Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI

Advanced Topics for Micro Services: From Data Streams to Online Monitoring (Wintersemester 2019/2020)

Dozent: Prof. Dr. Holger Giese (Systemanalyse und Modellierung) , Thomas Brand (Systemanalyse und Modellierung) , Lucas Sakizloglou (Systemanalyse und Modellierung)

Allgemeine Information

  • Semesterwochenstunden: 2
  • ECTS: 3
  • Benotet: Ja
  • Einschreibefrist: 01.10.-30.10.2019
  • Lehrform: Seminar
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch

Studiengänge & Module

IT-Systems Engineering MA
  • OSIS-Konzepte und Methoden
  • OSIS-Spezialisierung
  • OSIS-Techniken und Werkzeuge
  • SAMT-Konzepte und Methoden
  • SAMT-Spezialisierung
  • SAMT-Techniken und Werkzeuge


The microservice architectural style puts each element of software functionality into a separate service. Perhaps the most distinctive characteristics of the style are the following i) each service is independently deployable, ii) the deployment of services is fully automated and can be scaled up or down depending on the type and volume of the workload, and iii) the centralized management of services should be kept to a bare minimum (for more information see [1] and the figure below from the same source). In this seminar we concentrate on this last characteristic.

As services are being deployed and scaled, the microservice architecture can produce abundant data. In fact, each service can potentially produce a data stream that consist of events pertaining to the service. The question then arises as to how to generate, store, and utilize this data systematically in order to manage the architecture, without compromising the typical microservices characteristics.  With this question in mind, we will study the online monitoring (that is, data about the running system is analyzed for complex, time-dependent properties as it arrives and not ex post) of data related to a microservice architecture. A key element of monitoring is the underlying data model and this will indeed be the other main focus of this seminar.

We offer a selection of topics on these two aspects. For data modeling, the topics focus on sources and types of data about microservices and suitable data structures to represent architectural changes over time. For data monitoring, the topics focus on frameworks to process and monitor streams of events representing architectural changes.


[1] Martin Fowler. Characteristics of a Microservice Architecture. [Online; accessed: 2019-09-20]. 2019. URL: martinfowler.com/articles/microservices. html.

[2] Microsoft Azure. Microservices Architectural Style. [Online; accessed: 2019- 09-17]. 2019. URL: docs.microsoft.com/en-us/azure/ architecture/guide/architecture-styles/microservices.

Lern- und Lehrformen

There will be an introductory, mandatory meeting introducing basic concepts and topics. Students are then required to choose a topic. Afterwards, an assignment and corresponding material per topic will be given to students. The students are expected to submit a report with their respective assignments and present their findings in a final meeting.

Throughout the seminar, further meetings can be arranged, in order to answer questions of general interest. Students can work in teams.


We will grade the student reports (50%) and presentations (50%). Participation in the final meeting during other students' presentations in the form of questions and feedback is also mandatory.


Besides individual feedback meetings with the teaching assistants and the introductory meeting, there will not be any other regular meetings during the semester. Presentations will be given on the same day (date to be determined) usually near to the end of the lecture time of the semester.

The first meeting will be held on 16 October in room H-2.58 at 15:15.

For questions, please send us an email.