In the context of cloud-native applications, both Ingress and Gateway APIs serve critical roles in managing traffic flow. However, the key SLIs (Service Level Indicators) and SLOs (Service Level Objectives) that are relevant may vary based on the configuration and specific use cases. Below are some important SLIs and SLOs relevant to Ingress and Gateway API:
Response time should be less than 200ms for 95% of requests.
Error rate should be lower than 1%.
Service availability should be above 99.9%.
Throughput should meet the scaling requirements for user traffic.
Keep latency under 100ms for 95% of requests.
Utilizing tools such as Prometheus and Grafana can help in continuously monitoring these SLIs and ensuring that SLOs are met, thus maintaining the desired service quality.
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?