* switch to ARM templates for config and VMs
* switch to ARM templates for config and VMs
* auto-formatting
* addressed Scotts comment
* added missing imports
* fixed gpu templates
fixed wheel reference
* added missing reference
* cleanup wording and yamls
* Update doc/source/autoscaling.rst
Co-Authored-By: Scott Graham <5720537+gramhagen@users.noreply.github.com>
Co-authored-by: Ubuntu <marcozo@marcozodev2.zqvgrdyupqrudayw1il1agipig.jx.internal.cloudapp.net>
Co-authored-by: Scott Graham <5720537+gramhagen@users.noreply.github.com>
* adding directory and node_provider entry for azure autoscaler
* adding initial cut at azure autoscaler functionality, needs testing and node_provider methods need updating
* adding todos and switching to auth file for service principal authentication
* adding role / scope to service principal
* resolving issues with app credentials
* adding retry for setting service principal role
* typo and adding retry to nic creation
* adding nsg to config, moving nic/public ip to node provider, cleanup node_provider, leaving in NodeProvider stub for testing
* linting
* updating cleanup and fixing bugs
* adding directory and node_provider entry for azure autoscaler
* adding initial cut at azure autoscaler functionality, needs testing and node_provider methods need updating
* adding todos and switching to auth file for service principal authentication
* adding role / scope to service principal
* resolving issues with app credentials
* adding retry for setting service principal role
* typo and adding retry to nic creation
* adding nsg to config, moving nic/public ip to node provider, cleanup node_provider, leaving in NodeProvider stub for testing
* linting
* updating cleanup and fixing bugs
* minor fixes
* first working version :)
* added tag support
* added msi identity intermediate
* enable MSI through user managed identity
* updated schema
* extend yaml schema
remove service principal code
add re-use of managed user identity
* fix rg_id
* fix logging
* replace manual cluster yaml validation with json schema
- improved error message
- support for intellisense in VSCode (or other IDEs)
* run linting
* updating yaml configs and formatting
* updating yaml configs and formatting
* typo in example config
* pulling default config from example-full
* resetting min, init worker prop
* adding docs for azure autoscaler and fixing status
* add azure to docs, fix config for spot instances, update azure provider to avoid caching issues during deployment
* fix for default subscription in azure node provider
* vm dev image build
* minor change
* keeping example-full.yaml in autoscaler/azure, updating azure example config
* linting azure config
* extending retries on azure config
* lint
* support for internal ips, fix to azure docs, and new azure gpu example config
* linting
* Update python/ray/autoscaler/azure/node_provider.py
Co-Authored-By: Richard Liaw <rliaw@berkeley.edu>
* revert_this
* remove_schema
* updating configs and removing ssh keygen, tweak azure node provider terminate
* minor tweaks
Co-authored-by: Markus Cozowicz <marcozo@microsoft.com>
Co-authored-by: Ubuntu <marcozo@mc-ray-jumpbox.chcbtljllnieveqhw3e4c1ducc.xx.internal.cloudapp.net>
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Remove all __future__ imports from RLlib.
* Remove (object) again from tf_run_builder.py::TFRunBuilder.
* Fix 2xLINT warnings.
* Fix broken appo_policy import (must be appo_tf_policy)
* Remove future imports from all other ray files (not just RLlib).
* Remove future imports from all other ray files (not just RLlib).
* Remove future import blocks that contain `unicode_literals` as well.
Revert appo_tf_policy.py to appo_policy.py (belongs to another PR).
* Add two empty lines before Schedule class.
* Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
* [Serve] Added deadline awareness
Added deadline awareness while enqueuing a query
Using Blist sorted-list implementation (ascending order) to get queries according to their specified deadlines. [buffer_queues]
Exposed slo_ms via handle/http request
Added slo example
The queries in example will be executed in almost the opposite order of which they are fired
Added slo pytest
Added check for slo_ms to not be negative
Included the changes suggested
* Linting Corrections
* Adding the code changes suggested by format.sh
* Added the suggested changes
Added justification for blist
Added blist in travis/ci/install-dependencies.sh
* Fixed linting issues
* Added blist to ray/doc/requirements-doc.txt
* Cleaner, tabulated progress output.
* Minor HTML changes, trial ID instead of name
* Revert basic variant changes
* Cleanup, address richard's comments, add progress_reporter.py
* Add tabulate dependency
* Added more info to table, auto-hide columns with no data.
* lint
* Address comments
* Replace experiment tag w/ trial ID
* Fixed tests.
* Fixed test
* Added requirement
* Fix formatting
* Implement metric interface
* Address comment: made actor_handles a dict
* Fix iteration
* Lint
* Mark lightweight actors as num_cpus=0 to prevent resource starvation
* Be more explicit about the readiness condition
* Make task_runner non-blocking
* Lint
* Implement flask_request and named python request
* Forgot to include missing files
* Address comment
* Add flask to requirements for doc (lint failed)
* Update doc requirement so lint will build
* Install flask in CI
* Fix typo in .travis.yml
* Commit and format files
* address stylistic concerns
* Replcae "Usage" by "Example" in doc
* Rename srv to serve
* Add serve to CI process; Fix 3.5 compat
* Improve determine_tests_to_run.py
* Quick cosmetic for determien_tests
* Address comments
* Address comments
* Address comment
* Fix typos and grammar
Co-Authored-By: Edward Oakes <ed.nmi.oakes@gmail.com>
* Update python/ray/experimental/serve/global_state.py
Co-Authored-By: Edward Oakes <ed.nmi.oakes@gmail.com>
* Use __init__ for Query and WorkIntent class
* Remove dataclasses dependency
* Rename oid to object_id for clarity
* Rename produce->enqueue_request, consume->dequeue_request
* Address last round of comment
There are several reasons for this:
* We no longer support python2
* There should be only 1 way of installing Modin
* Issue management on these wheels
* I have never heard of anyone using this feature
* It is rarely kept up to date
* Modin depends on specific versions of Ray because of past API changes
