Honeycomb is a tool for observing and correlating events in distributed systems. It provides a different approach from existing tools like Zipkin in that it moves away from the single-request-tracing model to a more free-form model of collecting and querying data across layers and dimensions.
Yahoo! has made available Pulsar, their publish-subscribe messaging platform used internally in production by several services.
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.
Akka.NET 1.1 was recently released, bringing new features and performance improvements. InfoQ reached out to Aaron Stannard, maintainer of Akka.net, 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.
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.
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.
Summary of DevOps Days Kiel day 1 talks.
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.
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.
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 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.
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.
InfoQ's Rags Srinivas caught up with Stephan Ewen, a project committer for Apache Flink about the 1.0.0 Release and the roadmap
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.
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.