Cloud & Big Data

Understanding Serverless Cloud and Clear

By Martijn van Dongen. Serverless is considered the successor to containers. And while it’s heavily promoted as the next great thing, it’s not the best fit for every use case. Understanding the pitfalls and disadvantages of serverless will make it much easier to identify use cases that are a good fit. This post offers some technology perspectives on the maturity of serverless today. First, note how we use the word serverless

Orchestration, stacks and getting over Netflix

There are some huge challenges at Big Silicon Valley companies, like Netflix and the need to scale. But should you really get drawn into that? Sometimes the most complicated issue in development is the business logic, and Bernd Rücker is talking about these challenges at Voxxed Days Vienna this week. We asked him what the complications and challenges are beyond the stack.   What is missing in the typical ‘Silicon

Handling Billions Of Edges in a Graph Database

As the complexity and amount of data increases, new database structures that offer different solutions from relational databases are growing in popularity. One of these is the graph database. At Voxxed Days Bucharest, Michael Hackstein is talking about graph databases, and how to overcome the limits of scalability that they can suffer from. We asked him about them.   What is a node, edge and property in a graph database?

Securing microservices

Security is often seen as an abstract concept, a separate concern to everyday development. However with a shift in architecture and the increasing adoption of microservices, it is essential to factor it in to your development iterations. At Voxxed Days Bristol, Kate Stanley is giving a practical example of how to secure microservices. She will look at how to utilise industry-wide standards such as OAuth2 and OpenID Connect. We asked Kate

Trends in the Cloud: Cloud-Based Security

By William Hurley from Astadia Adoption and use of cloud-based software engineering platforms will accelerate in 2017. Teams have been working in the cloud for a few years now, but in 2017, the trend will gain far more momentum as senior engineering staff and service providers realise and document the benefits of cloud-based development gains. Adoption will not be limited to open source or Microsoft solutions as all software engineering tool stacks

App Dev in the Cloud: How To Run JBoss BPM Suite in a Container

Containerized JBoss BPM Suite! I have a series of articles where I explore with you the reasons why application developers can’t ignore their stacks anymore, which refers to the Cloud based infrastructures they working in their daily jobs. This led to my explorations of the possibility to create that Cloud based infrastructure locally as a substitution for the full blown Red Hat Cloud Suite experience. What would be nice I

The Rise of Big Data Streaming

Daniel Cook is speaking at Voxxed Days Bristol about High Velocity Streaming. Frequently I’m asked what all the hype behind this Big Data nonsense is about. To some extent I think dropping the ‘Big’ would get more buy in from developers. Streaming architectures supported by technologies such as Kafka, Storm, Spark and Flink can really scale to the Big in Big Data, however we’re missing the real use case. These

Near real-time Big Data

There is a wealth of data around on public transport. What is the best way to take advantage of it? Alexandre Masselot is giving an introductory talk, exploring some of the on-trend frameworks at Voxxed Days Zurich. We asked him what inspires him, and the importance of near real-time Big Data.   What inspires your talk on Big Data? I’ve been doing this kind of thing since my PhD in

Using a time series NoSQL database

By Stephen Etheridge, EMEA Solutions Architect In today’s increasingly automated world, we rely on vast networks of computers to help us make difficult decisions. We have long since passed the point where humans can manually analyse the vast swathes of data that are factored into each choice. Now even many purpose-built databases are failing to keep up with the scale of data generated by the vast number of IoT sensors

Accessible Machine Learning

Machine Learning is often seen as the exclusive preserve of Data Scientists. Danilo Poccia disagrees. To learn the basics he will be speaking at Voxxed Days Zurich on the 23rd of February. We asked him what makes him think non-mathematicians and scientists can get started with Machine Learning.   Do you think machine learning is accessible to everyone? Do I need a PhD? How easy is it to get started? Machine Learning