Nowadays many web applications are Single Page Apps that connect to an API via HTTP (for example REST or GraphQL). When you develop such an application, you do not only have to run a local development server, but also an API where it connects to. The API could be running on a dev cluster, but you can also run it locally on a different port for example.

A big advantage of connecting to a real API, is that you probably create less bugs. On the other hand, it is sometimes hard to test or setup up all possible scenarios. How do you for example test, in a controlled way, that your API responds with an internal server error and how the client handles this? In this blog I explain how to do this.

When using React Native, lists are created using the FlatList component. A FlatList is constructed using one or more repeatable list items, one item per row. In this blog I’ll demonstrate how TypeScript can help to create FlatLists with generic list items.

This is a technique where we can reduce boilerplate, but still have readable and customisable FlatLists.

Let’s dive right into the basics of a FlatList by creating a list of StarWars characters.

Why

Consumer lag is the most important metric to monitor when working with event streams. However, it is not available as a default metric in Azure Insights. Want to have this metric available as part of your monitoring solution? You can set it up with some custom code. In this blog we show you how.

Over the past years I’ve tried working with lambda functions on and off a couple of times. Each time I got stuck, either clicking in AWS UIs or writing YAML files.

Netlify changes all that by making lambdas easy to use. Below I’ll describe the basics of deploying a function, and I’ll show how the development tools support local development.

The most basic hello world example I could come up with can be found in this repo, tagged basic-javascript-lambda. There’s a simple index.html file (a left over from earlier experiments), and a hallo.js file in src/functions. That’s almost al there is to it, but it needs one specific bit of configuration in a file named netlify.toml, located in the root of the repository.

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While browsing the Netlify configuration site for my account (in a more or less panicky attempt to find some config item I’d lost track of), I stumbled on an option named split testing. I know this concept as A/B testing, where you try out different versions or options of a site and check analytics to find out which version yields the highest revenue. Netlify tags this option as beta, but at the time of writing I’m pretty happy with its performance. Below is a short introduction on how to use the split testing feature.

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Remember when we used to have a production, acceptance testing, integration and development version of a site? And that we struggled to get an extra environment from IT just so our customers could test our work?

Those days are over. Below I’ll show how to set up deploys for every branch. Or every commit. And how to have all of those versions available at the same time. The enabling technology is Netlify.

This post will show how to deploy a site on Netlify, based on a GitHub repository. And the killer feature: each single commit can be deployed to a unique URL with no extra effort at all. This facilitates fast and easy feedback from our clients on the products we build.

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A data-platform is nothing more than a normal (cloud) platform with some additional functionality on top to make it specific to the requirements of the data domain. Instead of the applications that run on a “normal” platform like (web)services and front-ends it runs ELTs/ETLs and data applications. 

Social media has been blamed for locking people in a bubble, only showing them news that is in line with their beliefs. This divides society into different groups that have almost nothing in common. People read what they think they want to read, never seeing a different opinion. At the same time governments and influencers have started to call for filtering. Facebook would have to filter out lies and fake news, so we all see the truth only. The problem with the filter approach is that it will cause opinions to drift toward some bottom line truisms we can all agree on. If we start fining social media for violations, the companies will get more and more conservative, and we’ll end up in a boring world. Like having a perpetually overcast sky and an eternal drizzle. Grey goo everywhere.

This is not what we need. What we need is to be confronted with opinions that differ from what we think is right. So we (i.e. Albert Brand, Arjan Molenaar and myself) started a one-day research project at Xebia, inspired by a feature of my favorite Dutch newspaper, NRC. The feature is called Twistgesprek. The format is that two people discuss a statement during the week. Their conversation is summarized and published in the Saturday paper as a back-and-forth of messages. Quite often I start with a strong opinion about the subject being discussed, but end up with a more thorough understanding of its nuances because of the discussion. Having your convictions challenged and modified is a wonderful gift.
So, the idea was to show people ideas that directly contradict each other.
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AWS (Amazon Web Services) offers a pretty neat NoSQL database called DynamoDB. It is fast and it can scale, what more can you wish for? The thing is, as a developer you are still responsible for designing your tables in such a way, that you actually make appropriate use of the benefits DynamoDB has to offer. If you simply apply your knowledge gained using other databases, you might end up wasting money and performance.

Many organisations have a new ambition to become a data-driven organisation. In essence, this means the organisation wants to make better business decisions based on insights provided by data [4]. Data itself is not able to advise a business for better decision-making. Therefore these organisations introduce a new capability: Data & Analytics. 
This blog elaborates on how adopting DevOps principles can enhance business value creation for the world of Data & Analytics.