We’re happy to announce the release of AppSignal for Elixir 2.1.0. 🥳 In this version, we’ve made our error helpers more flexible than before. You could already send Elixir exceptions directly through AppSignal and now you can add extra metadata to errors when using send_error/2-4. Let’s go through all of the changes 😀
Google has been saying for a long time that its primary goal is to improve the Internet in terms of increasing the quality of websites and the content published on them. This fits in with typical business goals (not so widely announced), i.e. maximizing revenues generated by a search engine. The better quality of search results provided to users, the more clicks. And the quality of results will never be higher than the quality of the best pages and content available for a given query.
InfluxDB is great at capturing many kinds of metrics and allowing end users to aggregate those metrics to custom time groupings whether you’re watching IoT devices perform at 10-minute intervals, GitHub repositories issues close over weeks, or web performance metrics over seconds. Dashboards provide that information at a glance, at precisely the intervals you’ve determined. But what about the next level?
Recently, I presented at .conf20, Splunk’s annual user conference, on link analysis, where I promised more technical details on the topic in the coming weeks. To keep my promise, I’ve started a three-part series to show you how to use Splunk for link analysis.
In this handbook, we’ll explain the AWS Step Functions Input and Output manipulation. There’s plenty to talk about AWS Step Functions. There are numerous articles available online talking about AWS Step Functions ever since Step Functions were introduced in 2016. Most of these articles might make you think that Step Functions are actually an extension of the Lambda function, allowing you to combine several Lambda functions to call each other.
The shift to Observability Over the last six months, unified monitoring, log management, and event management vendors have reoriented their technology portfolios (often without any change to the underlying functionality) towards Observability. In so doing, a fair amount of confusion has been generated in the market.
Databases are everywhere these days, every application uses databases to store, organize and retrieve data. It has become more efficient than paper storage since it does not require more space and can also be easily accessed by multiple users at a time. There is an increase in demand for processing vast collections of data and this has become the most important reason for several companies to use databases.
