Accelerating the adoption of Cloud Computing

Planning an OpenStack PoC Webinar

April 10, 2014

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Speakers Today

–  20 years as architect of infrastructure solutions for the enterprise

–  Experience designing and deploying across US, APAC and Emerging Markets

–  Specializes in infrastructure adoption in the worlds largest enterprises across people, process and technology

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–  Managed and delivered some of the largest cloud deployments, both public and private, worldwide

–  Business and technical leadership to service providers and enterprises around the world

–  Prior to Solinea, Seth was a Director in the Product Management Group at Cloudscaling

Brad Vaughan

Seth Fox

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Solinea Overview

Cloud is the only domain we focus on, with vertical industry and horizontal solutions specialization

Purpose-built for cloud

Track record of success architecting, building and operating production clouds – private and public – world-wide

Proven Delivery Success

We understand cloud adoption challenges of global companies

Enterprise IT Experience

Integrated capabilities lifecycle: cloud strategy, architecture, implementation and adoption services

Unique Approach

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Accelerating Open Infrastructure Adoption

Built the first OpenStack production clouds and contributors to the platform since its inception

OpenStack™ Experience

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Webinar Agenda

Why a Proof of Concept (PoC)? Select PoC Candidate Workloads Creating a Test Plan PoC Architecture Deployment Planning Solinea Jumpstart Methodology

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Technology Evaluation Continuum

Sandbox •  Informal exploration of

technology •  Small scale

installation to allow for experimentation

•  Single user/operator testing

Proof of Concept •  Quantifiable proof of business value to

multiple business stakeholders •  Scoped and budgeted project with

assigned staffing •  Proving technical viability for specific

use case and solution •  May also evaluate competing

solutions •  Fully understand the impact/value

across multiple business units/workloads

Pilot •  Initial build-out of

tested solution •  Limited user

community and SLAs •  Operated with

production tooling and support

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Setting Goals & Criteria

Sandbox •  No predefined goals

or criteria •  Reduced HW

footprint •  Functional

understanding of technology

Proof of Concept •  Prove a hypothesis •  Goals must be directly link to the

business requirements for approving next steps •  Generate convincing data

comparing current state solution •  Prove ROI and Investment

•  Gain practical skills and understanding, to properly design the end state

•  Understand impact on IT lifecycle service development and delivery process

Pilot •  Production quality/

performance goals •  Successful

completion of Preproduction QA testing

•  Completion of user testing

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Candidate Workloads

!  Selection Criteria –  Solve a existing problem –  Workload/application profile –  Representative architecture pattern –  Complexity and dependency –  Supportability, Customization

!  Stakeholder Involvement –  Resource commitment –  Is the pain point real

!  Measurability –  Existing quantifiable testing –  Historical data

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Selecting Tests

!  Defining the scope (breadth and depth of PoC) !  Defines timeline, cost and complexity !  Application level testing

–  Primary issue is finding existing test with actual data –  Needs to be self contained with limited dependency on other production

or test/dev systems –  Many applications require refactoring to take advantage of cloud

architecture !  Largest number of tests are generally functional testing

–  Auto-scaling –  High Availability –  Operational

!  Non-functional tests can be challenging –  PoC is usually only functional simulation of production –  Performance, capacity limited unless you have comparable benchmarks

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Creating a Test Plan

!  The candidate selection process should have identified a workloads with existing test harness

!  Developing, architecting and implementing testing tools is time consuming and complicated

!  Formal definition of use cases is required to ensure a valid scope

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Use Case ID Purpose Pre-requisites Required Data Steps Expected Results Actual Results

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OpenStack Operational Use Cases

!  Exercise the APIs –  Create and destroy

Objects (e.g. users, tenants, flavors, image)

–  Start/Stop, Enable/Disable

!  Non-functional features –  Upgrading the

environment –  High availability /

Failover !  Backup and recover

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OpenStack Testing Tools

!  Several tools available –  Tempest: automated CI/CD test suite for OpenStack –  Rally: benchmark OpenStack at scale

!  Valuable to validate PoC platform install prior to running other tests

!  Can be very complicated to configure !  Types of Tests

–  API – RESTful calls –  CLI – read-only actions of the client –  Scenario – often operational actions –  Stress – used primarily to identify race condition bugs –  3rd Party – test non-native API’s like EC2 compatibility

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This test showcases the ability for the cluster to grow and shrink as needed to handle expected and unexpected high load and can scale according to the level of load pushed against the cluster

Benefits

Results 1 2

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Once the stress testing load was initiated there was about 60K to 80K requests per second. During this initial phase the single caching server generated a sustained CPU load over 75% (Red Bars). This triggers a heat alarm which will launch and configure a new caching server.

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This new caching server is joined to the cluster and gets an equal number of requests distributed to itself. This causes the overall Cluster CPU load average to decrease by roughly half. This should allow the overall cluster to handle significantly more requests per second.

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Test Results: Auto Scaling

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Example PoC Plan

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!  Equipment –  Rack

•  RUs, Power, A/C –  Servers

•  Controller, Storage, Compute

–  Storage •  Storage software,

drives, backup space

–  Networking •  Networks, IPs, SSL

certs

!  Software & Data –  OpenStack Code –  Application Software

•  Licenses •  Who will install •  Who will customize

–  Testing Tools •  Install and configure

–  Sample Datasets •  Which datasets (live,

test) ?

!  Privacy and Security

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Identifying the Prerequisites

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Example Skills Matrix

Role Networking Compute Storage Other

“OpenStack” Generalist

Good Linux networking experience

Excellent hypervisor skills Excellent Linux administration skills Config management with Puppet, Chef, etc.

Experience administrating iSCSI or NFS servers

General python scripting Experience using OpenStack clouds

Network Specialist Strong general L2/L3 skills with chosen ToR switches Excellent virtualized networking skills (OVS, linux bridging, etc.)

Experience with chosen hypervisor(s) Experience with NICs and IPMI/ILo on chosen hardware

Understanding of network tuning for iSCSI / NFS traffic

Storage Specialist Familiarity with iSCSI / NFS tuning

Excellent tuning/troubleshooting with chosen storage

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OpenStack Distributions

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Sandbox • DevStack • RDO • Fuel

Proof of Concept • RDO/RHEL OSP • Fuel • Piston • Cloudscaling • Stackops • Many others …

Pilot • RHEL OSP • Fuel • Piston • Cloudscaling • Stackops • Many others …

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Distribution Selection Criteria

!  Price !  Adoption !  Support Offerings !  Installation Simplicity !  Maintainability and Management !  OpenStack release !  Value Added Tools !  Specialized Features

–  Storage –  VMware integration –  Quota –  SDN

!  Familiarity

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Logical Architecture

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Object Store •  Swift Proxy •  Container •  Object •  Account

Controller(s) •  All APIs

except Swift •  Neutron

gateway •  Qpid •  MySQL

Jump Box •  Foreman •  Repository •  Heat VM •  Horizon •  SSH

Compute •  Nova compute •  Neutron agent Block

•  iSCSI •  Cinder

IPMI Network

Mgmt Network

Storage Network

Public Network

192.168.103.0/24

Private Network 192.168.1.0/24 Floating IPs 10.10.1.0/24

192.168.102.0/24

192.168.101.0/24

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Unit   Segment   Role   Hardware  42  

Network  Switch  (IPMI)   Cisco  2xxx  

41   Switch  (Service)   Arista  7150  40   Switch  (Management)   Cisco  3xxx  39  

Management  

cntr-­‐01   Quanta  X12RS  38   cntr-­‐02   Quanta  X12RS  37   cntr-­‐03   Quanta  X12RS  36   cntr-­‐04   Quanta  X12RS  35   cntr-­‐05   Quanta  X12RS  34   cntr-­‐06   Quanta  X12RS  33  

Compute  

comp-­‐01   Quanta  X12RS  32   comp-­‐02   Quanta  X12RS  31   comp-­‐03   Quanta  X12RS  30   comp-­‐04   Quanta  X12RS  29   comp-­‐05   Quanta  X12RS  28   comp-­‐06   Quanta  X12RS  27   comp-­‐07   Quanta  X12RS  26   comp-­‐08   Quanta  X12RS  25   comp-­‐09   Quanta  X12RS  24   comp-­‐10   Quanta  X12RS  23   KVM   Monitor  +  KVM   Dell  KVM  22  21   Admin   jump-­‐01   Quanta  X12RS  20  

Block  

iscsi-­‐01   Quanta  X22RQ  19  18   iscsi-­‐02   Quanta  X22RQ  17  16   iscsi-­‐03   Quanta  X22RQ  15  14  

Object  

obj-­‐01   Quanta  X22RQ  13  12   obj-­‐02   Quanta  X22RQ  11  10   obj-­‐03   Quanta  X22RQ  9  8   obj-­‐04   Quanta  X22RQ  7  6   obj-­‐05   Quanta  X22RQ  5  4  

           

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!  Servers –  Minimal server hardware

configuration diversity –  One model for compute, one

for storage –  Most people segregate

compute, object and block storage from controller nodes

!  ToR Switches –  10Gb networking for public,

management and data networks

–  1GB for IPMI !  Storage will be determined

by workload needs –  NFS, iSCSI, Swift and Ceph

dominate storage configs

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Example Hardware Design

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OpenStack PoC Evaluation Weighting (0 to 5) 5=most

important

RHEL OSP SUSE

Rank Weighted Score Rank Weighted Score Criteria

1. Compute Resources This category defines the attributes of the compute resource that are under control of the end user. The end user should be able to configure the capacity and attributes of a compute unit with minimal friction and deploy the appropriate level of resources without the need to "over provision". The ideal situation is to have granular control over both the workload capacity of the compute unit and the service level. The compute unit should be able to easily scale to meet a variety of workloads, I.E. once the initial compute unit is provisioned you should be able to easily add incremental and storage resources.

Compute  B. Ability to configure private flavors 4 5 20 3 12 C. Ability to configure memory in GB increments from .5 to 128 4 5 20 4 0 D. Ability to configure attached storage in GB increments to 1TB 4 5 20 3 12 F. Ability to meter usage in 1 hour increments 1 5 5 2 2 G. Compute resource configuration changes can be made via the portal or via an API call 5 5 25 1 5

H. Ability to upload images into service catalog 5 5 25 2 10 I. 3 5 15 2 6

Compute Score 5.0 18.6 2.4 6.7 Allocation of Compute Score 15% 0.8 2.79 0.4 1.01

                       2. Storage Resources

This category defines the attributes of the storage services that are under control of the end user. Two categories of storage services are listed Object based storage and Block based storage. Object based storage, which would be appropriate for storing backups, images, archives, etc. Object based storage is used when latency and performance are not top criteria and low cost/high volume requirements preside. Object based storage is not part of the local attached file system. Amazon web services S3 or Openstack SWIFT are examples of object based storage. Block based storage refers to the typical file system storage that is directly accessible by OS

and conforms to the file system structure in use by the Guest OS. Block based storage can be delivered using a variety of service levels and is often classified using IOPS , latency or QoS levels.

Object  based  storage                      A. Ability to read, write and delete and Secure objects ranging in size from 1 byte to 5 terabytes 2 3 6 1 2

B. Objects can be stored over geographically tiered locations 1 4 4 2 2 E. Accessible via APIs 1 5 5 3 3 E. Objects are taggable and versioned 1 3 3 4 4 F. Objects are replicated to multiple locations 1 2 2 6 6

Block-­‐based  storage                      A. Integrate with compute (attach/detach) 3 2 6 3 9 B. Multiple SLAs based tiers of block storage service 3 5 15 1 3 C. Ability to provide point-in-time snapshot backups

2 5 10 5 10

D. Ability to resize volumes 1 5 5 7 7 E. Available across geographically dispersed locations 1 5 5 3 3 F. Storage has configurable IOPS 1 5 5 1 1 G. Metering is produced on volume/GB hours 1 5 5 2 2

Storage Score 4.1 5.9 3.2 4.3 Allocation of Storage Score 15% 0.6 0.89 0.5 0.65

!  Weighted ranking approach to evaluation –  Simple pass/fail testing

doesn’t capture flexibility and non-functional capabilities

–  Scoring metrics should be detailed to reduce subjective nature

!  Each use case and test should have several rating criteria

!  Should always be accompanied by testing output and narrative for executive audiences

!  Very useful in vendor/technology comparisons

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Evaluation Example

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Example: Cloud vs. Appliance Evaluation

PoC !  Cost: $125K + Services !  Timeframe: 3 weeks !  Performance: 40 minutes

Legacy Appliance •  Cost: $1.2MM •  Timeframe: 2 weeks •  Performance: Did not compute

Use Case Tested for Comparative Purposes: • A predefined and parsed data set is preloaded on Hadoop

• Map/Reduce transforms the data to a number of key and value pairs

• The Map/Reduce job is submitted • Job is monitored for completion

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Workshop !  Workload Analysis and

Categorization !  IaaS architecture confirmation !  Bill of Materials (BoM) !  Implementation Plan to

immediately go into POC

Proof of Concept !  Logical & Physical Architecture !  OpenStack Build Specification !  OpenStack Cloud (single rack); !  Training & Mentoring Program.

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Solinea Services

! ! !"Conceive Architect Integrate Adopt

We can make your PoC a success! A repeatable methodology. Proven with our customers.

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Resources Available on solinea.com

!  Slides / Project Plans for this webinar –  Replay and Materials available in 24-48 Hours –  Emails will be sent with link

!  Upcoming Webinars –  OpenStack Icehouse Preview – April 22nd

!  Replays / Downloads Available Now –  Building OpenStack Block Storage into your Cloud –  Making the case for OpenStack in the Enterprise –  OpenStack Breaking into the Enterprise

Accelerating the adoption of Cloud Computing

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