Browse our archives by topic…
Blog
Cloud Adoption: A Deep Dive into the Swiss Cheese Model
In the second part of this series, we take a deep dive into the Swiss Cheese Model and show how this type of threat modelling is essential for understanding the risks that adopting Microsoft Azure post your organisation, and how you mitigate them.
Querying the Azure DevOps Work Items API directly from Power BI
Discover Azure DevOps Work Items features, use RESTful API for insights, and Power BI visualization in our step-by-step guide.
Automating creation of new ALM environments using PowerShell and Azure DevOps
Did you know that you can fully automate the bootstrapping process of setting up an Azure DevOps enviornment? This post shows you how.
Microsoft Azure Most Valuable Professional 2016
It is with a huge amount of honour to announce that endjin co-founder, Howard van Rooijen, has been awarded an Azure MVP award for his contributions to the Azure ecosystem.
Guest Blog Post: Hello World! I'm Adanma and I'm doing work experience.
Adanma spent a week with endjin gaining work experience, to see if a job in the world of Tech is something she'd like to do.
"But it works on my cloud!" - are your developers still making the same mistakes in a world of DevOps and PaaS services?
In the world of DevOps, cloud and platform services, how does a developer's "definition of done" need to change? This post argues that as the silos of development and operations are broken down, the responsibility of understanding the whole solution increases meaning, to truly take advantage of the cloud, the need for quality and professionalism is critical for success.
Automating R Unit Tests With Azure DevOps
Many organisations are starting to adopt the R Programming Language for their data science and financial modelling scenarios. But just because the language is being used for modelling, doesn't mean you should write unit tests that can be exercised as part of your CI/CD pipeline. In this blog post Jess Panni demonstrates how you can run R unit tests inside Azure DevOps.
Deploying to Azure using Azure Resource Manager templates and Octopus Deploy
Learn how to combine the power of Azure Resource Manager and Octopus Deploy for a frictionless Azure DevOps experience.
Cloud Adoption: Risks & Mitigations Analysis
In the first part of this series, we look at how you take a strategic look at the risks of adopting Microsoft Azure, and how you report these to C-level execs.
Using Postman to load test an Azure Machine Learning web service
Explore creating and testing an Azure ML Studio web service using Postman for efficient machine learning model production.
TeamCity MetaRunner for creating Release Annotations in Azure Application Insights
Meta-Runners allow you to easily create reusable build components for TeamCity, in this post I demonstrate how to create a Meta-Runner to create Azure Application Insights Release Annotations.
Year 2 as a software engineering apprentice at endjin
Alice reflects on year 2, being given more responsibility, diving deeper into all aspects of software delivery, and the good habits she's been building.
Automated R Deployments in Azure
My Apprenticeship Retrospective
In this post, Mike Larah reflects on his experiences going through the endjin three-year apprenticeship scheme
Using Azure Automation to run VMs during office hours only – using graphical runbooks
We've improved our approach for saving money by turning off our virtual machines outside of office hours. This post explored how to do it using graphical runbooks.
Machine Learning - the process is the science
What do machine learning and data science actually mean? This post digs into the detail behind the endjin approach to structured experimentation, arguing that the "science" is really all about following the process, allowing you to iterate to insights quickly when there are no guarantees of success.
Embracing Disruption - Financial Services and the Microsoft Cloud
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.
What makes a successful FinTech start-up?
In this post we discuss the characteristics of a great FinTech startup, and the importance of the API Economy to innovation in Financial Services.
The 100 Year Start-up: Embracing Disruption in Financial Services
Hymans Robertson was set up in Glasgow in 1921 and is one of the longest established independent firms of consultants and actuaries in the UK. Hymans Robertson soon realised that the computational requirements of their models exceeded the capacity of their on-premise datacentres and that the most cost effective solution would be to use the cloud to perform their Big Compute. But before they could harness the cloud to help them solve their Big Data problems, the business needed to understand the ramifications of moving to the cloud; everything from regulatory, risk and compliance concerns, to how their internal Ops team would need to evolve and adapt, and how to deal with moving data from on-prem into the cloud.
Why is blockchain revolutionising Financial Services?
There is a lot of hype about the blockchain - usually wrapped up with talk about Bitcoin and crypto-currencies. In this article, we look at its impact on trust, and auditability in financial services, and why it may (or may not) be appropriate for your solutions.
Regulatory Compliance and Cloud Adoption
In this post we review the FCA's guidelines for the adoption of cloud services by FinTech businesses, and help you to understand their impact across the value chain.
FinTech Week and the Microsoft Cloud
To celebrate FinTech Week, we've released an eBook based our our talk about Disruption in Financial Services at Future Decoded.
Machine Learning - mad science or a pragmatic process?
This post looks at what machine learning really is (and isn't), dispelling some of the myths and hype that have emerged as the interest in data science, predictive analytics and machine learning has grown. Without any hard guarantees of success, it argues that machine learning as a discipline is simply trial and error at scale – proving or disproving statistical scenarios through structured experimentation.
Improve your Windows Command Prompt and PowerShell experience with ConEmu
Mike Larah shares his tips for how to best customize ConEmu to improve your terminal experience for Windows Command Prompy and PowerShell
An experiment to automatically detect API breaking changes in .NET assemblies and suggest a Semantic Version number
Exploring the creation of a tool to detect accidental .NET API changes for accurate SemVer in NuGet packages.