ByteDance DevOps Engineer System Design Questions

ByteDance aims to maintain high availability and performance across its multiple applications through effective monitoring. Your task is to design a Service Health Monitor that periodically checks the health of services and alerts when issues arise.Success Criteria:
- The system should check multiple endpoints.
- Monitoring should provide real-time and historical data on service performance.
- It should send alerts for health status changes via defined channels (e.g., Slack, email).
- The system needs to be efficient and scalable to handle a growing number of services over time.Key Users:
- DevOps teams who need to ensure uptime.
- Engineering teams who require feedback on service performance.
- Stakeholders who need assurance regarding system reliability.Constraints:
- Monitoring interval can be configurable from 1 to 60 seconds.
- The system must support at least 1000 services at peak load.

ByteDance requires an efficient caching mechanism to reduce latency for frequently accessed API responses. Your task is to implement an LRU (Least Recently Used) Cache class that supports get and put operations.Problem statement:
The LRU Cache should have a maximum capacity and evict the least recently used item when the capacity is reached.Method signatures:
- def get(self, key: int) -> int:: Get the value of the key if the key exists in the cache, otherwise return -1.
- def put(self, key: int, value: int) -> None:: Update the value of the key or insert the key if it is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting the new item.Example 1:
Input: cache = LRUCache(2)
cache.put(1, 1)
cache.put(2, 2)
cache.get(1)
Output: 1
Explanation: Returns 1Example 2:
Input: cache.put(3, 3)
cache.get(2)
Output: -1
Explanation: Evicts key 2 and returns -1.Constraints:
- Capacity of the cache will not exceed 3000.
- All keys and values will be in the range of 1 <= key,value <= 10^4.