Cloud platform infrastructure provision (AWS, Google, Microsoft, Oracle, etc.): Platform and software use results in an efficient cost solution, since most cloud providers offer pay-per-use rates, which fits the uneven usage patterns of QA platforms. The flexibility and speed of cloud environments is ideal for handling the emerging needs of, test, preproduction, migrations, POC, training, etc.
Platform Preparing: QA environment dynamism requires mechanisms and procedures of preparation and administration that allow us to answer swiftly to the requirements of QA environments.
Platform Administration: Depending on the degree of criticality and amount of resources involved, a QA platform may have a level of administration similar to that of productive platforms, probably with SLA and different hourly coverage.
Replication: QA environments, training and development often require duplicates of the productive environments. This can be done through selective handovers using scripts, import datapump or total handovers (using RMAN). It is important to have efficient and agile mechanisms to carry out data updates, whether scheduled or on demand.
Test automation: With Jmeter it is possible to implement automated tests of, load, functional, performance or regression. JMeter has modules to handle Web, Database, WebService, and other tests.
Source reception and validation, packaging of executables, release of application in QA, pre-productive and productive.
Administration and configuration of Continuous Integration tools (source control, packaging and distribution, unit tests, quality scan of sources, etc.)
Implementation and administration of server backups either in the cloud or on-premise.
Execution of server activity plan (upload and download) at scheduled intervals or on request. This allows to reduce charges in server use.