As an Azure developer, you will surely come across the challenge of choosing the right Azure services for data management for your applications. A large selection of services is both a blessing and a curse at the same time. That is why it is crucial to familiarize yourself with Azure's possibilities in the area of data and information management. The purpose of this session is to sprint through the PaaS data services available in Microsoft's public cloud and clearly state when to choose what for your applications.
On this session we want to show how to quickly implement a real-time air quality monitoring solution leveraging Azure IoT Hub or Azure IoT Central services. The air quality monitoring device can measure various quantities temperature, humidity, CO2 and VOCs. We will focus on detecting levels of PM10 and PM2.5 cause they are the valuable indicators of air quality in Poland.The given IoT devices an sensors will communicate to IoT Hub for device-to-cloud and cloud-to-device messaging. Azure Stream Analytics will later process and transform the air quality stream. Power BI will also enable us to build interactive visualizations against the stream, which we could later use in a form of a dashboard on mobile or stationary devices. Cosmos DB will be employed to store the IoT JSON data.This can serve as a perfect base for ML and predicting air pollution in the future.This solution can be implemented based on different devices like Arduino or Azure Sphere.
Edge Computing is gaining incredible hype and traction all over IoT community. Day by day we can see corporations and startups dive in this movement on both hardware and software level. Join me in the journey across the Cloud and beyond to the Edge. We will be climbing the peaks of real use cases to see the story behind all the buzzwords and fluff.Let’s analyze this based on real life case studies and demos of Edge Computing in practice.
Many of us are migrating to the cloud, however this transition will take time. So how do we manage and monitor our on-premises services and APIs during this migration? And what if we can never move them to the cloud, either due to technical, procedural or security reasons? Maybe we even want to have a multi-cloud strategy, bringing together the best from all different providers. How can we ensure they are still brought under governance, in a secure manner, and adhering to the policies we want?This is where Azure API Management comes in, allowing us to create a vibrant API ecosystem, not matter where our services live. In this session we will dive into the options to manage our APIs in Azure, on-premises in a hybrid environment, on the edge with our devices, or at any other provider in a multi-cloud scenario, all with one seamless experience. Expect a deep-dive into Azure Arc combined with API Management, with best-practices, demos and lessons learned from the field.
Azure Arc is a solution that simplifies management across different hybrid clouds or multi-clouds. Azure Arc extends Azure management and security beyond the walls of Azure to other cloud platforms or on-premises environments enabling you to make use of Azure services to manage infrastructure at these environments. In this session, you will be introduced to Azure Arc, why should you use it and how to make use of it in different scenarios.
Implementing CI/CD on a project can be frustrating, especially if it takes ages to requisition a new test environment.What if test environments were ephemeral, running on an agent or in AKS, provisioned on the fly and torn down after they are no longer needed?
Terraform is an amazing toolset for automating infrastructure in the public and private cloud. This course will teach you the fundamentals of Terraform to deploy infrastructure in a consistent, repeatable manner across multiple services.Systems Administrators and DevOp Engineers have always been charged to do more with less. Defining infrastructure in code and automating its deployment helps improve operational efficiency and lower administrative overhead. In this session, you’ll learn foundational knowledge of Hashicorp’s Terraform software, a toolset for infrastructure automation. First, you’ll discover how open source tools, such as Terraform can be leveraged to implement Infrastructure as Code (IaC). Finally, you’ll learn how to automate your infrastructure deployments in the Cloud with Terraform and Azure Pipelines.
Come learn what i did to automate process of Azure Data Factory Pipeline creation and make the entire process faster more efficient and reusable.
Have you ever need to run the same tests for different environments, version of tools or to do compatibility check? If yes, then this presentation will show you practical ways of how to do that with Azure DevOps, if not then it will explain why those tests are important and how your systems can benefit from that. It will show practical examples based eg. on the flow used in Marten framework (https://martendb.io/).
Manage Azure environment with Ansible. Overview of the solution with introduction for beginners, then practical use-cases - how to create small project 'as a code' and deploy with one Ansible command. Tips and Tricks for DevOps.
With the release of Azure Sentinel, Microsoft has shifted some features from Azure Security Center to their new threat hunting and SIEM/SOAR solution. But how do all the security tools Microsoft offers nowadays complement each other? How can you find a way through this security jungle? And how do you make sure to have the right tools in place when it comes to protecting your IT environments and hunting threats?Join cloud security expert, Microsoft MVP, and NinjaCat Tom Janetscheck for this demo-rich session to get all these questions answered and to learn how to easily and efficiently find out if something bad is going on in your environments.
In real world business things don't always go (or rather, nearly never go) as described in the service documentation. They are confronted with a specific landscape of existing solutions which includes both technical limitations and business expectations. I want to show a few examples I met and needed to solve in and around of AAD B2C. The session will have its focus revolving around subjects of moving users across tenants (while splitting or merging), dealing with third party identity providers like Facebook or Apple ID and solving issues popping up with other third party services integrated in the system and dependent on AAD B2C. All from a perspective of long-established, multi-brand, corporate organization.
The Cloud Adoption Framework is the One Microsoft approach to cloud adoption in Azure, consolidating and sharing best practices from Microsoft employees, partners, and customers. The framework gives customers a set of tools, guidance, and narratives that help shape technology, business, and people strategies for driving desired business outcomes during their adoption effort. During this presentation we will discuss how to deploy your migration "landing zone". We will focus on recommended best practices to enhance network and workloads security as well as configuration of identity and access management in your cloud environment.
In this session you will learn what Azure Policy is and how to use it in a right way to protect your company and their resources.
During the session I will tell you how to secure data in Azure. Where mistakes are often made. Some services you need to pay more attention to.
The SignalR real-time framework has been there for ages, but how do you connect to services as volatile like Azure Functions? In my session, I will show you how to create a SignalR service, send messages to the SignalR service and handle events on a connected SPA application.
W FinAi jakoś w styczniu 2019 zdecydowaliśmy, że przejdziemy na k8s. Powód prosty - CTO powiedział, że za drogo. I UDAŁO się nam to zrobić. (choć FinAi jakiś czas temu przeszedł przeobrażenie). W czasie tych 50 minut postaram się opowiedzieć dlaczego migracja na k8s jeśli masz:a) nowoczesny stack, (.net core 2.2)b) popisane wszystko w CI/CDc) działający system na produkcji d) mikroserviceswcale nie jest prosta - i nie zajmuje mało czasu i trzeba wziąć pod uwagę zaskakująco dużo czynników (z których postawienie klastra jest najmniejszym problemem). Zwłaszcza jak w tym samym czasie musisz balansować z dowożeniem feature'ów biznesowych.
To be in Azure China or not to be in Azure China. Azure China Myths and Facts, how to use it, alternatives and how to build network infrastructure for your company in China.
Azure Functions is a key part of Microsoft serverless offering. At its core, it is a compute service, but its real power lies in integration capabilities. A lot has been said and written on how to use build in triggers and bindings to connect with databases, queues, web requests, and third-party APIs. There is however one aspect of Azure Functions which has been neglected - extensibility. This talk will walk you through Azure Functions extensibility with practical examples. It will give you the tools to push its integration capabilities further and get even more from Azure Functions.
Azure Logic Apps are cloud integration service that enable us to build and deliver enterprise integration solutions in with ease. In this session I will show you what are the most important tips and tricks for production logic apps, including ARM template generation, CI/CD, security and best practices.
You probably heard about continuous integration and continuous deployment. DevOps world would not be the same without various ways to automate builds, tests and deployments. However, any tool will not suffice if you just can't automate it and version by yourself. During this session you'll see how you scan script CI/CD pipelines using YAML in Azure DevOps.
Machine learning has become a vital part in many aspects of our daily life and is becoming more and more important. However, the performance of many machine learning methods is very sensitive to a plethora of design decisions. As a result, building well performing machine learning applications requires highly specialized data scientists and domain experts. It turns out that machine learning, a field dedicated to building systems that automatically learn from data, depends heavily on human experts. Isn’t that ironic …Come and see how Azure Machine Learning Service reduce the demand for data scientists by enabling domain experts to automatically build machine learning applications without expert programming skills and extensive knowledge of machine learning algorithms.
XXI wiek zwyczajne hurtownie danych, rozwiązania Business Intelligence nie spełniają swoich oczekiwań. elastyczność rozwiązania i różnorodność źródeł w tym danych z obszaru Big Data i IoT powodują, iż biznes ma zupełnie inne wymagania do analityki, zarówno tej klasycznej, jak i zaawansowanej wykorzystującej chociażby elementy sztucznej inteligencji. Odpowiedzią jest Azure Synapse Analytics.
70 billions... this is the number of devices which will be connected to the cloud by the end of 2025. Big number of device equals big amount of data and data is a holy grail of nowadays business. Knowing how to extract important information from the data which is already there is a key to your company success. This session will show you how to prepare cloud side infrastructure to connect your fleet of devices in a secure manner and how to start using AI in the easiest way to reach you business goals.