Cloudward Bound: Planning for Beneficial Migration of Enterprise Applications to the Cloud Mohammad Hajjat, Xin Sun, Yu-Wei Sung (Purdue University) David.

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Cloudward Bound: Planning for Beneficial Migration of Enterprise Applications to the Cloud Mohammad Hajjat, Xin Sun, Yu-Wei Sung (Purdue University) David Maltz (Microsoft Research), Sanjay Rao (Purdue University), Kunwadee Sripanidkulchai (IBM T.J. Watson) Mohit Tawarmalani (Purdue University) 1

Cloud Computing “Most influential management ideas of the millenium” – Harvard Business Review Early successes (e.g., indexing NYTimes Archive) Much interest in migrating enterprises to the public cloud 2

Concerns with cloud computing Data privacy – National Privacy Laws – Industry-specific privacy laws (e.g., Health Care) SLA Requirements – Application response time – Availability 3

Hybrid Cloud Architectures an ACL Local Data Center Cloud back- end frontend Internet back-end (sensitive databases) front- end “ And there are some things they might not want to put in the cloud for security and reliability reasons….So, you've got to have these kinds of hybrid solutions.” Steve Ballmer, Microsoft CEO “We think it's a combination of putting applications in your own data center, and then use the cloud to take out peaks, or you could put specific things in the cloud.” Joe Tucci, EMC CEO “Virtually every enterprise will adopt a hybrid format” Russ Daniels, CTO of cloud computing, HP 4

Our focus #1 : Planning hybrid cloud layouts Cost savings, Application response times, Bandwidth costs Scale and complexity of enterprises applications back- end front- end Local Data Center back end an ACL Local Data Center Cloud back- end frontend Internet back end front- end

Our focus #2: migrating security policies an ACL permit frontend  backend port 8000 deny any  backend Local Data Center Cloud back- end frontend Internet back end front- end ? back- end front- end Local Data Center back end Security most important initiative for 83% of surveyed operators Security policies often realized using Access Control Lists (ACLs) Typical to see hundreds of firewall contexts, ACLs with hundreds of rules 6

Contributions of this paper Highlight complexity of enterprise applications, data- center policies Framing and providing first-cut solutions for two key challenges in migrating enterprises to hybrid cloud – Models for planning hybrid cloud deployments – Abstractions and algorithms for assurable migration of security policies Validations using real enterprise applications, Azure- based cloud deployments

Talk Outline Enterprise Applications Models for planning hybrid cloud deployments Assurable migration of security policies Evaluation and Results Related Work and Conclusion

Enterprise Applications E.g., Payroll, travel and expense reimbursement, customer relationship management etc. BE FE BL Front End (FE) Business Logic (BL) Back End (BE) 3-tier Application Structure 9 FE1FE2 BL1BL2 BL3 BL4BL5 BL1BL2BL3 BL4BL5

Enterprise Applications E.g., Payroll, travel and expense reimbursement, customer relationship management etc. 10 BE FE BL

Scale of enterprise applications 11

To determine: m i = number of servers of component C i to migrate to the cloud (m i ≤ N i ) T ij = number of transactions per second along (i,j) S ij = average size of transactions along (i,j) C0C0 C1C1 C2C2 C3C3 C4C4 C5C5 CiCi CjCj CkCk I E Enterprise App1 App2 Abstracting the planning problem Internal External N i = number of servers in component C i Ci Cj 12

Formulating the planning problem Local Data Center Cloud back- end frontend back-end (sensitive databases) front- end 13 Objective: Maximize cost savings on migration – Benefits due to hosting servers in the cloud – Cost increase/savings related to wide area Internet communication Constraints: – Policy constraints – Bounds on increase in transaction delay Future work: – Application availability

Partitioning requests after migration (1) Location sensitive routing Migrate C iL C jL C iR C jR T’ iR,jL T’ iL,jR T’ iL,jL T’ iR,jR Cloud Local DC CiCi CjCj T i,j Local DC (2) Location Independent routing Split in proportion to the number of servers in C jL and C jR Introduces non-linearity in constraints. 14

Modeling Approach 15 Model complexity Vs. Practicality of data collection Fine-grained models: Potentially more accurate Model parameters harder to collect Our Approach: Use easily available information (e.g., computation times of components and communication times on links) Empirical experience to drive iterative model refinements

Modeling user response times Ideally, desirable to bound increase in: – Mean response time – Response time variations (e.g., 95%ile response times). Bounding changes to mean delay relatively easier – Linearity of expectations Bounding delay variations harder – Feasible to bound changes to variance of response times By conditioning on path taken by transactions Independence assumptions Can be extended to applications with non path-like transactions – Conservative bounds on changes to delay percentiles feasible 16

Benefits/costs on migration Benefits due to hosting servers in the cloud – Economies of scale, lowered operational expenses – Estimates from Armbrust et al (Berkeley TR, 2009) – Benefits dependent on compute or storage servers – Future extension: savings due to using cloud for peaks Focus on recurring costs associated with migration Modeling costs related to Internet communication – Linear cost model – Matches charging model of EC2, Azure etc. 17

Talk Outline Enterprise Applications Models for planning hybrid cloud deployments Assurable migration of security policies Evaluation and Results Related Work and Conclusion

BE 2 R RRRR BE 1 a3a3 a3a3 a2a2 Local Data Center Internet (INT) BR = Border Router, AR = Access Router fe 2 FE fe 1 migrate Migration algorithm overview fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 t(a 3 ) BE 1 t(a 2 ) t(a 3 ) BE 2 t(a 2 ) t(a 3 ) INT t(a 1 )∩ t(a 2 ) t(a 1 )∩ t(a 3 ) t(a 3 ) t(a 1 )∩ t(a 2 ) t(a 3 ) fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 a3a3 a3a3 BE 1 a2a2 a2a2 a3a3 BE 2 a2a2 a2a2 a3a3 INT a1∩a2a1∩a2 a1∩a3a1∩a3 a1∩a3a1∩a3 a3a3 a1∩a2a1∩a2 a3a3 fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 BE 1 BE 2 INT a1∩a2a1∩a2 a1∩a2a1∩a2 Extract common ACLs and place them in new setting. Edge-cut-set between source and destination entities. Avoid unnecessary wide-area communication Symbolic representation for scalability Entities: BE 2 R RRRR BE 1 Internet (INT) fe 2 FE Cloud fe 1 Local Data Center fe 1 fe 2 BE 1 BE 2 INT fe 1 fe 2 t(a 3 ) BE 1 t(a 2 ) t(a 3 ) BE 2 t(a 2 ) t(a 3 ) INT t(a 1 )∩ t(a 2 ) t(a 1 )∩ t(a 3 ) a1a1 a2a2 a1a1 a2a2 Reachability Matrix (R)Transform R 19 t(a 2 )

Evaluation Evaluation Goals: – Are there scenarios where a hybrid approach makes sense? – Is it feasible to achieve cost savings with the cloud while meeting performance targets and policy constraints? – How effective are our planning models? Case Studies: – Windows Azure SDK application – Campus Enterprise Resource Planning (ERP) application 20

Experiments on cloud test-bed Thumbnail example application Two Azure data centers (DCs), represent local/remote Internal users: hosts in campus close to internal DC External users: Planetlab Reengineer application for hybrid cloud deployment 21

Results Plan requirements: increase in mean delay less than 10%, increase in variance less than 50% Algorithm Recommendation: Migrate 1 FE, 3 BL servers Observed: 17% increase in mean, 12% increase in variance 22

users FE 1 BL 1 BL 3 BL 2 FE 2 BL 4 BL 5 BE 3 78% Internal 22% external 30% 10% 20% 5% 59% 1% 9%22% 5% BE 1 BE 2 BE 5 BE 4 500GB 300GB 700GB 50GB Campus ERP application architecture (3) (7)(3) (2) (1) BE BL FE 23

Recommendations from planned migration approach Hybrid clouds can achieve cost savings while meeting enterprise policies and delay bounds See paper for sensitivity studies to benefit ratios 24

Migrating security policies: Evaluation users FE 1 BL 1 BL 3 BL 2 FE 2 BL 4 BL 5 BE 1 Campus Core Network R R R R RR a3a3 a4a4 a2a2 a1a1 a1a1 a2a2 Internet (INT) BL 1 BL 2 BL 3 BL 4 FE 2 FE 1 R a5a5 BL 5 R a7a7 BE R RR a3a3 Local Data Center BE 2 BE 3 BE 4 BE 5 25 BE

Migration scenario Campus Core Network R R R R RR a3a3 a4a4 a2a2 a1a1 a1a1 a2a2 Internet (INT) BL 1 BL 2 BL 3 BL 4 FE 2 FE 1 R a5a5 BL 5 R a7a7 BE R RR a3a3 Local Data Center 26

New ACL placement generated by our algorithms Local Data Center 27 Other Evaluations: Ensuring unauthorized traffic does not traverse the Internet Scalability to large networks

Related Work Recent works on partial application migration: – Teregowda et al, HotCloud 2010 – Clouds for disaster recovery alone: Wood et al, HotCloud 2010 Economics of using clouds: – Armbrust et al, Berkeley Technical Report, 2009 – Comparisons across providers: Li et al, HotCloud 2010 Security policies on migration to the cloud – Li et al, LADIS 2010 Other challenges with migrating enterprises – Wood et al, HotCloud 2009, … Work from cloud provider perspective – E.g., Shieh et al (HotCloud2010), Lam et al (UCSD TR, 2010),.. Analytical models of multi-tier applications – Urgaonkar et al, Sigmetrics

Conclusions Hybrid cloud models often make sense – Enable cost savings, while meeting enterprise policies and application response time requirements Planned approach to migration important and feasible – Algorithms for hybrid cloud layouts – Algorithms for correct reconfiguration of security policies Future Work – Exploring model complexity and performance inaccuracy – Wider range of application case studies – Take workload and network dynamics into account