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How to Use Bugfender on Flutter

Flutter is a user interface toolkit from Google which is primarily used to develop mobile applications but can also be deployed to create web and desktop apps. With Flutter, we can develop applications for both IOS and Android using the same source code. This dovetails neatly with Bugfender, our remote logging service that allows users to collect logs for everything in the application.

AWS Data Pipeline Best Practices

Knowing best practices for Amazon Web Services (AWS) data pipelines is essential for modern companies handling large datasets and requiring secure ETL (Extract, Transform, Load) processes. In this article, we discuss AWS data pipeline best practices to ensure top performance and streamlined processes — without complications that can impede the execution of data transfer.

Extending Connectivity to Cloud Native and VM-based Applications

We all know that what customers see in the market is, in fact, only a small percent of the shifts happening within our organizations. Recently, Time Magazine stated that “Every Company is a Tech Company… The Disruption is Just Beginning.” We’re seeing it in the way we wait in lines, find places to stay when traveling and work from anywhere. The disruption is distribution, and it impacts how we live and build applications.

Community Creations: Bitrise Open Source & the API - Introducing the Bitrise Wall mobile app

Being able to extend the functionality that Bitrise provides, by writing your own Apps that exploit the openness of the API is an added value feature of Bitrise. And, good use of this possibility has already been made by existing Bitrise users. A case in point is Bitrise Wall, created by Jas Manigundan. This is an app for both iOS and Android that allows you to monitor the activity of your builds and even download the latest app version directly from your mobile phone.

Build/Buy in MLOPs for R&D Does "off-the-shelf" exist yet?

What kind of tools and infrastructure does a company need in order to build, train, validate and maintain data-based models as part of products? The straight answer is - “it depends.” The longer one is: “MLOps.” It is far too early to determine the “best” patterns and workflows for Data-Science, Machine- and Deep-Learning products. Yet, there are numerous examples of successful deployments from businesses both big and small.

Comprehending ClearML and MLOps - Enabling the New A-Z (ODSC East '21)

ClearML is an industry leading MLOps suite, fully open source and free in the best sense. Designed to ease the start, running and management of experiments and orchestration for every day practitioners, we will also see how it provides a clear path to deployment. Starting with a high level overview of the parts built into ClearML, we will then journey into what is and also, importantly, what is not part of ClearML's mandate. Along the way we will demonstrate how-to integrate into your PyTorch code, as well as the capabilities of reporting and possible workflows that could be made easier by pipeline usage.