The DevOps Journey
Organizations implementing DevOps and Continuous Delivery practices understand testing often and getting quicker feedback is key to a successful DevOps implementation. But as organizations seek to improve their product quality and delivery speed, having the ability to predict quality and performance issues before they occur would help organizations concentrate their efforts on improving other areas of the CI/CD pipeline. As organizations implement DevOps practices, it is important they track key metrics and KPIs which can be leveraged in such predictions.
Saving the day with Predictive Analytics
Qentelli helped many organizations implement end to end CI/CD pipeline with automated early Performance, Security and Functional testing. In our experience, production defects and performance issues caused unanticipated application downtimes and rollbacks. As we started collecting metrics, logs and data from the environments and analysing the logs and other KPIs, we were able to identify patterns and generate algorithms that could predict possible areas in environment and code that could cause most common production issues. There were many instances when many hours or days of production downtime was avoided as the incidents were predicted in production environments before they occurred, and corrective actions could be taken to almost cause no downtimes and rollbacks.
As organizations implement predictive analytics, alert and notification systems, they would be able to improve their processes to avoid common mistakes. But, being able to achieve better quality and speed would mean more than predicting production issues, and AI can help in other areas during the pipeline to improve quality and speed.
Improving Quality and Speed with AI
Improving quality in a CI/CD pipeline would mean identifying failures and failing fast, auto healing test scripts based on application changes. AI-driven tools, such as Qentelli’s AiR, provide the ability to auto-heal test scripts based on changes to code base and predicting issues with code during performance tests based on the result patterns. Such AI-driven tools will improve the overall quality of the application being deployed into production and help in faster feedback during various stages of the CI/CD pipelines. This ability to predict issues and to fail fast would result in better overall delivery speed for organizations. AI-driven tools and Predictive analytics as part of your CI/CD pipeline is the next big step your organization can take today to be future ready and deliver faster with better product quality.
To learn and explore more in detail about Qentelli’s AI-driven DevOps implementations, please write to us at email@example.com. Our experts will be delighted to engage with you. Also, you can visit Qentelli’s social links for more details – Facebook Twitter LinkedIn
Headquartered in Dallas, TX with global delivery teams in India, Qentelli is an Industry Thought Leader in Quality Engineering, Automated Testing and Continuous Delivery. With high performing engineering teams working in the dedicated Innovation Group, Qentelli brings design thinking to address complex business problems and enables Continuous Delivery across Enterprise IT through automation for its global customers.