Creating IAM Roles in AWS
Amazon Web Services, the “Powered by AWS” logo, and AWS Lambda are trademarks of Amazon.com, Inc. or its affiliates in the United States and/or other countries.
Amazon Web Services, the “Powered by AWS” logo, and AWS Lambda are trademarks of Amazon.com, Inc. or its affiliates in the United States and/or other countries.
Talend Cloud is an Integration platform as a service (iPaaS) offering by Talend. It is a fully managed cloud option which has the capabilities of data integration, data stewardship, data preparation, API designer and Tester and Pipeline designer. These tools can be used for lightweight ETL and detecting the schema on the fly. One of the unique features of Talend Cloud is it provides both on premise and cloud execution environments.
We know that data is a key driver of success in today data-driven world. In fact, according to Forrester, data and insight-driven businesses are growing at an average of more than 30% annually. However, becoming a data driven organization is not easy. Companies often struggle with speed in accessing and analyzing their data, as well with ensuring delivery of trustworthy data that is free of critical errors.
Amazon Web Services, the “Powered by AWS” logo, and AWS Lambda are trademarks of Amazon.com, Inc. or its affiliates in the United States and/or other countries.
We are excited to announce a partnership establishment with Sauce Labs – a cloud-hosted, web, and mobile application automated testing platform company. This collaboration aims at delivering better automated cloud execution, allowing software development businesses to release high-quality products faster. “One of the challenges that software development teams often face is not having a user-friendly test automation tool, or insufficiency in testing environments.
A household name in global media analytics – let’s call them MTI – is using Unravel to support their data operations (DataOps) on Amazon EMR to establish and protect their internal service level agreements (SLAs) and get the most out of their Spark applications and pipelines. Amazon EMR was an easy choice for MTI as the platform to run all their analytics. To start with, getting up and running is simple. There is nothing to install, no configuration required etc.
In my last post I laid out our reasoning for moving from Heroku to Google Kubernetes Engine (GKE) and other GCP services. Now I'll describe the actual migration process in detail. This isn't designed as a how-to guide for migrating from Heroku to GKE—Google has their own excellent tutorial for that—but rather a description of some of the challenges of migrating real-world production applications and how we overcame them.
As API programs gain traction, we know many companies want to empower developers to quickly build and deliver their API products. To aid them in this effort, we recently announced the availability of new capabilities in Apigee, the enterprise API management platform of Google Cloud Platform (GCP), to help enterprise IT teams speed up their API development. With faster API development within GCP, you can innovate faster and create connected customer experiences, plus increase developer productivity.
The cloud native paradigm for application development has come to consist of microservices architecture, containerized services, orchestration, and distributed management. Many companies are already on this journey, with varying degrees of success. To be successful in developing cloud native applications, it’s important to craft and implement the right strategy. Let’s examine a number of important elements that must be part of a viable cloud native development strategy.
Until late last year, Rainforest ran most of our production applications on Heroku. Heroku was a terrific platform for Rainforest in many ways: it allowed us to scale and remain agile without hiring a large Ops team, and the overall developer experience is unparalleled. But in 2018 it became clear that we were beginning to outgrow Heroku.