Performance Engineering of Scalable Web Services

1.

Subject title

Performance Engineering of Scalable Web Services

Инженерство на перформанси на скалабилни веб сервиси

2.

Code

m23_s_009

3.

Study program

Data science in computer science and engineering, IT management, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Software for embedded systems, Software Engineering, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Software Engineering, Eco-informatics, Statistics and Data Analytics, IT management, Cloud Computing, Cloud Computing,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

ворн. проф. д-р Владимир Здравески

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

This course will enable the student to develop the performance of the scale applications or web services set up in the cloud, which will make the most of the virtual data centers to set up scalable applications and web services. It will help the student design and build scalability in the SAAS software. Mathematical Modeling for Best Performance Relationship / Price for a given application / service when setting up in a commercial cloud.

11.

Subject content:

SAAS performance and scalability testing. Regression performance testing. SEO. Benchmarking. Finding a bottleneck of Saas. Applying the theory of accommodation in the waiting rows in SOA. Caching effects. Impact of safety measures on software performance (node-node or end-end). Analytical modeling. Analysis of the results. Comparison of measurement modeling. Isolating performance. Challenges to solve software scalability. Modeling for choosing optimal infrastructure to software works in regions of superlinear acceleration, rather than in saturation regions. Extracting maximum performance from rented resources in the cloud.

12.

Learning methods:

Предавања, вежби, самостојна работа, проектни задачи, семинарски работи

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 15 + 0 + 0 + 0 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

15 hours

16.

Other forms of activities

16.1.

Project tasks

0 hours

16.2.

Independent tasks

0 hours

16.3.

Homework

0 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

0 points

17.3.

Activities and learning

0 points

17.4.

Final exam

0 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature