My session from Tuga IT 2017 on the Azure Container Service

May 24, 2017Download as PPTX, PDF0 likes491 views

This document summarizes the TUGA IT 2017 conference in Lisbon, Portugal. It thanks sponsors and lists participating communities. It then provides information on Docker and containers, including how they simplify app development and deployment by allowing code to run anywhere. Several demos are described, including connecting Office 365 groups from a container and using Azure Container Service. The document concludes by soliciting feedback and providing contact information for the presenter.

THANK YOU TO OUR SPONSORS
PLATINUM
GOLD SILVER

Email : rick.vanrousselt@outlook.com
rickvanrousselt #tugait

My session from Tuga IT 2017 on the Azure Container Service

- Ligthweight, open secure
platform
- Simplify building, shipping,
running apps
- Shipping container system
for code
docker and containers

Virtual Machines
• EachGuestOSneeds:
• CPU
• RAM
• Licensing
• Maintenance

• Moreroomforapps
• Lessermaintenance
• Licensing
Containers

• Blueprint or definition of a container (readonly)
• Needed by docker engine to create a running instance of
a container
• Can consist out of multiple layers
Code Node.js UbuntuImage

V1 V2 V3
Why use containers
Eliminate app conflicts

DEV TEST PROD
Why use containers
Easy app shipping

It’s just easy for us developers
• When joining an ongoing project no need to do a long setup
for a developer environment
• No need for heavy virtual machines
• Development environment is almost the same as production
Why use containers

The SharePoint Context
Why use containers

Connecting to Office 365
groups from a container
Demo

- Optimisedforhostingcontainers
- Easytomanagecontainers atvery
largescales
- Docker swarmorDC/OSor
kubernetes included
- Opensource
What is the Azure Container Service

• Largescale
• Proveninproduction
environments
• Complex
• Nativefromdocker
• Standarddocker
interface
DC/OS vs docker Swarm
• FromGoogle
• Different API

Overview of the Azure
Container Service
Demo

Twitter streams &
Cognitive Services
Demo

- Windowscontainers
- VS,VSTSandVSCodeintegrationand
deploymenttoAzureContainer
Service
Roadmap

If you have any more questions
Email:rick.vanrousselt@outlook.com
Twitter:@rickvanrousselt
GitHub:RickVanRousselt

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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

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Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev

If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic? Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search. Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval. GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.

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