Data is the Hard Part Working with Microservices

by Jan Stenberg on  Aug 28, 2016 2

One of the hardest problem when creating and developing microservices for an enterprise is their data. Analysing the business domain using Domain-Driven Design (DDD) and reason about what your data represents will help in achieving a microservices architecture, Christian Posta claims in one of a series of blog posts about microservices implementations.

Q&A on Akka.NET 1.1 with Aaron Stannard

by Pierre-Luc Maheu on  Jul 21, 2016

Akka.NET 1.1 was recently released, bringing new features and performance improvements. InfoQ reached out to Aaron Stannard, maintainer of, to learn more about Akka.Streams and Akka.Cluster. Stannard also explains how the roadmap is planned with regards to the JVM implementation of Akka.

Five Ways to Not Mess Up Microservices in Production

by Mark Little on  Jun 19, 2016

Alex Zhitnitsky of Takipi has written about five ways to try to improve the chances of successful deployed of microservices into production. As we will see, they share many similarities with other independent efforts, perhaps leading us to agreement on top areas of concern, if not ways of solving these problems.

Combine SQL Server with Hadoop Using PolyBase

by Jonathan Allen on  Jun 02, 2016 2

With the recently released SQL Server 2016, you can now use SQL queries against Hadoop and Azure blob storage. Not only do you no longer need to write map/reduce operations, you can also join relational and non-relational data with a single query.

DevOps Days Kiel Day 1

by Manuel Pais on  May 15, 2016

Summary of DevOps Days Kiel day 1 talks.

Elephant in the Cloud - Hadoop as a Service

by Srini Penchikala on  May 02, 2016 2

Hadoop and other big data technologies revolutionized the way organizations run data analytics but the organizations are still facing challenges with operating costs of using these technologies for on-premise data processing. Ashish Thusoo recently spoke at Enterprise Data World Conference about Hadoop as a service offering that helps organizations bridge the gaps with these capabilities.

Google Cloud Machine Learning and Tensor Flow Alpha Release

by Dylan Raithel on  Apr 18, 2016

Late last month Google released an alpha version of their TensorFlow (TF) integrated cloud machine learning service as a response to a growing need to make their Tensor Flow library to run at scale on the Google Cloud Platform (GCP). Google describes several new feature sets around making TF usage scale by integrating several pieces of the GCP like Dataproc, a managed Hadoop and Spark service.

Apache Storm Reaches 1.0, Brings Improved Performance, Many New Features

by Sergio De Simone on  Apr 14, 2016

Version 1.0 is "a major milestone in the evolution of Apache Storm", writes Apache Software Foundation VP for Apache Storm P. Taylor Goetz, and it includes many new features and improvements. In particular, Goetz claims a 3x–16x boost in performance.

GitHub’s DGit Improves Reliability, Performance, and Availability

by Sergio De Simone on  Apr 07, 2016 1

GitHub has been quietly rolling out DGit, short for “distributed Git”, a new distributed storage system built on top of Git with the aim of improving reliability, availability, and performance of using GitHub.

LFE Brings Lisp to the Erlang Virtual Machine

by Sergio De Simone on  Apr 05, 2016

After 8 years of development, Lisp Flavoured Erlang (LFE) has reached version 1.0, bringing stable support for Lisp programming on the Erlang virtual machine (BEAM). LFE was created by Robert Virding, one of the initial developers of Erlang. InfoQ has spoken with Duncan McGreggor, current maintainer of LFE.

Apache Flink 1.0.0 is Released

by Rags Srinivas on  Mar 24, 2016

InfoQ's Rags Srinivas caught up with Stephan Ewen, a project committer for Apache Flink about the 1.0.0 Release and the roadmap

Anti-Patterns Working with Microservices

by Jan Stenberg on  Mar 15, 2016 4

The main problem with monolithic applications is that they are hard to scale, in terms of the application, but more importantly, in terms of the team. The main reason for a switch to microservices should be about teams, Tammer Saleh claimed at the recent QCon London conference when describing common microservices anti-patterns and solutions he has encountered.

Microservices for a Streaming World

by Jan Stenberg on  Mar 14, 2016

Embrace decentralization, build service-based systems and attack the problems that come with distributed state using stream processing tools, Ben Stopford urged in his presentation at the recent QCon London conference.

Real-World Consistency Explained: Uwe Friedrichsen Discusses His Favourite Academic Papers

by Daniel Bryant on  Mar 13, 2016 2

At the microXchg 2016 conference, held in Berlin, Germany, Uwe Friedrichsen presented a deep-dive into “real-world consistency explained”. Friedrichsen referenced multiple academic papers and discussed topics such as ACID vs BASE, his belief that many developers may not fully understand consistency guarantees with a typical SQL database, and how consistency affects microservice systems.

Moving from Transactions to Streams to Gain Consistency

by Jan Stenberg on  Mar 13, 2016

With many databases in a system they are rarely independent from each other, instead pieces of the same data are stored in many of them. Using transactions to keep everything in sync is a fragile solution. Working with a stream of changes in the order they are created is a much simpler and more resilient solution, Martin Kleppmann stated in his presentation at the recent QCon London conference.

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