- Update to version 0.0+git20200220.d3be16a:
  * use pull mode instead of event mode to monitor the stream changes on broker, since original event mode will block the read async thread
  * mkdir .cache if not exists
- Update to version 0.0+git20200219.7534b05:
  * add script to install kube-prometheus and k8s-prometheus-adapter
  * add checksum for download files
- Update to version 0.0+git20200219.4dab74d:
  * add HPA yaml files
  * fix python warning for unused return value
  * when a task meet with unrecovery exception, then stop all tasks and stop application, let kubernete restart container for full recovery
  * add initContainer for service dependency
  * add more references for custom metrics based HPA
  * add custom metrics based HPA
  * add note for timezone setting
- Update to version 0.0+git20200218.db6ecc1:
  * fix k8s document typo
  * add HPA example yaml file on metric CPU usage
  * fix broken link of doc reference
  * add step for exposing NodePort for metrics previewing
  * cleanup unused document reference
  * add reference of metrics and scale in top README.md
  * add document for dynamic scale and HPA
  * add doc inference_metrics.md for detail explains on metric collection and monitoring
  * add equation picture
  * add equation picture
  * add description of inference metrics monitoring
  * add description of tested kubernetes version
  * Correct the inference type with INT8/FP32 in dockerfile and standalone running scripts.
  * Correct the inference type with INT8/FP32 in dockerfile and standalone running scripts.
  * Add reference link for INT8 and FP32 model seperately.
  * add whitepaper reference
- Update to version 0.0+git20200215.2b8765e:
  * clean up the script of download-models.sh
  * fix the bug that websocket could not get event of stream adding/remove
  * fix the bug that websocket could not get event of stream adding/remove
  * add int8 inference support
  * use different macro for the path and name of inference model to avoid triggering the model download logic from openvino base container, which lead some issues for deployment
  * refine the gen-k8s-yaml script to handle the special characters like : / in prefix(namespace) of registry name
  * add pip mirror arg to accelerate docker build speed
  * check whether npm is installed before run npm command
  * Add customized grafana dashboard
  * Update metric scale_ratio algorithm
  * Update monitor docs
  * HPA on prometheus metrics
  * Add ei_scale_ratio metric for HPA
  * Reset the infer and drop fps metrics when idle 30s
  * Clean up the Dockerfile and script
  * Move drop fps to the inference stage
  * Use kube-prometheus for monitoring
- Use MYRIAD device instead of CPU
- Next round of adjustments for kustomize
- More changes to k8s-yaml samples for kustomize
- Rework k8s-yaml to fit better with kustomize
- Use official openSUSE redis image
- Rename dldt-python3 to python3-dldt
- Fix building on CODE15
- Add systemd service to run the css container
- run-css.patch: Adjust shell script to run the camera stream
  service
- Add elastic-inference-camera-stream sub packages allowing
  streaming a webcam into the cluster
- Fix dependencies of ei-css
- Adjust colors of stream view
- frame.py-error-handling.patch: do some error handling if the
  redis service is not yet reacheable
- websocket-server-retry.patch: handle timeout if gateway server
  is not coming up fast enough
- fix-person-detection-model-name.patch: use correct model for
  person detection
- Use ogv files instead of mp4 for the samples
- Add conflicts to the ei-* packages as the are not parallel
  installable
- Revert one user only change
- Create a k8s-yaml package
- Consolidate to one user only
- Enable health-check for redis calls
- Add ei-camera-stream-service
- Build models directory from git
- Add LICENSE files for sample videos and models
- Add ei-gateway-server
- Add ei-file-stream-service
- Add ei-websocket-server

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