Ml devops

How machine learning is reshaping the traditional software development lifecycle.

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22 June 2020
4 min read
Today, mass amounts of data come from a myriad of applications and microservices. DevOps engineers are often tasked with ensuring that data is collected, retained, and secured in a way that follows strict regulations. Focusing on data security, many companies rely on VMware for various internal cloud-computing...
20 March 2020
4 min read
There is no doubt that more needs to be said about how time series data analysis advances DevOps. Time series classification is a tertiary aspect of time series data itself. By harnessing performance benefits from the powerful capabilities of a machine learning deployment platform, multiple types of...
13 February 2020
5 min read
Time series data, the key data points that have an associated timestamp allowing indexing in time order, are in most cases INSERT-intensive, requiring specialized time series databases as opposed to traditional relational practice as seen in SQL. Prior to advancements in machine learning, much of the...
2 January 2020
3 min read
DevOps Engineers are delighted when they find a product or service that fits in with their already refined CI/CD processes. When we choose a new pipeline tool, engineers depend on a number of factors. Ease of use, repeatable processes, and a solid support model are key. Choosing a continuous integration...
16 November 2017
8 min read
When Google’s Gradient Ventures invested in us, they did so with an understanding that it is incredibly hard to deploy AI/ML infrastructure — and that every dev team is going to need to solve this problem. Our solution, the AI Layer, is the best-in-class architecture.As our co-founder, Kenny...