As the business world continues to integrate AI and machine learning to better manage big data processes, one area that arguably has benefitted the most is business monitoring. From IT management to business intelligence, the last few years have seen a drastic shift in how companies are monitoring their data.
When it comes to data, let’s start with the obvious. Averages suck. As developers, we all know that percentiles are much more useful. Metrics like P90, P95, P99 give us a much better indication of how our software is performing. The challenge, historically, is how to track the underlying data and calculate the percentiles. Today I will show you how amazingly easy it is to aggregate and create SQL based percentile rollups with Postgresql and t-digest histograms!
Imagine going to work only to find that your inbox is flooded with customers telling you how happy they are with your software. People are in such a hurry to download your app, you need to scale your servers to meet the demand before the infrastructure crashes. Your phone rings: it’s a tech journalist trying to book an interview with you about your company's growth. This is the dream for every business owner and entrepreneur. But the reality is often in stark contrast to the scenario above.
We are all familiar with this scenario, you work on your training code, fix “all” of the bugs (the ones you know about), wait for a few iterations, see that batch size wasn’t wrong and nothing blows up, and then you happily go home. However, when you come back into the office the next day look at your loss and test accuracy you’re horrified to find that the experiment crashed on the first test cycle because you pointed your test set in the wrong folder 🙁
There is a great number of logging plugins for Kong, which might be enough for your needs. However, they have certain limitations: Most of them only work on HTTP/HTTPS traffic. They make sense in an API gateway scenario, with a single Kong cluster proxying traffic between consumers and services. Each log line will generally correspond to a request which is “independent” from the rest.
When visiting a new website, it is quite normal to get carried away by the bells and whistles of the fancy UI and UX and not be able to appreciate all the lower level, back-end code that runs tirelessly to ensure a smooth and fast website experience. This is because your front-end HTML code has a visually rich browser page interface as a platform to showcase its output. Whereas your back-end, server-side code usually only has a console at its disposal.
We know that test automation is expected to make processes faster and easier in software organizations and also to enhance the quality of the software significantly. However, in reality, test automation fails around 64% of the time to deliver according to the expectations as per Cigniti. Here are some of the main reasons why test automation fails for your web automation:
From now on, you can check code coverage and use the Test Reports add-on with your Flutter apps as well. Woo-hoo! 🎉
The Industry Transformation category at the Data Impact Awards has never been more timely. While the business world is mostly focused on digital transformation, Cloudera and our customers know that true, data-driven change is reshaping whole enterprises and entire industries.
