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Provisioning Performance of
Cloud Microservice Platforms
Hamzeh Khazaei, Cornel Barna, Nasim Beigi-Mohammadi
and Marin Litoiu
University of Toronto and York University
hamzeh.khazaei@utoronot.ca
Oct 30, 2016
Agenda
• VM and containers
• Containers and microservices
• Microservice on top of macroservices
• Interactive layered performance model and experiments
• Preliminary results
• References
Oct 30,
2016
CSER-
2016
2
VMs and Containers
• Virtual Machines (VM) are a widely used building block of
workload management and deployment.
• VMs are quite mature and provide good performance and security
isolation.
• However, for applications that require higher flexibility at runtime
and less isolation, hypervisor based virtualization might not satisfy
the entire set of quality of service (QoS) requirements.
• A container runs on a kernel with similar performance isolation
and allocation characteristics as VMs but without the expensive
VM runtime management overhead.
Oct 30,
2016
CSER-
2016
3
Containers and Microservices
• Containerized microservices are being leveraged by
many software service providers for a number of
reasons:
– Lightweight
– Fast start-up
– Improved scalability and portability
– Reduced management overhead
– Enhanced reliability
– Consistent operating environment for development, testing,
and deployment (better DevOps)
– Improved continues integration and delivery
– Higher utilization of resourcesOct 30,
2016
CSER-
2016
4
Containers on top of VMs
• A flexible computing
model combines
Infrastructures-a-Service
(IaaS) with container
based Platform-as-a-
Service (PaaS).
• Nirmata, Docker Cloud,
Kubernetes and others
• There is a concern here,
however?
Oct 30,
2016
CSER-
2016
5
Microservice Platform on top of IaaS
Oct 30,
2016
CSER-
2016
6
Performance Model
Oct 30,
2016
CSER-
2016
7
Performance Model
Oct 30,
2016
CSER-
2016
8
VMSM
PsBPq
PMSM
CSM
α,β
λc
ηc
Microservice Platform (MSP)
Macroservice Infrastructure (MSI)
• We implement a MSP from
scratch in Java using Docker
engine, Swarm and Composer.
• Leverage it to estimate
measured parameters including
provisioning and deprovisioning
of containers and VMs on both
SAVI and Amazon EC2.
Experiment
9
Results
CSER-
2016
10Oct 30,
2016
References
1. Hamzeh Khazaei, Cornel Barna, Nasim Beigi-Mohammadi
and Marin Litoiu. Provisioning performance of cloud
microservice platforms. Accepted in 8thIEEE International
Conference on Cloud Computing Technology and Science
(CloudCom), June 2016, Luxembourg, Dec 2016.
2. Hamzeh Khazaei, Cornel Barna and Marin Litoiu. A model
based performance engineering of
containerized microservice platforms. Submitted to IEEE
Transaction on Cloud Computing, September 2016.
Oct 30,
2016
CSER-
2016
11

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Provisioning Performance of Cloud Microservice Platforms

  • 1. Provisioning Performance of Cloud Microservice Platforms Hamzeh Khazaei, Cornel Barna, Nasim Beigi-Mohammadi and Marin Litoiu University of Toronto and York University hamzeh.khazaei@utoronot.ca Oct 30, 2016
  • 2. Agenda • VM and containers • Containers and microservices • Microservice on top of macroservices • Interactive layered performance model and experiments • Preliminary results • References Oct 30, 2016 CSER- 2016 2
  • 3. VMs and Containers • Virtual Machines (VM) are a widely used building block of workload management and deployment. • VMs are quite mature and provide good performance and security isolation. • However, for applications that require higher flexibility at runtime and less isolation, hypervisor based virtualization might not satisfy the entire set of quality of service (QoS) requirements. • A container runs on a kernel with similar performance isolation and allocation characteristics as VMs but without the expensive VM runtime management overhead. Oct 30, 2016 CSER- 2016 3
  • 4. Containers and Microservices • Containerized microservices are being leveraged by many software service providers for a number of reasons: – Lightweight – Fast start-up – Improved scalability and portability – Reduced management overhead – Enhanced reliability – Consistent operating environment for development, testing, and deployment (better DevOps) – Improved continues integration and delivery – Higher utilization of resourcesOct 30, 2016 CSER- 2016 4
  • 5. Containers on top of VMs • A flexible computing model combines Infrastructures-a-Service (IaaS) with container based Platform-as-a- Service (PaaS). • Nirmata, Docker Cloud, Kubernetes and others • There is a concern here, however? Oct 30, 2016 CSER- 2016 5
  • 6. Microservice Platform on top of IaaS Oct 30, 2016 CSER- 2016 6
  • 9. • We implement a MSP from scratch in Java using Docker engine, Swarm and Composer. • Leverage it to estimate measured parameters including provisioning and deprovisioning of containers and VMs on both SAVI and Amazon EC2. Experiment 9
  • 11. References 1. Hamzeh Khazaei, Cornel Barna, Nasim Beigi-Mohammadi and Marin Litoiu. Provisioning performance of cloud microservice platforms. Accepted in 8thIEEE International Conference on Cloud Computing Technology and Science (CloudCom), June 2016, Luxembourg, Dec 2016. 2. Hamzeh Khazaei, Cornel Barna and Marin Litoiu. A model based performance engineering of containerized microservice platforms. Submitted to IEEE Transaction on Cloud Computing, September 2016. Oct 30, 2016 CSER- 2016 11

Editor's Notes

  1. Comparison of native deployment, VM deployment, native Docker and VM Docker of applications. The way and time an application can provision and deprovision resources determines the service response time and availability. So we decided to study the provisioning performance of microservices under this configuration.