March 24, 2015 - December 3, 2014

A New Way to Debug Scala in Production: Takipi for Scala

March 24, 2015

After an inspiring Scala Days (the next one is in Amsterdam), it's great to be able to shine some light on technologies dedicated to improving the workday of Scala developers. We recently talked about eight hot technologies that perhaps you didn’t know were built in Scala, and in the spirit of that we’re happy to highlight Takipi, a company that's making life for commercial Scala apps better. Branching out from Java, Takipi now helps Scala developers understand when and why their code breaks in production. For more details, we asked Josh Dreyfuss, who recently joined the Takipi team, to take us through it all.  -Oliver White, Typesafe, Inc.


Welcome to the Typesafe family, ConductR!

March 12, 2015

It’s 2015, and deploying Reactive systems is no longer just a luxury enjoyed by early adopters like Twitter, Netflix, Amazon and Facebook. Reactive application development is becoming mainstream, leading to demands on Operations that are simply not met by yesterday’s software architectures and technologies.


Check out Text By the Bay!

March 11, 2015

In addition to all the amp and excitement around Scala Days San Francisco (next week!!) and Scala Days Amsterdam in June, we wanted to call attention to another exciting conference coming up soon, Text By the Bay. Below is a quick note from our good friend and partner, Alexy Khrabrov, who would like to share more information.


The 3 pains Operations feels when deploying and managing Reactive applications

Responsive, resilient, elastic and message-driven applications are not longer being deployed just by a handful of early adopters like Netflix, Twitter, Google and Facebook. In the previous article Why managing Reactive systems is keeping your Operations team up at night, we reviewed how Reactive application development becoming mainstream is leading to demands on Operations that are simply not met by yesterday’s software architectures and technologies. 

Enterprises actively migrating or considering evolving parts of their systems towards microservice-based applications need a convenient way to deploy and manage everything. What’s needed is a system that is allowed to fail, isolating the issue gracefully without disrupting the user experience. As a reminder, Martin Fowler’s blog post shows us the differences in approach between Monoliths and Microservices...


Play 2.4 - A sneak peek

March 8, 2015

The Play team has been hard at work on Play 2.4 for almost a year now.  With a release scheduled for Q2, we’re coming to the final stages, about to release the last milestone, and looking toward the RC phase of the project.  The headline feature ofPlay 2.4 is dependency injection support from the core.  This is part of a larger plan to eventually remove Play’s reliance on global state (the “current” application), allowing more flexible deployment and simpler testing of Play applications.


Eight hot technologies that were built in Scala


With Scala Days 2015 San Francisco just around the corner (and only 15% of tickets left), it has got me thinking quite a bit about how much the ecosystem has expanded since I first became involved with the conference in 2011. 

The rapidly-growing Scala community has evolved from what was largely a very academic and research-oriented crew, with some early champions like Twitter and Foursquare, to a language that’s become a standard for enterprises, start-ups and universities alike. 

But even as companies and individuals use Scala to build their own new ideas, they also utilize other excellent tools like Play Framework, Akka, Apache Spark and Kafka...which are not only some of the hottest tools and projects on the market right now, but also intentionally built in Scala (for many reasons…)


Why managing Reactive systems is keeping your Operations team up at night

While Reactive application development is off to a roaring start and becoming mainstream, this leads to demands on Operations that are simply not met by yesterday’s software architectures and technologies. The pressure facing enterprises to manage resilient, responsive systems is brutal, yet most existing technologies available today are not designed to deploy and manage Reactive systems running on clusters. It’s due to this fact that Operations face a higher risk of downtime by using inappropriate tools/practices at a time when being unavailable is more costly than ever. So why is this happening? Well, it's not 2005 anymore–and why that's a problem for Operations is explained here...


Typesafe Activator 1.3.0 released: Contains new sbt server and UI

February 25, 2015

Ten months ago we posted about architectural changes to Typesafe Activator. After a few a lot of yak shaves, side projects, and detours, we have Activator 1.3.0 based on sbt server, a new setup where multiple clients can share the same instance of sbt. sbt server is also available in ABI-stable protocol-stable form for other clients (IDEs, command line, desktop status icon, whatever you can think of) to try out.


How Spark beats MapReduce: Event Streaming, Iterative Algorithms and Elasticity

In my previous post Why Enterprises of different sizes are adopting ‘Fast Data’ with Apache Spark, I gave a quick introduction to how massive petabyte data sets proved to be unmanageable in a cost-effective way with traditional tools, which paved the way for Hadoop and NoSQL databases. Hadoop has traditionally been an environment for batch processing, while NoSQL databases provided some subset of record-oriented CRUD operations. More recently, the need to process event streams has become more important. My Typesafe colleague Jonas Bonér calls this “Fast Data”.



Why Enterprises of different sizes are adopting ‘Fast Data’ with Apache Spark

A couple of weeks ago, Typesafe launched the results of a survey in which over 2000 people were asked about the explosive adoption of Apache Spark. In the Slideshare presentation embedded above, you can see a sneak preview of some of the results of Apache Spark: Preparing for the Next Wave of Reactive Big Databut the full version has a lot more to offer. The Scala community is showing intense interest in Apache Spark as well (according to the report, 88% of Spark users are working in Scala, 44% in Java, 22% in Python). So as resident “Apache Spark guy”, I thought it would be nice to put the popularity of Apache Spark in context, looking at what led us here, how enterprises are reacting, and what the needs of the mid-market really are.


New Case Study: BrightTALK Increases Concurrency and Resiliency with Akka

December 19, 2014

Today, we're proud to share a case study with our customers at BrightTALK, a leading provider of webinars and videos for professionals and their communities. In this piece, Alistair Cairns (VP of Engineering) and Brett Bell (Software Developer) discuss BrightTALK's decision to move away from the company's legacy PHP codebase to the Typesafe Reactive Platform.


Eh, What’s Up Scaladoc?

December 16, 2014

(with thanks to Bugs Bunny).

If you are new to Scala, Scaladoc is one of the most useful resources you can use to navigate the unfamiliar waters. Scaladoc has a lot of functionality. Some of the functionality continues to be surprising to newcomers though, hence this article (and screencast).


Case Study: Nitro Moves Desktop Apps to the Cloud with Typesafe Reactive Platform

Our newest case study is with Nitro, a company whose software make it easy to create, edit, share, sign and collaborate with documents—online or offline. In our recent interview, Nitro's VP of Technology, Tihomir Bajic, outlines the importance of Play, Akka and Scala to the company’s product delivery evolution during their recent years of explosive growth. Back in 2011, Nitro had millions of users and a massive code base of C++ for desktop apps for document processing and workflows. Nitro’s desktop products were supported by .NET.



Spark Survey

December 3, 2014

Back in September, we ran a survey to gather people’s thoughts and upgrade plans around Java 8. We were surprised to find that among the 3,000 respondents, more than 17% are already using Apache Spark in production. Considering how Spark support by the major Hadoop vendors is only about a year old, this number took many by surprise.