improving kieker's scalability by employing linked read-optimized

Improving Kieker’s Scalability by Employing Linked Read-Optimized and Write-Optimized NoSQL Storage

Armin Moebius | IBAK H. Hunger GmbH & Co. KG, Kiel, Germany Sven Ulrich | IBAK H. Hunger GmbH & Co. KG, Kiel, Germany

7th Symposium on Software Performance 2016

08.11.2016

Regression Benchmarking Execution Environment

Agenda

• Kieker extension for Apache Cassandra data storage

• Regression Benchmarking Execution Environment (RBEE) architecture excerpt

• Data storage with RBEE Monitoring Log

• Evaluation scenarios and details

• Conclusion

2 / 22 7th Symposium on Software Performance 2016 | Moebius & Ulrich| 08.11.2016

Introduction

7th Symposium on Software Performance 2016 | Moebius & Ulrich| 08.11.2016

• Bring regression benchmarks into continuous integration environments

• Improve Kieker’s scalability

• Create a gateway between Kieker and our RBEE Regression Benchmarking Execution Environment

kieker-monitoring.net rbee.io

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RBEE Architecture (Excerpt)


SUT

Communication Backend

Control Center

MLog

Com. API Com. API

Cassandra Extension

Benchmark Result

Repository

Com. API

Com. API

Microservices as self-contained Systems Virtual Machine

4 / 22

GUI

UI UI

Other SCS

Own Data Storage

Kieker Extension


• Enabling Kieker to store its monitoring output in Apache Cassandra

• Extending Kieker’s SyncDbWriter and AsyncDbWriter classes

• New classes: – CassandraDb: basic implementation to access Apache Cassandra

– CassandraSyncDbWriter: - extends Kieker’s AbstractMonitoringWriter - newMonitoringRecord() overwritten

– CassandraAsyncDbWriter: extends Kieker’s AbstractAsyncWriter - asynchronous implementation of our writer

– CassandraWriterThread: workerthreads for persisting monitoring data

• Added configuration parameters to kieker.monitoring.properties file

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Data Storage


MLog

Com. API

• Containerized system based on Docker

• Employs polyglot persistence – Apache Cassandra: write-optimized wide-column noSQL data storage

– ElasticSearch: read-optimized document store noSQL data storage

• Scales horizontally

• CTE pushes data asynchronously from Cassandra to ElasticSearch

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Linking Read- and Write-Optimized Storage


RBEE Monitoring Log

Keyspace

Col 2

Col n

Col 1

Tab 1 Tab 2 Tab n

Col 2

Col n

Col 1 Col 2

Col n

Col 1

{

"_index": "tab1",

"_type" : "tab1",

"_id" : "AVgf49kPr3sjN1Qg0hWa",

"_score" : 1.0,

"_source" : {

"col1" : 1,

"col2" : 2,

"coln" : "n"

}

}

Connecting to both

querying table names

fetching data for each table

sending data of each table

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Evaluation


• System under test (SUT) – Java-based employee work time registration system

– Swing-based GUI

– Exactly reproducible monitoring output is generated by executing a Marathon script

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Marathon </>

type numbers

Evaluation


• Test scenarios:

a) Non instrumented setup

b) Kieker file-based setup

c) Non containerized setup with read- and write-optimized data storage

Containerized setups

d) 1 container on 1 container host

e) 6 containers on 1 container host

f) 6 containers on 3 container hosts with 2 containers per container host

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Evaluation


• Test hardware:

– HP Workstation Z420 • Intel Xeon E5-2670, 32 GB RAM, SATA HDD, 1 GBit/s Lan

– HP Proliant DL380 G7 (Server) • 2x Intel Xeon X5650, 144 GB RAM, 16 SAS 10K HDDs, 1 GBit/s LAN

– HP ProCurve 2910al-24G (Switch) • Dedicated 24 Port Gigabit Switch

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Evaluation Results Part (a) – Execution Time


• Non-instrumented System Under Test (SUT)

11 / 22

Evaluation Results Part (b) – Execution Time


• Kieker instrumented system under Test (SUT)

• Logging to files on local file system

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Evaluation Results Part (c) – Execution Time


• Instrumented with Kieker

• No containerization

• Read- and write optimized data storage

HP ProCurve Gigabit Switch (Dedicated Ethernet)

Ubuntu 16.04 LTS

HP ProLiant DL380 G7

Instrumented System Under Test

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Evaluation Results Part (d) – Execution Time


• Containerization on physical hardware • Employing RBEE Monitoring Log (1 instance)

Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1



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Evaluation Results Part (e) – Execution Time


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1

• Containerization on physical hardware • Employing RBEE Monitoring Log (6 instances)



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Evaluation Results Part (f) – Execution Time


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1 Container Host 2 Container Host 3

D o c k e r S w a r m

• Containerization & Clustering • Employing RBEE Monitoring Log (3x2 instances)



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Evaluation Results – Execution Times - Summary


• Speedup of method’s execution times in relation to Kieker’s file based instrumentation:

– (c) RBEE Monitoring Log without containerization 8% faster

– (d) RBEE Monitoring Log Docker image (1 host | 1 instance) 12% faster

– (e) RBEE Monitoring Log Docker image (1 host | 6 instances) 14% faster

– (f) RBEE Monitoring Log Docker image (3 hosts | 2 instances each) 22% faster

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Evaluation Results Part (d) – Transfer Time


• Containerization on physical hardware • Employing RBEE Monitoring Log (1 instance)

Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1



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Evaluation Results Part (e) – Transfer Time


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1

• Containerization on physical hardware • Employing RBEE Monitoring Log (6 instances)



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Evaluation Results Part (f) – Transfer Time


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Ubuntu 16.04 LTS

Docker Engine

bins / libs


Container Host 1 Container Host 2 Container Host 3

D o c k e r S w a r m


• Containerization on physical hardware • Employing RBEE Monitoring Log (3x2 instances)


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Conclusion


• Employing linked write-optimized and read-optimized data storage for storing Kieker’s monitoring output reduce monitoring overhead

• The usage of RBEE Monitoring Log, built upon Docker, Apache Cassandra and ElasticSearch improves Kieker’s data storage scalability.

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Thank you


Kieker: http://www.kieker-monitoring.net

RBEE: http://www.rbee.io

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http://www.kieker-monitoring.net/



http://www.rbee.io/

improving kieker's scalability by employing linked read-optimized

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