- An understanding of distributed systems
- Experience with some kind of distributed application or framework (e.g., Hadoop)
- Familiarity with Linux commands
Audience
- IT administrators
- Software Engineers
- Developers
Apache Mesos is an open source cluster manager that enables dynamic resource sharing and allocation across multiple distributed systems. It provides a scheduling mechanism that facilitates the logistics for running and monitoring tasks over a set of frameworks or applications. Some software companies that use Apache Mesos are Twitter, Airbnb, Netflix, and Apple.
This instructor-led, live training (online or onsite) is aimed at IT administrators, software engineers, and developers who wish to use Apache Mesos to efficiently manage resource workloads and applications in large-scale clustered environments.
By the end of this training, participants will be able to:
- Install, configure, and run Apache Mesos for distributed systems.
- Manage resource sharing and allocation of multiple applications and frameworks.
- Implement scheduling mechanism for managing tasks.
- Set up and use Marathon to handle container orchestration on Apache Mesos.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction
- Apache Mesos vs Kubernetes or other cluster managers
- Overview of Apache Mesos Features and Architecture
Getting Started
- Installing and building Apache Mesos
- Setting up Master and Agent
Configuring Apache Mesos
- Setting up roles and users
- Configuring networking
- Configuring security
Managing an Apache Mesos Cluster
- High-Availability usage and fault recovery
- Logging and debugging
- Upgrading and downgrading clusters
- Implementing metrics and alerts for monitoring
Working with Containers
- Installing Marathon on Apache Mesos
- Deploying containerized applications on Apache Mesos with Marathon
Troubleshooting
Summary and Conclusion