According to a recent survey, companies that use databases as a service have grown to 45%. Interestingly, half of the large companies employ more than one open-source database service.
Open-source projects such as Linux or Kubernetes come once in a decade and change the course of industries. Open-source software has launched many billion-dollar ventures.
Open-source enables developers around the world to collaborate on a common goal. Benefits of the open-source market include:
- Infrastructure modernisation.
- Flexibility.
- Driving innovation.
- Incremental improvement of software
- Cost-effectiveness
Popular open-source projects:
Kubernetes
Application development is a big part of the open-source ecosystem. In 2014, Google introduced Kubernetes, a cluster of management systems to manage containerised applications. It provides mechanisms for maintenance, scaling and deployment of applications. Managers like Helm, Kubeflow, Kubetail, Knative, kubespray are part of this system.
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Cucumber
One of the most popular and recent open-source tools is Cucumber, which uses the latest Behavioural Driven Development (BDD) approach. Released in 2018, Cucumber supports different languages like Java.net and Ruby. It acts as a bridge between the business and technical language and allows the test script to be written without any coding knowledge.
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Appium
Appium is an open-sourced framework that automates the apps to be available in any language and testing framework. It provides full access to the back-end of APIs and DBs.
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CARLA
Open source simulators are used for developing as well as validating different prototypes for autonomous driving. CARLA is such an open-source simulator. CARLA, released in 2020, can be used to study modular pipeline, model for imitation learning and model for reinforcement learning.
AI Fairness360
IBM has come up with a toolkit called AI Fairness360 in 2018. It is an open-source library that contains algorithms for any AI lifecycle. Its package can be found in Python and also in R. The toolkit includes:
- An architecture to represent the dataset and also algorithms used for bias detection, explanation and also mitigation.
- An interactive interface for web users.
- A proper explanation for all metrics.
Despite its democratic outlook, open source has its share of fights. Earlier this year, two of the most significant open source contributors locked horns. Elastic had decided to alter the license for its flagship service called “Elasticsearch”, which also happens to be a key feature of AWS. Shay Banon, the CEO of Elastic, blamed AWS for doing things that are just “NOT OK”. “If we don’t stand up to them now, as a successful company and leader in the market, who will?”
He strictly disagreed with allowing any company to use Elasticsearch without first collaborating with them.
Also Read: Open Source Not So Open Anymore
Miscommunication between open source software developers and service providers can put other benefactors at risk. For instance, the landmark Google vs Oracle case might have put the whole billion-dollar Android industry in jeopardy if not for the top courts, favouring the open-source community. These periodic resets are good for the community as it makes the industry more antifragile. Be it machine learning application or the trip to Mars, 2021 has proven yet again that the open-source ecosystem is crucial for path-breaking innovations, and the open-source market is here to stay.
