TL;DR style notes from articles I read today.
From API craftsmanship to API landscaping
- Don’t let a fear of having too many APIs limit you. Some APIs will die while others will flourish with natural selection.
- The effectiveness of your APIs should be felt and not seen. Changes in how consumers use APIs should be invisible to producers and vice versa.
- Moat your APIs with a robust, organization-wide security strategy.
- Allow your APIs to be discovered depending on whether they’re public, partner-facing, or private.
- Use a sound versioning strategy.
- Build your API ecosystem in a way that it can still work even if one is broken.
Full post here, 5 mins read
Learnings from the journey to continuous deployment
- Incremental changes result in easily maintainable products.
- Releasing with smaller changes at regular intervals brings value to customers faster and provides early feedback on future tasks.
- Improve code quality by writing quality tests and setting up comprehensive test strategies for the entire build and deploy pipeline.
- Improve integration testing in the staging environment to detect issues related to dependencies.
- Monitoring critical parameters such as system load, API latency, and throughput are vital to assess the health of the software.
Full post here, 5 mins read
Back-end performance, those metrics we should care about
- The latency requirement should correspond to the specific service type.
- There is a strong correlation between throughput and latency in a performance test. Latency increases with the growth of throughput.
- Normally network issues like congestion-caused errors should not exceed 5% of the total requests, and application-caused errors should not exceed 1%.
- As the CPU determines a server’s performance, a high sy means the server switches between user mode and kernel mode too often, which is bad for overall performance.
- Frequent reading or writing the disk could cause long latency and low throughput.
Full post here, 10 mins read
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