As APIs become the de facto standard for building and connecting business-critical applications, it’s important for operations teams to gain visibility into the security attributes of your APIs in order to continuously monitor and maintain the health of your API programs.
Machine learning is a branch of Artificial Intelligence that makes it possible for systems to learn without being programmed. Applying this technology to real world Marketing is often misunderstood and is within your reach.
From its inception back in 2005 to today, Talend has always sought to be a different kind of data integration company – one rooted in open source to provide our customers with greater choice and flexibility and not afraid to change and embrace new innovations, such as multi-cloud and hybrid support and native integration with serverless cloud platforms.
Melbourne, 06 August 2019 - Yellowfin, a world-leading and innovative analytics vendor, has been named Leader by Enterprise Management Associates (EMA) in the research report ‘Innovation in the Use of Artificial Intelligence and Machine Learning for Business Intelligence’. EMA selected Yellowfin as an innovation leader as the analytics suite featured eight of the ten AI-enabled capabilities evaluated in the report and best aligned with today’s customer priorities and pain points.
Katalon Studio 6.3 is now available to download. Take a sneak peek of some new and exciting features! Download Katalon Studio 6.3 First, one of the most requested features by users: namely the dark theme, is now available. The decision to proceed with this new feature was due to the number of upvotes for this mode of display that triumphed all other proposed features (including applying machine learning to make coffee – seriously, no joke).
In the current microservices DevOps environment, there are tough new and evolving challenges for developers and teams to consider on top of the more traditional ones. From worsening versions of already common threats to new-generation evolving threats, new perspectives are required on securing microservices. These new perspectives may not be intuitive for many otherwise sophisticated DevOps and data teams.
Running real time data injection and multiple concurrent workloads on HBase clusters in production is always challenging. There are multiple factors that affect a cluster’s performance or health and dealing with them is not easy. Timely, up-to-date and detailed data is crucial to locating and fixing issues to maintain a cluster’s health and performance.
DevOps – a renowned software development practice that many companies adopt into their workflow – has been drawing a great deal of attention. More and more companies have adopted this practice, including large enterprises such as Netflix, Facebook, or Amazon. As a matter of fact, DevOps-related job has become one of the most promising career choices for IT professionals.
In the previous article of our last chapter of Data Integration Best Practices, we took a look at how to describe integrations in such a way that everybody – from developers to business users – understands the requirements correctly. We also discussed why you eventually might need some type of an integration layer to keep your integration projects under control. In this article, we continue reviewing some tips that revolve around preparing for and running an integration project.
Talend 7.1 brings in many new features, one such feature which needs a special discussion is containerization, which opens the doors to design and implement new Architectures namely Microservices. With a Maven plugin the Studio is now able to Build and Publish standard Jobs as Docker images into a Docker registry.
