Omega (CC, Distributed Processing)

Question 1

What is the Background (Omega)?

Answer 1

Omega is a parallel scheduler architecture built around shared state, using lock-free optimistic concurrency control. It is Google’s next-generation cluster management system.

Omega aimed to address the limitations of monolithic and two-level scheduling architectures.

Question 2

What is the Problem (Omega)?

Answer 2

• Monolithic schedulers, like Borg, are inefficient and do not scale well.
• Two-level approaches, like Mesos and Hadoop-On-Demand, lack flexibility and parallelism due to resource-visibility and locking tools. They also struggle with tasks that don’t modularize well.
• Previous cluster scheduling algorithms could not meet the demands of Google’s high-level, diverse workloads.

Question 3

What is the Solution to the problem (Omega)?

Answer 3

• Omega uses a shared-state architecture where multiple application-level schedulers share a cluster and schedule jobs in parallel.
• Changes are made optimistically, with the idea that failures are acceptable in favor of overall speed.
• Omega allows frameworks’ schedulers to make decisions and update the shared cell state in an atomic commit.

Question 4

What is the application (Omega)?

Answer 4

Google’s Borg system uses Omega.

Question 5

Strengths and Weaknesses (Omega)?

Answer 5

Advantages:
- Architectural Novelty: Shared-state scheduling allows multiple schedulers to operate in parallel.

• Flexibility: It supports tailored scheduling policies for diverse tasks.
• Scalability: It is designed for large-scale clusters with fault tolerance.
  Pluggable Logic: Scheduler logic can be replaced or customized by users.
• Omega’s design has influenced other systems, including Kubernetes and Ray

Disadvantages:
- Increased conflicts can occur with more schedulers, potentially leading to recomputations.

• Being closed source, Omega is not directly accessible for use outside of Google