A group of Charioteers sat down last week to discuss some of the technologies and tools we have been and will be watching in 2015. Some of these are beginning to establish themselves in the enterprise and some are still in early stages of adoption.
Many of these topics will be covered at the upcoming Philly Emerging Technologies for the Enterprise conference, coming up on April 7-8, 2015. Did we mention that early bird registration is open?
Here is the list. It is not exhaustive, but gives you an idea on where some of our engineers are focusing our research.
Massive Server Deployments and Containers – because more and more of the applications Chariot works on are being deployed to the cloud. Some technologies include:
- CoreOS and their Rocket container runtime
- Google's Kubernetes Container cluster manager
- Apache Mesos – a cloud distributed systems Kernel for programming your cloud datacenter and access services like Hadoop, Kafka, Zookeeper, configuring resources, deploy to Docker and more.
- Go golang.org– is a programming language in the C/Java family. There is a great engineering team behind it, the languages is simple to read, has good concurrency, compiles to native binaries.. It is a general-purpose language. Search for it with 'golang' rather than 'go' or you'll find a lot of information about the ancient board game…
- AtScript – not a language per-se, but a type definition layer atop of ECMAScript 1.6 and used by the Angular team for Angular 2.0 (see below).
- Spark – dubbed 'lightning fast cluster computing' holds the mantle as the new approach for data reduction, with claims of being more than 100x faster than typical Map/Reduce methods.
- Apache Kafka – a distributed cluster of server nodes that serves a number of use cases well, including messaging, website tracking, metrics collection, log aggregation and more.
- Graph-based data stores continue to innovate, including neo4j, Apache Giraph which helps analyze Facebook's social graph: this is the open source version of a technology written about at Google called Pregel.
- We are following machine learning innovations, with focus within the graph space – for a taste of this combination see this O'Reilly article.
- HBase – an API for random read/write access to your Big Data sets. Used by tools such as Hadoop and Spark.
- Parallel query engines for massive data searches using SQL and SQL-like languages. Tools include the MariaDB's Shard-Query and Impala.
The Internet of Things
- Bluetooth Low Energy allows for low-power devices that can run for hours or days on a single charge – see these Android Resources, iOS rseources
- Beacons – Apple's iBeacon and Google’s Nearby can help you track physical objects in space.
- Newer [less expensive wifi (http://hackaday.com/2014/08/26/new-chip-alert-the-esp8266-wifi-module-its-5/) – which could enable devices to work better for mesh networks, in low power situations, on smaller platforms, etc.
- Apple is moving away from Objective-C and into the new Swift Programming Language for its iOS and OS X development platform. Any iOS developer should be learning it for future development efforts.
- As usual, the raging debate of whether to write native phone applications, pure web-based applications that are phone-friendly, or hybrid mobile native apps with tools like Apache Cordova, rages on.
- Anything that Facebook, Google, Netflix, LinkedIn is writing a paper on or their open source projects is worth reading about and keeping on our radar. A really interesting GitHub repository for those is called Papers We Love.
Which ones will you be using in the upcoming year in your environment? Leave us a comment below.