Apr
21
2020
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Pulumi brings support for more languages to its infrastructure-as-code platform

Seattle-based Pulumi has quickly made a name for itself as a modern platform that lets developers specify their infrastructure through writing code in their preferred programming language — and not YAML. With the launch of Pulumi 2.0, those languages now include JavaScript, TypeScript, Go and .NET, in addition to its original support for Python. It’s also now extending its reach beyond its core infrastructure features to include deeper support for policy enforcement, testing and more.

As the company also today announced, it now has over 10,000 users and more than 100 paying customers. With that, it’s seeing a 10x increase in its year-over-year annual run rate, though without knowing the exact numbers, it’s obviously hard to know what exactly to make of that number. Current customers include the likes of Cockroach Labs, Mercedes-Benz and Tableau .

When the company first launched, its messaging was very much around containers and serverless. But as Pulumi founder and CEO Joe Duffy told me, today the company is often directly engaging with infrastructure teams that are building the platforms for the engineers in their respective companies.

As for Pulumi 2.0, Duffy says that “this is really taking the original Pulumi vision of infrastructure as code — using your favorite language — and augmenting it with what we’re calling superpowers.” That includes expanding the product’s overall capabilities from infrastructure provisioning to the adjacent problem spaces. That includes continuous delivery, but also policy-as-code. This extends the original Pulumi vision beyond just infrastructure but now also lets developers encapsulate their various infrastructure policies as code, as well.

Another area is testing. Because Pulumi allows developers to use “real” programming languages, they can also use the same testing techniques they are used to from the application development world to test the code they use to build their underlying infrastructure and catch mistakes before they go into production. And with all of that, developers can also use all of the usual tools they use to write code for defining the infrastructure that this code will then run on.

“The underlying philosophy is taking our heritage of using the best of what we know and love about programming languages — and really applying that to the entire spectrum of challenges people face when it comes to cloud infrastructure, from development to infrastructure teams to security engineers, really helping the entire organization be more productive working together,” said Duffy. “I think that’s the key: moving from infrastructure provisioning to something that works for the whole organization.”

Duffy also highlighted that many of the company’s larger enterprise users are relying on Pulumi to encode their own internal architectures as code and then roll them out across the company.

“We still embrace what makes each of the clouds special. AWS, Azure, Google Cloud and Kubernetes,” Duffy said. “We’re not trying to be a PaaS that abstracts over all. We’re just helping to be the consistent workflow across the entire team to help people adopt the modern approaches.”

Oct
30
2019
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Google launches TensorFlow Enterprise with long-term support and managed services

Google open-sourced its TensorFlow machine learning framework back in 2015 and it quickly became one of the most popular platforms of its kind. Enterprises that wanted to use it, however, had to either work with third parties or do it themselves. To help these companies — and capture some of this lucrative market itself — Google is launching TensorFlow Enterprise, which includes hands-on, enterprise-grade support and optimized managed services on Google Cloud.

One of the most important features of TensorFlow Enterprise is that it will offer long-term support. For some versions of the framework, Google will offer patches for up to three years. For what looks to be an additional fee, Google will also offer to companies that are building AI models engineering assistance from its Google Cloud and TensorFlow teams.

All of this, of course, is deeply integrated with Google’s own cloud services. “Because Google created and open-sourced TensorFlow, Google Cloud is uniquely positioned to offer support and insights directly from the TensorFlow team itself,” the company writes in today’s announcement. “Combined with our deep expertise in AI and machine learning, this makes TensorFlow Enterprise the best way to run TensorFlow.”

Google also includes Deep Learning VMs and Deep Learning Containers to make getting started with TensorFlow easier, and the company has optimized the enterprise version for Nvidia GPUs and Google’s own Cloud TPUs.

Today’s launch is yet another example of Google Cloud’s focus on enterprises, a move the company accelerated when it hired Thomas Kurian to run the Cloud businesses. After years of mostly ignoring the enterprise, the company is now clearly looking at what enterprises are struggling with and how it can adapt its products for them.

Feb
11
2019
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Google Docs gets an API for task automation

Google today announced the general availability of a new API for Google Docs that will allow developers to automate many of the tasks that users typically do manually in the company’s online office suite. The API has been in developer preview since last April’s Google Cloud Next 2018 and is now available to all developers.

As Google notes, the REST API was designed to help developers build workflow automation services for their users, build content management services and create documents in bulk. Using the API, developers can also set up processes that manipulate documents after the fact to update them, and the API also features the ability to insert, delete, move, merge and format text, insert inline images and work with lists, among other things.

The canonical use case here is invoicing, where you need to regularly create similar documents with ever-changing order numbers and line items based on information from third-party systems (or maybe even just a Google Sheet). Google also notes that the API’s import/export abilities allow you to use Docs for internal content management systems.

Some of the companies that built solutions based on the new API during the preview period include Zapier, Netflix, Mailchimp and Final Draft. Zapier integrated the Docs API into its own workflow automation tool to help its users create offer letters based on a template, for example, while Netflix used it to build an internal tool that helps its engineers gather data and automate its documentation workflow.

 

 

Feb
16
2017
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Percona Blog Poll Results: What Programming Languages Are You Using for Backend Development?

Programming Languages

Programming LanguagesIn this blog we’ll look at the results from Percona’s blog poll on what programming languages you’re using for backend development.

Late last year we started a poll on what backend programming languages are being used by the open source community. The three components of the backend – server, application, and database – are what makes a website or application work. Below are the results of Percona’s poll on backend programming languages in use by the community:

Note: There is a poll embedded within this post, please visit the site to participate in this post’s poll.

One of the best-known and earliest web service stacks is the LAMP stack, which spelled out refers to Linux, Apache, MySQL and PHP/Perl/Python. We can see that this early model is still popular when it comes to the backend.

PHP still remains a very common choice for a backend programming language, with Python moving up the list as well. Perl seems to be fading in popularity, despite being used a lot in the MySQL world.

Java is also showing signs of strength, demonstrating the strides MySQL is making in enterprise applications. We can also see JavaScript is increasingly getting used not only as a front-end programming language, but also as back-end language with the Node.JS framework.

Finally, Go is a language to look out for. Go is an open source programming language created by Google. It first appeared in 2009, and is already more popular than Perl or Ruby according to this poll.

Thanks to the community for participating in our poll. You can take our latest poll on what database engine are you using to store time series data here. 

Dec
21
2016
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Percona Blog Poll: What Programming Languages are You Using for Backend Development?

Programming Languages

Programming LanguagesTake Percona’s blog poll on what programming languages you’re using for backend development.

While customers and users focus and interact with applications and websites, these are really just the tip of the iceberg for the whole end-to-end system that allows applications to run. The backend is what makes a website or application work. The backend has three parts to it: server, application, and database. A backend operation can be a web application communicating with the server to make a change in a database stored on a server. Technologies like PHP, Ruby, Python, and others are the ones backend programmers use to make this communication work smoothly, allowing the customer to purchase his or her ticket with ease.

Backend programmers might not get a lot of credit, but they are the ones that design, maintain and repair the machinery that powers a system.

Please take a few seconds and answer the following poll on backend programming languages. Which are you using? Help the community learn what languages help solve critical database issues. Please select from one to six languages as they apply to your environment.

If you’re using other languages, or have specific issues, feel free to comment below. We’ll post a follow-up blog with the results!

Note: There is a poll embedded within this post, please visit the site to participate in this post’s poll.

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