Tue.Jun 11, 2019

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Tool up your API integration testing with OpenAPI

TechBeacon Testing

APIs have become the adhesive that holds the modern web together, reflecting the changing nature of web apps.

Testing 63
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ACM Survey, Part 2: How your peers use production monitoring data to innovate faster

Dynatrace

Dynatrace news. Welcome back to the blog series in which we summarize the findings of our Autonomous Cloud Management Survey. In part 1 we examined the Dev-to-Ops ratios that organizations have for their most critical application projects. In this post, we’ll look at organizational silos, and how far organizations have come in breaking them down. To explore this issue, we asked participants the following question: Which of your teams have access to production monitoring data?

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2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence

Scalegrid

Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Or, considering adding a new database to your application and want to see which combinations are most popular? We found all the answers you need at the Percona Live event last month, and broke down the insights into the following free trends reports: Top Databa

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Supporting Disaster Recovery with Dynatrace at NYCM

Dynatrace

Dynatrace news. When disaster strikes, it is important to react fast and get live updates on the recovery progress of the business and mission-critical systems. Dynatrace not only makes it easy to monitor all critical systems (hosts, processes, services, applications, users, network, cloud, custom devices, …) but thanks to the metadata the Dynatrace OneAgent captures for each entity, you can organize, filter, get alerted and get an overview of your system based on data that is relevant to the di

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Beyond data and model parallelism for deep neural networks

The Morning Paper

Beyond data and model parallelism for deep neural networks Jia et al., SysML’2019. I’m guessing the authors of this paper were spared some of the XML excesses of the late nineties and early noughties, since they have no qualms putting SOAP at the core of their work! To me that means the “simple” object access protocol, but not here: We introduce SOAP, a more comprehensive search space of parallelization strategies for DNNs that includes strategies to parallelize a DNN in the Sa

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