5 items found: Search results for "api simulation" in all categories x
March 17, 2016 | Software Consultancy
In order to be able to regularly release an application, your automated tests must be set up to give you fast and reliable feedback loop. If bugs are only found during a long and expensive multi-service or end-to-end test run, it can be a hinderance to fast delivery. Unfortunately I have often seen this problem in development environments: a huge suite of clunky, flaky and slow end-to-end tests which test the full functionality of the application as opposed to being more lightweight and reflecting basic user journeys. This produces the “ice cream cone” anti-pattern of test coverage, where unit tests aren’t providing the kind of coverage and feedback they need to.
July 3, 2016 | DevOps
Several of us from the OpenCredo team were in attendance at the inaugural EU edition of the DevOps Enterprise Summit conference. We have been big fans of the two previous US versions, and have watched the video recordings of talks (2014, 2015) with keen interest as many of our DevOps transformation clients are very much operating in the ‘enterprise’ space.
March 2, 2016 | DevOps, Microservices
Many of our clients are currently implementing applications using a ‘microservice’-based architecture. Increasingly we are hearing from organisations that are part way through a migration to microservices, and they want our help with validating and improving their current solution. These ‘microservices checkup’ projects have revealed some interesting patterns, and because we have experience of working in a wide-range of industries (and also have ‘fresh eyes’ when looking at a project), we are often able to work alongside teams to make significant improvements and create a strategic roadmap for future improvements.
January 11, 2018 | Data Engineering
The last few years have seen Python emerge as a lingua franca for data scientists. Alongside Python we have also witnessed the rise of Jupyter Notebooks, which are now considered a de facto data science productivity tool, especially in the Python community. Jupyter Notebooks started as a university side-project known as iPython in circa 2001 at UC Berkeley.
September 21, 2016 | DevOps
Sometimes, it can be difficult to write automated tests for parts of your application due to complexities introduced by an external dependency. It may be flaky or have some sort of rate limiting, or require sensitive information which we don’t want to expose outside of our production environment. To get around this, teams might take the approach of manually stubbing the service or using mocks – but the former is tedious and error prone, whereas the latter doesn’t test collaboration at all.
