Best Practices for Validating the Performance of Data Center

Infrastructure

Henry He

Ixia

Game Changers

Big data - the world is getting hungrier and hungrier for data

Big data, Web 2.0 and social networking applications and mobile apps are all contributing to unprecedented growth in unstructured data

Don’t let your data center be the bottle neck

• 2.5B pieces of content • 500+ TB ingested per day • 2.7M Likes per day • 300M photos per day • 100+PB data in single

Hadoop cluster

• 25M+ Subscriber • 4M Rating per day • 3M Searches per day • 30M Plays a day • 1B hours of streamed

traffic in June 2012 • 75% select movies based

on recommendation

Data Center Scale

How do you validate the elastics scalability requirements to manage demands of Big Data applications?

Compute

Storage

Networking

All three vector limits need to be stretched to truly assess the big data application performance impact

Enterprise Challenges

Is my data secure?

How will my application workloads perform?

Private

Public Hybrid

Which cloud?

What is the capacity limits? How will the infrastructure scale as business grows ?

Provider Challenges Infrastructure hardening

Performance, quality of service delivery, security effectiveness of physical & virtual infrastructure

Optimization of resources Performance assessment of compute, network and storage infrastructure

Characterize the capacity limits

Improving application performance

End-to-end application workload performance and impact on user experience

IaaS

Compute Storage Network

Processor Memory

Nodes

Drives Images

Persistence

Internal External

Inter connect

Virtualization in Cloud Data Centers

Server, Storage and Network virtualization are critical aspect of data center deployment

“How can I guarantee the

performance of tier 1 applications

on my virtual infrastructure?”

Key Test Challenges: • What is the tradeoff between # of VMs and…

• I/O performance? • Throughput/latency of virtual components/hypervisor?

• How does VM mobility impact application performance? • QoS for different applications on a converged link? • Can the network infrastructure manage traffic growth?

New Test Tools

Need to seamlessly validate both virtual and physical data center infrastructure

Testing in a virtual environment requires “embedded” test tools

Virtual test ports act as VMs to: – Generate network and application traffic

– Measure throughput/latency

– Validate application performance

– Identify impact of VM mobility

Virtual test ports

Use Case: IO Performance

OBJECTIVE: Validate the converged traffic performance of virtualized servers and CNAs

TEST SETUP Install virtual Ixia ports inside the server

Attach physical Ixia ports to CNA

Apply real-world application I/O profiles with local and remote storage

KEY METRICS TCP/UDP throughput

Latency

Storage I/O performance (IOPS)

Error rates

Physical ports:

emulate the converged data center network

SUT

Virtual ports: emulate VMs,

generate & measure

application traffic

Use Case: CNA IO Performance

Latency

Measurements

I/O Throughput

Use Case: Live VM Migration

OBJECTIVE: Measure how applications/services are affected during live migration

TEST SETUP: Virtual test ports emulate and generate traffic between an HTTP Client and HTTP server. Migrate HTTP server to another host machine

KEY METRICS: Transaction Latencies

Transaction Rates

HTTP Client

HTTP Server HTTP

Server

Live Migration

Use Case: Live VM Migration

Transaction

Time

Transaction

Rates

Is HTTP adversely affected in the time it

takes for the VM to achieve full

operation state on new physical server?

Use Case: Virtual Appliance Tuning

OBJECTIVE: Compute resources are often assigned in an ad-hoc fashion and assigning more cores to VM can decrease performance Validate the optimal amount of compute resources to VMs

TEST SETUP: Vary compute resource (CPU, memory) assignment Generate realistic application workload on virtual appliance interfaces Use application emulation to validate the QoE metrics

KEY METRICS: Application Throughput Transactional Latencies Connection capacities and setup rates

1 CPU

2 CPUs

4 CPUs

Optimal

Use Case – Storage Performance

OBJECTIVE: Validate the virtualized and real storage performance impact

Understand the tradeoffs between different storage architectures FC, NAS/iSCSI or CDMI

Assess the impact of caching and data integrity

TEST SETUP: Use virtual Ixia ports or physical ports to emulate storage clients or initiators

Generate realistic storage workloads with user defined random data within the I/O

Validate the storage performance, user authentication and data integrity

When caching is in place validate the data reduction performance

KEY METRICS: Application Throughput

Transactional Latencies

Data Integrity Mismatch

Data Reduction Performance of WAN Optimization

Use Case: Network Performance

OBJECTIVE: Measure capacity, forwarding performance and energy efficiency

TEST SETUP: Physical or Virtual test ports generate and measure traffic across switching infrastructure

KEY METRICS: Port density

Traffic throughput, latency and loss

Power consumption

Use Case: Converged Storage Performance

OBJECTIVE: Verify no drop (no pause control) in absence of congestion

Verify rate drop (pause control) for the lower priority flows under congestion

TEST SETUP: Configure switching tiers with at least two PFC priorities for LAN and SAN traffic

Send different ratios of application and SAN traffic

Oversubscribe egress ports to observe PFC operation

KEY METRICS: Measure SAN and LAN traffic separately

Application and Storage throughput

Application and Storage latencies

Public test: Lippis Data Center Fabric Testing

Internet Browsing: North-South Client-Server/ South-North Server-Client Traffic Flows

Server Lookup & Data Retrieval: East-West Server-Database/ Database-Server Traffic Flows

IP-based Storage Requests & Retrieval: East-West Server-Storage/ Storage-Server Traffic Flows

Live VM Migration: East-West HTTP Server-Server Traffic Flows

QoS 100% Throughput

RFC 2544 RFC 2889

Low Latency/Jitter No Loss

Lippis Report Cloud Simulation Test

Public test: EANTC/LightReading Cisco CloudVerse

• End-to-end cloud validation

• Multi-tenancy

• Active-active fabric

• Tiered cloud services

• Virtual security gateway

• Service provisioning time

Testing the Elastics Data Centers

Measure performance of cloud infrastructure – VM scalability – Throughput and IO capacity of NAS or SAN

architectures – Forwarding performance of the networking

infrastructure (N-S vs E-W)

Emulate realistic application workloads – Compute and storage tuning for various

applications on virtualized infrastructure – Flexible IO generations for simulation of various

application workload patterns

Ensure data security and data integrity

– Realistic subscriber emulation with authentication to validate enterprise access policies

– Validate data corruption with byte-by-byte pattern matching

Validate the converged cloud infrastructure

– Unified platform to validate compute, storage & network in conjunction with applications

– Seamless validate both virtual and physical

End-to-end Converged Data Center Validation

Thank you

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