Rolling updates on Linux allow you to upgrade or modify services without taking down the entire system, ensuring high availability and minimal downtime. This process is particularly beneficial in production environments where continuous service is critical.
Rolling updates, Linux updates, High availability, Service management, Zero downtime
This guide covers the process of implementing rolling updates on Linux systems, using tools and techniques that ensure system reliability and continuous service delivery.
# Example of rolling updates using a container orchestration tool (Kubernetes)
# 1. Make sure you have a deployment set up
kubectl create deployment myapp --image=myapp:1.0
# 2. Update the application
kubectl set image deployment/myapp myapp=myapp:1.1
# 3. Monitor the rollout status
kubectl rollout status deployment/myapp
# 4. Rollback if necessary
kubectl rollout undo deployment/myapp
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?