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Build autoscaler abstractions like fetcher, client and scaler #300
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algorithm is extracted to distinguish with the scaler.
1. Split the Scaler interface and BaseAutoscaler implementation 2. Create APA/KPA scaler separately and adopt the corresponding algorithms
Great work! I 'd like to follow
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What's the update-to-date |
kr11
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Oct 16, 2024
kr11
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Oct 16, 2024
@kr11 Here's the new commands to use
We change to |
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This PR LSTM, let's merge it. |
Jeffwan
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Oct 22, 2024
* Update manifests version to v0.1.0-rc.3 (#287) * [Misc] Add sync images step and scripts in release process (#283) Add sync images step and scripts in release process * [batch] E2E works with driver and request proxy (#272) * e2e driver and test * comment functions * check job status in test * format update * update copyright * add examples with instructions and interfaces * move batch tutorial --------- Co-authored-by: xin.chen <[email protected]> * Fix address already in use when AIRuntime start in pod (#289) add uvicorn startup into file entrypoint * Read model name from request body (#290) * Use model name from request body * rename dummy to reserved router * Fix redis bootstrap flaky connection issue (#293) * skip docs CI if no changes in /docs dir (#294) * skip docs CI if no changes in /docs dir * test docs build * Improve Rayclusterreplicaset Status (#295) * improve rayclusterreplicaset status * nit * fix lint error * improve isClusterActive logic * fix lint error * remove redundant isRayPodCreateOrDeleteFailed check --------- Signed-off-by: Yicheng-Lu-llll <[email protected]> * Add request trace for profiling (#291) * Add request trace for profiling * add to redis at 10 second interval * nit * round to nearest 10s interval * round timestamp to nearest 10s interval and aggregate data by model * add go routine to add request trace * Update the crd definiton due to runtime upgrade (#298) #295 introduce the latest kuberay api and the dependencies bumps sigs.k8s.io/controller-runtime from v0.17.3 to v0.17.5. Due to that change, make manifest update the CRD definitions * Push images to Github registry in release pipeline (#301) * Disable docker build github workflow to cut CI cost * Push images to Github registry in release pipeline * Build autoscaler abstractions like fetcher, client and scaler (#300) * minor clean up on the autoscaler controller * Extract the algorithm package algorithm is extracted to distinguish with the scaler. * Refactor scaler interface 1. Split the Scaler interface and BaseAutoscaler implementation 2. Create APA/KPA scaler separately and adopt the corresponding algorithms * Introduce the scalingContext in algorithm * Introduce k8s.io/metrics for resource & custom metrics fetching * Extract metric fetcher to cover the fetching logic * Optimize the scaler workflow to adopt fetch and client interface * Further refactor the code structure * Support pod autoscaler periodically check (#306) * Support pod autoscaler periodically check * Fix the error case * Add timeout in nc check for redis bootstrap (#309) * Refactor AutoScaler: metricClient, context, reconcile (#308) * Refactor AutoScaler: optimize metric client, context, and reconcile processes. * fix make lint-all * fix typos --------- Signed-off-by: Yicheng-Lu-llll <[email protected]> Co-authored-by: xinchen384 <[email protected]> Co-authored-by: xin.chen <[email protected]> Co-authored-by: brosoul <[email protected]> Co-authored-by: Varun Gupta <[email protected]> Co-authored-by: Yicheng-Lu-llll <[email protected]> Co-authored-by: Rong-Kang <[email protected]>
gangmuk
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Jan 25, 2025
* minor clean up on the autoscaler controller * Extract the algorithm package algorithm is extracted to distinguish with the scaler. * Refactor scaler interface 1. Split the Scaler interface and BaseAutoscaler implementation 2. Create APA/KPA scaler separately and adopt the corresponding algorithms * Introduce the scalingContext in algorithm * Introduce k8s.io/metrics for resource & custom metrics fetching * Extract metric fetcher to cover the fetching logic * Optimize the scaler workflow to adopt fetch and client interface * Further refactor the code structure
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Pull Request Description
This pull request includes several significant updates to the Pod Autoscaling algorithms and their related components. The changes introduce new scaling algorithms, enhance the existing ones, and update the metrics fetching mechanisms. Below are the most important changes grouped by theme.
New and Enhanced Scaling Algorithms:
ScalingAlgorithm
interface and extract theApaScalingAlgorithm
andKpaScalingAlgorithm
classes with their respectiveComputeTargetReplicas
methods.PodMetricClient
structure and introduced methods for updating and fetching pod metrics.MetricFetcher
interface and implemented it withRestMetricsFetcher
,ResourceMetricsFetcher
, andCustomMetricsFetcher
classes. (pkg/controller/podautoscaler/metrics/fetcher.go
)These changes collectively enhance the autoscaling capabilities and metrics handling of the Pod Autoscaler, making it more robust and flexible for different scaling scenarios.
Related Issues
Resolves: part of #119
Important: Before submitting, please complete the description above and review the checklist below.
Contribution Guidelines (Expand for Details)
We appreciate your contribution to aibrix! To ensure a smooth review process and maintain high code quality, please adhere to the following guidelines:
Pull Request Title Format
Your PR title should start with one of these prefixes to indicate the nature of the change:
[Bug]
: Corrections to existing functionality[CI]
: Changes to build process or CI pipeline[Docs]
: Updates or additions to documentation[API]
: Modifications to aibrix's API or interface[CLI]
: Changes or additions to the Command Line Interface[Misc]
: For changes not covered above (use sparingly)Note: For changes spanning multiple categories, use multiple prefixes in order of importance.
Submission Checklist
By submitting this PR, you confirm that you've read these guidelines and your changes align with the project's contribution standards.