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Application and distributed systems development in the Google Cloud Platform

Informacje ogólne

Kod przedmiotu: 1120-IN000-ISA-0505 Kod Erasmus / ISCED: (brak danych) / (brak danych)
Nazwa przedmiotu: Application and distributed systems development in the Google Cloud Platform
Jednostka: Wydział Matematyki i Nauk Informacyjnych
Grupy: Elective courses, Computer Science
Multilayer application development (elective block)
Punkty ECTS i inne: 4.00
Język prowadzenia: angielski
Skrócony opis: (tylko po angielsku)

Prerequisites: UNIX fundamentals, Programming (Java, Python), Programming in graphical environment, Databases

Course objective:

Google Cloud Platform allows its users to process data on servers owned by Google, using virtual machines, containers, functions, databases, or other dedicated cloud services. The platform also contains tools that help with monitoring and debugging production systems. In this set of lectures, we will explain the idea of Computing Cloud and present the most important services on Google Cloud Platform.

Pełny opis: (tylko po angielsku)

Lectures:

1) Cloud Computing & Google Cloud Platform – Generic Information

2) Google Compute Engine – managed service for Virtual Machines

3) Google Cloud Networking (concept of Virtual Private Cloud, network firewall, load balancing)

4) Identity and Access Management, Security services of Google Cloud Platform

5) Databases and storage services (Cloud Storage, Cloud SQL)

6) Databases and storage services (Datastore, Spanner, Memorystore)

7) Kubernetes - Fundamentals

8) Kubernetes – Advances Topics

9) Building cloud native apps based on 12-factor rules

10) Logging and Monitoring (Stackdriver, Prometheus, ElasticSearch)

11) Serverless Computing with Cloud Functions

12) Google App Engine – Platform as a Service

13) Big Data Services (Dataproc, BigTable, BigQuery, etc.)

14) Machine Learning Services (Tensorflow, CloudML, Kubeflow, Vi-sion/Translate/Video Intelligence API)

15) Data Services (Cloud Composer, Data Labeling, Tables, Data Catalog)

Laboratories:

During laboratories students transform knowledge from lectures into prac-tical, working application elements. For example, during the lab to Machine Learning will see how to train and test a simple machine learning model built with Tensorflow and use Vision API to label images.

Course Project:

Building cloud-native application and deploying it on Google Cloud Platform. Using GCP native mechanisms for Continuous Integration/Continuous Delivery and using Big Data or Machine Learning services to deliver appli-cation functionality (e.g. labeling pictures).

Literatura: (tylko po angielsku)

1. Compute Engine: https://cloud.google.com/compute/docs/

2. App Engine: https://cloud.google.com/appengine/docs/

3. Kubernetes Engine: https://cloud.google.com/kubernetes-engine/docs/

4. Cloud Functions: https://cloud.google.com/functions/docs/

5. Cloud Storage: https://cloud.google.com/storage/docs/

6. Cloud IAM: https://cloud.google.com/iam/docs/

7. Stackdriver logging: https://cloud.google.com/logging/docs/

8. Stackdriver Monitoring: https://cloud.google.com/monitoring/docs/

9. Cloud Spanner: https://cloud.google.com/spanner/docs/

10. Cloud SQL: https://cloud.google.com/sql/docs/mysql/

11. Firebase Realtime DB: https://firebase.google.com/docs/database/

12. Cloud Machine Learning: https://cloud.google.com/ml-engine/docs/

13. Big Query: https://cloud.google.com/bigquery/docs/

14. Big Table: https://cloud.google.com/bigtable/docs/

15. Virtual Private Cloud: https://cloud.google.com/vpc/

Metody i kryteria oceniania: (tylko po angielsku)

The final grade will be based on the written exam (50%), project (30%) and small tasks during the laboratory classes (20%). Delivering a working ap-plication as the project is necessary for obtaining a positive grade.

Points to grades mapping:

- 50 points and less: 2.0

- 51 – 60 points: 3.0

- 61 – 70 points: 3.5

- 71 – 80 points: 4.0

- 81 – 90 points: 4.5

- 91 points and more: 5.0.

Zajęcia w cyklu "rok akademicki 2019/2020 - sem. zimowy" (zakończony)

Okres: 2019-10-01 - 2020-02-21
Wybrany podział planu:


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Typ zajęć: Laboratorium, 30 godzin, 24 miejsc więcej informacji
Wykład, 30 godzin, 24 miejsc więcej informacji
Koordynatorzy: Rafał Biegacz
Prowadzący grup: Rafał Biegacz
Lista studentów: (nie masz dostępu)
Zaliczenie: Egzamin
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Politechnika Warszawska.