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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: 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