Systems | Development | Analytics | API | Testing

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What's Your Streaming-Data Strategy?

Are you ready to harvest the massive real-time data that your organization generates? You need to master streaming data to  gain an edge in business, in every industry. But, most businesses still rely on batch and incremental processing. If that’s you, don’t despair. Join this session to understand key concepts, common technologies and best practices you need to succeed with streaming  data. You will  also learn about the Hitachi Vantara streaming data stack and how we can help you meet your goals.

Deliver Analytics-Ready Data to the Cloud With Snowflake and Hitachi Vantara

One of the toughest challenges for data professionals today is migrating data from on-premises environments to the cloud. Many companies still lack the tools and infrastructure to ingest and process complex datasets to achieve critical business outcomes. Tune in for a joint-session with Snowflake and Hitachi Vantara as we discuss best practices to address common edge-to-multicloud issues and how our joint offering can dramatically simplify data preparation, migration and analytics tasks to help deliver analytics-ready data in the cloud.

API Load Testing Mistake #2: Not Calibrating Virtual Users to Real Users - @SmartBear Talks

A huge part of your strategic plan for load tests built into your app development business processes is understanding and ensuring that the user profiles or the actions that your simulated users take in any testing environment accurately depict what happens in a real-world use case. That's why you need to be very careful with setting up virtual users in your load tests. We will investigate possible issues with Damion White, software testing consultant from WiseClouds, in this video.

Make Your Keyboard Great Again! - User Story

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 🙁

Tracing With Zipkin in Kong 2.1.0

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.

Node.js Logging: A How-to Guide

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.

10 Reasons Why Test Automation Fails

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: