This DevOps Machine Learning Tutorial will help you understand;
1. What is Machine Learning? ( 0:33 )
2. Difference between machine learning and artificial intelligence ( 1:09 )
3. What is DevOps? ( 1:43 )
4. Benefits of Machine learning in DevOps ( 2:08 )
5. Disadvantages of Machine Learning ( 5:20 )
6. How to apply Machine Learning in DevOps? ( 3:37 )
Machine learning provides the computers with the ability to learn without being programmed. DevOps helps in the development and the operations teams work together which results in faster and shorter release cycles.
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DevOps and machine learning share a powerful alliance with related capabilities such as:
1. Proof check highly complex datasets.
2. Detect patterns and antipatterns.
3. Uncover new ideas.
4. Repeat and refine queries.
5. Predictive analytics.
6. Operations analytics.
7. Artificial intelligence.
Below are some of the examples of machine learning being applied in DevOps:
1. Detect anomalies in the data of DevOps tools.
2. Figure errors in QA results and present better patterns.
3. Detect malicious activities of DevOps personal-stealing intellectual property, deploying authorized code.
4. Point errors in large data volume, transaction records, and the number of users.
5. Detect issues with new release based on available logs.
6. Plan the best configuration to maximize performance.
7. Detects good and bad patterns and alerts ” Business and development team.
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Who should do this course?
DevOps career opportunities are increasing. Many organizations with to adopt DevOps practices to improve the reliability and maintainability of their production environments. The course will be of benefit for the following professional roles:
1. Software Developers
2. Technical Project Managers
4. Operations Support
Prerequisite knowledge of software development, preferably in Java, and the UNIX/Linux command line tools is essential for this course.
Simplilearn’s DevOps training course is designed to help you become a DevOps practitioner and apply the latest in DevOps methodology to automate your software development lifecycle right out of the class. You will master configuration management; continuous integration deployment, delivery, and monitoring using DevOps tools such as Git, Docker, Jenkins, Puppet, and Nagios in a practical, hands-on and interactive approach. The DevOps training course focuses heavily on the use of Docker containers, a technology that is revolutionizing the way apps are deployed in the cloud today and is a critical skillset to master in the cloud age.
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