autoscaling

问题 I am working on a picking legend with matplotlib. The goal is to hide and shows curves, by clicking on the legend. I found this solution (Hiding lines after showing a pyplot figure), which works very well. I want improve this code to adapt automatically the axis after each clic on the legend. I don't know if it is possible. Do you have any hint? Their is an example of what I want on the images below. First of all, the Image 1 represents the graph. Then after clicking on the legend 5*sin(x),

问题 I am working on a picking legend with matplotlib. The goal is to hide and shows curves, by clicking on the legend. I found this solution (Hiding lines after showing a pyplot figure), which works very well. I want improve this code to adapt automatically the axis after each clic on the legend. I don't know if it is possible. Do you have any hint? Their is an example of what I want on the images below. First of all, the Image 1 represents the graph. Then after clicking on the legend 5*sin(x),

问题 I have a server running on Kubernetes to handle hourly processing jobs. Thinking of using a service to expose the pods, and using an (external) cron job to hit the load balancer so that kubernetes can autoscale to handle the higher load as required. However in implementation, if the cron job sends, say, 100 requests at the same time while there's only 1 pod, all the traffic will go to that pod whereas subsequently spun up pods will still not have any traffic to handle. How can I get around

问题 Heroku doesn't offer auto-scaling for anything under the "performance tier" dynos ($250/mo). Hirefire used to be a gem that you could configure to autoscale dynos, but they realized that their solution could make money so now it's a paid service. What options are there (including rolling my own) for smaller apps to have intelligent scaling of dynos at no extra cost? 回答1: The cheapest solution in term of money, but at the cost of time would be to use Heroku's Platform API. The formation

问题 I have a requirement in which I need to automate the start and stop of the AWS EC2 Instances (within Autoscaling group) daily. This is mainly to prevent cost. I have built a Python script to start and stop EC2 instances but it's not working properly as EC2 instances are within an Autoscaling group. Does anybody know any solution for this? 回答1: An Amazon EC2 Auto Scaling group is designed to automatically scale so that extra instances can be added when there is a higher workload and instances

问题 I have a specific requirement where I just want to create only pull replicas using the solr autoscaling feature whenever the cluster starts the recovey process after a node failure. However Using solrcloud autoscaling creates NRT type replicas when node goes down and brought up. I have gone through the examples given in the policy specifcation list : https://lucene.apache.org/solr/guide/7_4/solrcloud-autoscaling-policy-preferences.html#policy-specification but I am not able to find a example

问题 I have configured Prometheus-adapter to fetch custom metrics from Prometheus. When I execute the command: kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1 Following is the result. { "name": "namespaces/envoy_http_ingress_http_downstream_cx_http1", "singularName": "", "namespaced": false, "kind": "MetricValueList", "verbs": [ "get" ] }, { "name": "namespaces/envoy_cluster_xds_cluster_upstream_cx_rx_bytes", "singularName": "", "namespaced": false, "kind": "MetricValueList", "verbs": [ "get

问题 I'm trying to enable AWS EKS autoscaling based on a custom Cloudwatch metric via the Kubernetes Cloudwatch adapter. I have pushed custom metrics to AWS Cloudwatch, and validated they appear in Cloudwatch console as well as are retrievable using the boto3 client get_metric_data. This is the code I use to publish my custom metric to Cloudwatch: import boto3 from datetime import datetime client = boto3.client('cloudwatch') cloudwatch_response = client.put_metric_data( Namespace='TestMetricNS',

问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 months ago . Improve this question I set a hpa use command sudo kubectl autoscale deployment e7-build-64 --cpu-percent=50 --min=1 --max=2 -n k8s-demo sudo kubectl get hpa -n k8s-demo NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE e7-build-64 Deployment/e7-build-64 <unknown>/50% 1 2 1 15m sudo

问题 Context: I am designing the auto-scaling (scale out) configuration for my .NET Framework 4.7 web app hosted on a Microsoft Azure App Service. I am using the P3V2 pricing tier. The application is CPU-bound. The app's 30 day CPU average is 30% usage while running on 2 instances, according to the stats indicated in the App Service plan. We occasionally have traffic spikes which will overwhelm the 2 instances: I want to implement auto-scaling. I want to take into account the App Service