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Using a Twitter example, Pivotal data scientist, Chris Rawles shares how to build a machine learning app on Pivotal Cloud Foundry that scales to nearly 15 times the average total number of tweets per second from all of Twitter. Video, setup details and code on github are included.
2016 was quite the year for technology. From the inside, it feels like we’ve collectively figured out how to get the boiler going, and for the past year have been fueling the fire and raising the pressure—picking up steam along the way and heading straight toward the golden age of software. This is a logical progression, as the substrate we use to build software now has actual substance, letting us focus on the real value here: the shower of exceptional user experiences that are pouring out of the cloud. This post takes a look at some of the most transformative innovations, and how they are taking off.
Pivotal Cloud Foundry recently launched on Google’s cloud. We thought it would be fun to go behind the scenes, and discuss the engineering collaboration. To this end, Google produced a few short videos starring engineers from both companies. Those videos are included here
We’ve brought together some of the smartest minds to look ahead at what 2017 holds for software itself, as well as some of the industries it’s affecting. Among these voices are Pivotal employees, Pivotal customers, and a few guest appearances from other leading technologists. Hopefully these insights can help you and your team get ahead on what’s to come, and build software that’s better, faster, safer, and more valuable than ever before.
In this episode, we dig into a recent survey by the Cloud Foundry Foundation on developer skills gaps, and how IT departments needs to rethink their approach to training and hiring. To do so, we invited Abby Kearns and James Governor. Abby is the Executive Director of the Cloud Foundry Foundation who did the survey. James is one of the founders of the analyst firm RedMonk.
Modern application architectures require a new approach to data. Modern apps need databases that get deployed through automation, prioritize availability and fault tolerance, and deliver low-latency performance. To solve this, Pivotal customers asked for integration between Pivotal Cloud Foundry and DataStax Enterprise (DSE), so we partnered together earlier this year. In the summary from DataStax, learn about the latest ways that Pivotal customers can be just like the cloud-natives.
In this episode of Pivotal Insights, host Jeff Kelly speaks with Pivotal’s Ivan Novick and Jag Mirani about the new GemFire-Greenplum Connector that supports use cases that require both high-performance transactions (fast data) and big data analytics such as fraud detection, risk management and customer recommendations.
Pivotal GemFire 9.0 became generally available last week, marking the culmination of over a year’s worth of development. The release includes a new feature, called the GemFire-Greenplum Connector, that enables users to more easily tackle use cases that require a blend of analytical and transactional processing, such as fraud detection.
Pivotal Cloud Foundry 1.9, demonstrates a new level of platform scale, expands multi-cloud support by adding Google Cloud Platform and Microsoft Azure as supported clouds, introduces a new PCF App Autoscaler, expands Metrics & Logs to be stored for 2 weeks--up from 24 hours, brings us Tasks for one-off commands and scripts in context with the app, delivers a slew of security improvements, and native integration of Spring Boot Actuator in Apps Manager.
One tactic Pivotal Cloud Foundry customers use to make their apps perform better and scale more easily, is to use Redis. For those interested in highly available Redis, we recommend considering Redis Labs Enterprise Cluster (RLEC). In this post, we talk to Leena Joshi, Redis Labs VP of product marketing, to learn more about Redis and their service.