Systems | Development | Analytics | API | Testing

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Metrics and Logs Are Out, Distributed Tracing Is In With Chinmay Gaikwad | Kongcast Episode 5

In this Kongcast Episode, Chinmay Gaikwad, tech evangelist at Epsagon, explains why metrics and logs aren’t sufficient for companies with a microservices architecture. Instead, Chinmay recommends leveraging distributed tracing for optimal observability.

Why Security Quality Matters - And What You Should Do About It

As more users opt to do their banking online, the cost of having an unresponsive, unreliable and feature-deficient financial application or website will have growing negative implications. In this presentation, Justin Dolly draws on experience from 20+ years as a CISO and CSO to discuss the current state of security testing. He then shares how Sauce Labs is working to make security testing more comprehensive and more efficient, to help financial services organizations deliver reliable and secure web and mobile apps, faster.

10 Things Testers Wish CIOs and CTOs Knew About Testing: Episode 4

In this new series from Sauce Labs, Marcus Merrell addresses ten things he wishes CIOs and CTOs understood about testing. In episode four, Marcus discusses how Selenium is not a complete test automation strategy, just a key component. Come along on this ten-episode journey to learn some best practices while Marcus dispels some myths about the testing space.

Testquality | Test Management Github Integration Overview

TestQuality helps you build better software with fully integrated and easy to use Test Management for high-performance teams. The fastest way to build, run, and manage test cases, plans, runs, and cycles. Easily understand the quality and performance of your tests and with powerful test analytics.

Introduction to TF Serving

Machine learning (ML) model serving refers to the series of steps that allow you to create a service out of a trained model that a system can then ping to receive a relevant prediction output for an end user. These steps typically involve required pre-processing of the input, a prediction request to the model, and relevant post-processing of the model output to apply business logic.

How to migrate a data warehouse to BigQuery

Has your data team outgrown its on-premise traditional data warehouse? Are you looking for a system to store data that is secure, scalable, and cost effective? In this episode of Architecting with Google Cloud, Priyanka Vergadia speaks with Gary Morreale, the Director of Data Services from Independence Blue Cross about how his team migrated from Terradata to Bigquery on Google Cloud Platform. Listen as Gary Morreale discusses his team’s giant undertaking on migrating dataware to BigQuery.