instance size/type Determine appropriate instance configuration Dynamically adjust allocation decisions at runtime 32
33 Adjusting Allocations at Runtime Runtime: monitor app performance Remove co-scheduled apps Reserved On-demand Move to larger instance within cluster Move to reserved cluster 33
34 Conclusions HCloud: hybrid cloud provisioning (reserved & on-demand) Account for interference sensitivity Account for performance-cost tradeoffs Adjust to load fluctuations 2.1x better performance than on-demand, 50% lower cost than reserved See paper for: Performance unpredictability analysis on EC2 and GCE Sensitivity studies on system & app parameters n Spin-up overheads, cost, retention time, load, app characteristics, external load, Further workload scenarios 34
35 Questions?? HCloud: hybrid cloud provisioning (reserved & on-demand) Account for interference sensitivity Account for performance-cost tradeoffs Adjust to load fluctuations 2.1x better performance than on-demand, 50% lower cost than reserved See paper for: Performance unpredictability analysis on EC2 and GCE Sensitivity studies on system & app parameters n Spin-up overheads, cost, retention time, load, app characteristics, external load, Further workload scenarios 35
36 Questions?? Thank you 36
37 Resource Efficiency 37
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