Endjin - Home

Big Compute

In this series, we’re comparing cloud services from AWS, Azure and Google Cloud Platform. A full breakdown and comparison of cloud providers and their services are available in this handy poster. We have assessed services across three typical migration strategies: Lift and shift – the cloud service can support running legacy systems with minimal change […]


We have produced an insightful booklet called “Embracing Disruption – Financial Services and the Microsoft Cloud” which examines the challenges and opportunities for the Financial Service Industry in the UK, through the lens of Microsoft Azure, Security, Privacy & Data Sovereignty, Data Ingestion, Transformation & Enrichment, Big Compute, Big Data, Insights & Visualisation, Infrastructure, Ops & Support, and the API Economy.


Azure Batch – Time is Money in Big Compute

by James Broome

Earlier in the year, endjin worked with the Azure Batch Product Team to run a series of experiments against the Azure Batch service using a framework we developed for performing scale, soak and performance tests. We’ve had conversations with a number of organisations over the last 5 years who have scaled their compute intensive workloads (SAS, […]


A short while ago, I was trying to classify some data using Azure Machine Learning, but the training data was very imbalanced. In the attempt to build a useful model from this data, I came across the Synthetic Minority Oversampling Technique (SMOTE), an approach to dealing with imbalanced training data. This blog describes what I […]


Spinning up 16,000 A1 Virtual Machines on Azure Batch

by Howard van Rooijen

Big Compute, like Big Data has a different meaning for every organisation; for Big Data this generally tends to be when data grows to a point where it can no longer be stored, queried, backed up, restored or processed easily on traditional database architectures. For Big Compute this tends to be when computation grows to […]