Monitoring container ecosystem becomes critical in terms of large business applications with complex use cases, making it challenging for the human brains to troubleshoot problems. Though there are traditional monitoring tools available for containers, recurring problems caused by business use case flow cannot be monitored or healed in traditional docker monitoring systems.
With the help of AI, containers can be monitored in a way where the business operations can inject rules depending on their use case and help save sapiens from troubleshooting. Moreover, AI provides flexibility for use case architects to define their commonly known problems in a docker environment, and define rules accordingly to mitigate them dynamically by better prediction algorithms and gradually optimizing the containers in the long run.
This presentation offers knowledge on making use of the benefits of AI in container ecosystem in solving business aspects of container monitoring and healing.
Key takeaway:
- Understand monitoring capabilities on containers.
- Exploring possible causes of failures in container ecosystem with respect to large-scale complex business applications.
- Understand the need for using AI to analyze recurring problems in container ecosystem and heal them in an optimized way.
- Understand the key concepts of AI with respect to container monitoring.
- Knowledge on Integrating AI engine with the container
