Guest Post: Keeping Up with the Cycle of Continuous Delivery
The strain on businesses to keep up with the speedy technological advances make it ever more important to make sure that test teams are able to function at full capacity right from the start.
The concept and cycle of ‘Continuous Delivery’ (CD) is something that all businesses should not just consider; they should make it a necessity in their major delivery strategies. Let’s look into the end-to-end process at the sort of problems that may arise when organisations attempt to continuously deliver applications into production.
For many test teams, one of the first tasks is masking/subsetting the database, so that it is ready to use in non-production. This is usually a manually process which causes delays and constraints when searching for appropriate and effective data. Quality data is inherently compromised in this first instance as production data only really covers states that have previously been covered before: it doesn’t therefore contain the negative scenarios, outliers, or unexpected results which are most likely to cause a system to collapse and which must be tested against.
This means that testers are not able to build a new subsystem and defects will most likely be detected in later stages, where they cost up to 1000 times more to fix than if the fault had been recognised at the beginning (Bender RBT, 2009).
Because CD must be ongoing and testing occurs quickly, testers and developers will often receive feedback and have to quickly implement change requests before they can move on to another aspect of the project. Have a peek at this quirky cartoon developed by Nhan Ngo from Spotify to find out more.
“How can we implement Continuous Delivery? Is it a thing, a process or what?” Well, the answer is by simply minimising and reducing constraints around the testing process from start to finish by overcoming the obstacles that stand in front of product delivery. How do we do this? By removing dependency constraints on data availability from upstream teams – i.e. removing the constraints which mean that teams often wait for weeks for data to become available because another team is using it. This in turn makes the team able to respond to quick changes and evolving business requirements….Rather than working on borrowed time and cost on the budget extension.
A simple, effective and fast solution is to synthesize all possible data needed initially so that it can be tested against ‘real world’ conditions instantly. Read more on this here
Find out more on implementing Continuous Delivery on our webinar with guest Diego Lo Giudice from Forrester Research, at 4-5pm BST / 11-12am EDT / 8-9am PDT on June 30th. Register now!
Grid-Tools is the leading test data management company providing innovative methods for synthetic data creation, data masking, subsetting, data analysis and SOA virtualization. Headquartered in Oxford, UK, with offices in New York, USA, our personnel write and develop solutions for some of the largest financial institutions and government agencies, telecoms, insurance providers and media and communications corporations around the globe.