About APIs; backend performance metrics; & learnings from continuous deployment

mohanarpit profile image Arpit Mohan Originally published at insnippets.com ・2 min read

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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Posted on Dec 3 '19 by:

mohanarpit profile

Arpit Mohan


Co-founder & CTO, Appsmith. ❤️ Distributed Systems. 3X Founder - backed by YC, Sequoia Capital & Accel Partners. Strongly believe in the philosophy “Always be building"


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