Arguably the most powerful feature of Apache Flink is its ability to do stateful computations on a boundless stream of data. Apache Flink is the core of Eventador’s Fully Managed Apache Flink stack. That said, to understand the value of Apache Flink, it’s still important to know the difference between a checkpoint and a savepoint. […]
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While Twitter and WordCount are probably two of the most common ways to get started with streaming data, there’s good reason (for Twitter at least) – it’s a fun way to work on actual real-time, unbounded streams of interesting data. In this post, I’m going to explore some techniques to normalize, window, and introspect the […]
When we started Eventador.io in 2016 we needed a simple data source to help us build the platform on. We needed something that exemplified streaming data, something massively dynamic, and something with a lot of data. Tweets were played out, we wanted something better.
Every Kafka deployment on Eventador has an associated access control list (ACL). The ACL defines what IP addresses are whitelisted and allowed access to produce and consume to and from your deployment. In fact, there are no entries at deploy time, thus access is completely denied. In order to use our service you must first […]
Getting connected and producing (publishing) and consuming (subscribing) messages is relatively easy in Apache Kafka. In this post we will go over connecting, producing a simple message, and consuming that message via one of a couple native python clients. Most languages are similar and there are a host of native drivers to choose from.
With the release of Eventador 0.5 we are introducing new plans with one-click provisioning. This allows you to deliver your projects in a more timely basis, save costs on valuable resources, leverage the cloud more effectively, get worry free 24×7 support, and have best in class data pipeline infrastructure simply by using Eventador.io. I thought […]