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Monitoring Support for Manta Flow Agent in Cloud-Based Architecture
Název práce v češtině: Podpora monitorování Manta Flow agentů v cloudové architektuře
Název v anglickém jazyce: Monitoring Support for Manta Flow Agent in Cloud-Based Architecture
Klíčová slova: monitoring|time series databázy|Java inštrumentačný agent|multi-agentné prostredie|cloud architektura
Klíčová slova anglicky: monitoring|Java instrumentation agent|multi-agent environment|cloud architecture|time series databases
Akademický rok vypsání: 2021/2022
Typ práce: diplomová práce
Jazyk práce: angličtina
Ústav: Katedra distribuovaných a spolehlivých systémů (32-KDSS)
Vedoucí / školitel: doc. RNDr. Pavel Parízek, Ph.D.
Řešitel: Mgr. Roman Firment - zadáno a potvrzeno stud. odd.
Datum přihlášení: 29.06.2021
Datum zadání: 30.06.2021
Datum potvrzení stud. oddělením: 09.07.2021
Datum a čas obhajoby: 07.06.2022 10:00
Datum odevzdání elektronické podoby:05.05.2022
Datum odevzdání tištěné podoby:16.05.2022
Datum proběhlé obhajoby: 07.06.2022
Oponenti: Mgr. Filip Kliber
 
 
 
Zásady pro vypracování
The next major version of the Manta Flow platform for data lineage analysis will support cloud-based architecture where only the necessary components, in particular the Manta Flow Agent with extractor plugins, should run in the customer's environment (on-premises), while all other components (e.g., the data lineage analysis itself) will be deployed somewhere in the cloud.
In this context, a very needed feature is the support for monitoring of the Manta Flow Agent, its status, communication with other components of the Manta Flow platform, and interaction with internal systems of the respective customer.

The goals of this master thesis project are the following:
(1) analyze functional requirements on the monitoring framework for Manta Flow Agent,
(2) analyze possible use cases of running multiple agents in the environment of a single customer, focusing on the management of agents and their interaction,
(3) then propose a solution that fits into the Manta Flow platform and reflects also important non-functional requirements (performance overhead, security risks), and
(4) finally create a proof-of-concept implementation just for the scenario of a single agent for one customer.

Results of the analysis will include the list of relevant metrics and discussion of possible ways how to retrieve their values.
The monitoring framework should also observe how efficiently agents (and their plugins) use resources in a computer system, that means CPU, memory usage, disk space, and network bandwidth, for example.
Author should use existing robust technologies and libraries for runtime monitoring of Java programs, such as JVM TI and JMX, and for bytecode instrumentation.
Seznam odborné literatury
1. Java Virtual Machine Tool Interface (JVM TI), https://docs.oracle.com/javase/8/docs/platform/jvmti/jvmti.html
2. Java Management Extensions (JMX), https://docs.oracle.com/javase/8/docs/technotes/guides/jmx
3. Java agent and package java.lang.instrument, https://docs.oracle.com/javase/8/docs/technotes/guides/instrumentation/index.html
4. Walter Binder, Jarle Hulaas, and Philippe Moret. Reengineering Standard Java Runtime Systems through Dynamic Bytecode Instrumentation. SCAM 2007
5. Luis Mastrangelo and Matthias Hauswirth. JNIF: Java Native Instrumentation Framework. PPPJ 2014
6. Holger Eichelberger and Klaus Schmid. Flexible resource monitoring of Java programs. Journal of Systems and Software, volume 93, 2014
 
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