Async processing of long-running tasks in ASP.NET Core Written by Thomas Ardal, September 14, 2021 Sometimes, invoking an API endpoint needs to trigger a long-running task. Examples of this could be invoking an external and slow API or sending an email, which you don’t want the caller of your API to wait for. There are multiple ways of implementing this using a message broker, a fire and forget API request, or something completely third. In this post, I’ll show you how to implement async processing in ASP.NET Core, using a queue and the Background Worker feature. To understand how to process long-running tasks, let’s start by creating an example and making it sloooooow. Create a new ASP.NET Core application through Visual Studio, dotnet, or your preferred scaffolding engine. For this example, I have chosen the MVC template, but it could just as well be one of the other options. Next, in the HomeController.cs file, create a new method to simulate a call to a slow running task: For the demo, I’m waiting 10 seconds to simulate some work. The Task.Delay line would be replaced with some integration code in a real-life example. I have wrapped the code in information messages, which I can later inspect in Visual Studio or through the configured logger (maybe elmah.io?). Then, invoke the CallSlowApi method from the Index method: Let’s run the application and inspect the performance in Developer Tools: As expected, loading the frontpage takes just above 10 seconds (10 seconds for the Task.Delay and 30 milliseconds to load the page). Refactoring time! To process the message asynchronously, we’ll implement a background worker...
Today is assuredly the best day to start a . Indeed, people are turning to technology to track and improve their well-being. Naturally, anyone would want a reliable and trusted solution to manage their health. For instance, it is no secret that doctors are already taking advantage of mobile technologies in their practice. User bases grow, and so does demand. There is even some indication that data from patients’ wearables will increasingly be used in the analysis. And what about the mental health space? There probably isn’t a person who hasn’t seen a YouTube commercial for one of those apps. Anyway, in 2017 the market size was estimated at 2.4 billion dollars. Guess what? In 2025, it is in comparison. So, looking to get into the lucrative mHealth as they call it? Here are the cherry-picks among all the mobile health app advice for 2021. Setting correct goals Users are picky. They want all the features they can get, but do you have the time to deliver it all perfectly? Oftentimes, it just isn’t worth it to chase desires. On the other hand, what makes sense is to plan exactly what your app is. What problem does it solve at the core? What does it do best? What do the users need to expect from your app at the very least? This application you’re making – it’s made for people. Sometimes they can’t tell you what they want. Thus, it’s up to you to figure out what it is that they need. How do you do that? Incorporating user feedback and doing it early Healthcare apps are there to make our...
Better safe than sorry: Companies risk disastrous consequences if they try to save on security measures in their automation systems or to do without them entirely. In a worst-case scenario, companies are not only regretful following a cyberattack, but can also suffer serious losses – or even lose their competitive edge. As a central engineering framework, TIA Portal combines a number of functions that can minimize the risk of a cyberattack. I’d like to introduce you to a few of them. “That isn’t going to happen to me – I’d see if anything like that was happening!”– I’d bet that a lot of us are pretty confident we’d never fall victim to a cyberattack. After all, we’re far too clever for that, we recognize phishing emails immediately, and would never download malware. But are we really so clever? According to a report by the Federal Office for Information Security (BSI) on the state of IT security in Germany in 2021, one in every four Germans has been the victim of Internet crime. Such cyberattacks are much more lucrative when directed against companies rather than individuals and, sadly, criminals are enjoying more and more success in that area: A study by digital association Bitkom showed that nine out of ten companies (88%) were affected in 2020-21. Effectively combating cyber threats What makes it so easy for attackers is the constantly increasing pace of digitalization and the associated growth in networking between OT (Operational Technology) and IT (Information Technology). As a result, OT is increasingly becoming the focus for cyber criminal attackers, and must be protected with the same security measures...
Today, have gained the status of being all-pervasive across functions and domains. The mammoth wings of data and analytics are determining how we buy our toothpaste, how we choose dating partners, and how we lead our lives. Nearly 90% of all small, mid-size, and large organizations have adopted analytical capabilities over the last 5 years to stay relevant in a market where large volumes of data are recorded every day. They use it to formulate solutions to build analysis models, simulate scenarios, understand realities and predict future states. According to a recent report by LinkedIn here’re some of the fastest-growing in-demand jobs of the past year and the next few years to come. Hiring for the roles of Data Scientist, Data Science Specialist, Data Management Analyst, Statistical Modelling has gone up by 46% since 2019. While there has been a surge in job openings, there are also some common myths co-existing with them. Contrary to popular belief, you don’t need a programming background or advanced math skills to learn skills. This is so because most of the tools and techniques are easy to use and find ubiquitous application in all domains and professionals from vastly different industries like BFSI, Marketing, Agriculture, Healthcare, Genomics, etc. A good knowledge of statistics will need to be developed though. Also, Data Science and Business Analytics is based on the use of common human intelligence that can be applied to solve any and all industry problems. Hence, you don’t need Fourier series or advanced mathematical algorithms to build analytical models. Math learned till 10+2 level is good enough and can serve as a starting base for...
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