Autoscale good parts
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The good parts of https://github.com/rackerlabs/otter
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Autoscale good parts
- 1. Otter – the good parts
- 2. Stateless functional architecture - Suitable for running on “the cloud”
- 4. Health check / monitoring
- 7. Deferred utils - retry_and_timeout
- 8. Deferred utils – wait decorator
- 9. Logging
- 10. Structured logging with JSON output
- 11. Logging – Spec based
- 13. Effect – better unit tests
- 14. Cloud client library based on Effect - Nova - CLB - RCv3 - Heat - Cloud feeds
- 16. get_server_details get_my_server_details(tenant_id) authentication & service catalog http request with URI and auth token Perform the request on twisted
Editor's Notes
- There are two properties described: stateless and functional, Stateless advantages: Horizontally scalable, Allows partial failures (nodes can go down or network can malfunction), Easily deployable via docker Functional means core behavior is implemented as pure functions which enables easy unit tests. Property based testing also possible
- Each log is identified in the table on the left, it gets expanded to string on the right. The format strings gets expanded based on keyword args. There is also provision to split large logs as in `execute-convergence`.
- Detailed error handling specific to Rax public cloud Response logging for debugging
- The implementation of APIs does not know about concrete details like specific service URI, authentication, service catalog, tenant ID and so on. In fact they don’t know about underlying framework used.
- The auth part is implemented with caching authenticator where for every request code always auths and invalidates it when it receives 401. All this is completely shielded from actual API implementation
- This is part of code that takes the tenant id and generates the final HTTP request to be sent. Request is bare minimum function that returns step to execute HTTP request. Notice how it adds functionality to function using decorators
- The idea of scoping effect on a tenant was applied to logging.