kubernetes workers autoscaling based on rabbitmq queue size

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It's easy to use , Well documented , And there are a lot of ready-made retractors .

Once Adapter was in its place, I had to play with HPA and different Adapater config in order to understand its working.

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How To Use Remote Database For Rackspace Cloud Server? The Horizontal Pod Autoscaler automatically scales the number of Pods in a replication controller, deployment, replica set or stateful set based on observed CPU utilization (or, with custom metrics support, on some other application-provided metrics).

How do you work. Questions and Comments are welcome.

Applications Manager automatically discovers all RabbitMQ instances in your network and starts metric collection in minutes. Prometheus is.

Use KEDA From the dynamic expansion of our working device , Can significantly avoid Due to blocking I/O Caused by call Zap Processing delay . Use the RabbitMQ queue size to autoscale messaging applications in will check the queue size and scale our worker deployment based on. It describes how to set up Horizontal Pod Autoscaler based on RabbitMQ queue size. With KEDA, You can easily define the application you want to extend , Without changing the application itself , Other applications continue to run . https://github.com/jaskeerat789/Horizontal-Autoscale-Example.

Ideally, we would like to scale our workers on both CPU and our backlog of ready messages in RabbitMQ. Is this video of a fast-moving river of lava authentic? Is there a PRNG that visits every number exactly once, in a non-trivial bitspace, without repetition, without large memory usage, before it cycles? By defining our own metrics through the adapter's configuration we can let HPA perform scaling based on our custom metrics. The purpose of this project is to simplify and automate the configuration of a Prometheus based monitoring stack for Kubernetes cluster. Want To Show A Radar Chart In Flutter App, Radial Gradients Unexpected Webkit/Chrome Behaivor Full Area. Read the rest of this post on how Zapier uses KEDA on the Cloud Native Computing Foundation blog.

It involves a command or set of commands that collect a few essential metrics of the monitored system.

A simple golan server with two routes, one for pushing messages to rabbitmq queue and one for exposing metrics. There is a potential solution , stay Prometheus To collect RabbitMQ indicators , Create a custom indicator server , And configuration HPA To use these indicators . stay Zapier, We use Grafana[10] To visualize Thanos[11] High availability with long-term storage capacity Prometheus Set up Indicators of . information for subsequent evaluation of the performance of the intervention while minimising data collection costs. As discussed above, our goal is to auto-scale by looking at the queue length anf to achieve this we need to add monitoring service to our Cluster.

Well discuss the entire infra in the upcoming section and role of each part in detail.

Kubernetes Workers Autoscaling based on RabbitMQ queue size of more autoscalers for anyone interested in this topic. Since our metrics are not based on the Kubernetes. stay Zap in , At each step, we will send the message queue to RabbitMQ. (instead of occupation of Japan, occupied Japan or Occupation-era Japan), How to help player quickly made a decision when they have no way of knowing which option is best. However it doesn't collect custom metrics from RabbitMQ or Celery so you won't be able to use them in your Horizontal Pod Autoscaler HPA. KEDA is a Kubernetesbased Event Driven Autoscaler. We then try to scale the worker pods on the basis of the rabbitmq queue length. Once I was ready with my metric, next challenge was to get to HPA. Read the Zapier blog for tips on productivity, automation, and growing your business. Learn more. Prometheus Metrics based autoscaling in Kubernetes and then let the Horizontal Pod Autoscaler HPA use it to scale the pods up or down.

Is it possible to prevent quantum communication detection? 465). If a creature with damage transfer is grappling a target, and the grappled target hits the creature, does the target still take half the damage? There are community is actively adding exports and thus it likely that youll find one for your service. fast forward, i'm using keda now for scaling pods on queue metrics, here's the doc for rabbitmq. He has since then inculcated very effective writing and reviewing culture at golangexample which rivals have found impossible to imitate.

Now you can expose your web-server service using kubectl port-forward command and hit /generate route from browser multiple time in order to generate some traffic. Instrument your application to monitor application and businesslevel metrics via Cloud Monitoring. In order to generate a real life scenario, we take one message at a time and add a delay of 5 sec, representing the time needed to process a message.

Do Schwarzschild black holes exist in reality? I hope it will help someone: https://ryanbaker.io/2019-10-07-scaling-rabbitmq-on-k8s/. To learn more, see our tips on writing great answers. And then how we actually use RabbitMQ telemetry to scale our system dynamically of queues that we're interested in in a single metric.

I would like to thank Daniele Polencic whose talk motivated to design this architecture. These messages are run in Kubernetes Back end worker on worker Use . Natively horizontal pod autoscaling can scale the deployment based on CPU and Memory usage but in more complex scenarios we would want to. .css-143kls3-Link[class][class][class][class][class]{all:unset;box-sizing:border-box;-webkit-text-fill-color:currentColor;cursor:pointer;}.css-143kls3-Link[class][class][class][class][class]{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-143kls3-Link[class][class][class][class][class][data-color='ocean']{color:var(--zds-colors-blue-jeans,#3d4592);}.css-143kls3-Link[class][class][class][class][class][data-color='ocean']:hover{color:var(--zds-colors-night,#2c3266);}.css-143kls3-Link[class][class][class][class][class][data-color='ocean']:focus{color:var(--zds-colors-blue-jeans,#3d4592);outline-color:var(--zds-colors-blue-jeans,#3d4592);}.css-143kls3-Link[class][class][class][class][class][data-color='white']{color:var(--zds-colors-neutral-100,#fffdf9);}.css-143kls3-Link[class][class][class][class][class][data-color='white']:hover{color:var(--zds-colors-neutral-500,#a8a5a0);}.css-143kls3-Link[class][class][class][class][class][data-color='white']:focus{color:var(--zds-colors-neutral-100,#fffdf9);outline-color:var(--zds-colors-neutral-100,#fffdf9);}.css-143kls3-Link[class][class][class][class][class][data-color='primary']{color:var(--zds-colors-blue-jeans,#3d4592);}.css-143kls3-Link[class][class][class][class][class][data-color='primary']:hover{color:var(--zds-colors-night,#2c3266);}.css-143kls3-Link[class][class][class][class][class][data-color='primary']:focus{color:var(--zds-colors-blue-jeans,#3d4592);outline-color:var(--zds-colors-blue-jeans,#3d4592);}.css-143kls3-Link[class][class][class][class][class][data-color='secondary']{color:var(--zds-colors-neutral-100,#fffdf9);}.css-143kls3-Link[class][class][class][class][class][data-color='secondary']:hover{color:var(--zds-colors-neutral-500,#a8a5a0);}.css-143kls3-Link[class][class][class][class][class][data-color='secondary']:focus{color:var(--zds-colors-neutral-100,#fffdf9);outline-color:var(--zds-colors-neutral-100,#fffdf9);}.css-143kls3-Link[class][class][class][class][class][data-weight='inherit']{font-weight:inherit;}.css-143kls3-Link[class][class][class][class][class][data-weight='normal']{font-weight:400;}.css-143kls3-Link[class][class][class][class][class][data-weight='bold']{font-weight:700;}RabbitMQ is at the heart of Zap processing at Zapier. Currently just working for beacon nodes, Package go-unzip provides a very simple library to extract zip archive, A repository of example implementations of using AWS CDK with Go language, Neutrino CloudSync - An open-source tool used to upload entire file folders from any host to any cloud, OpenTelemetry Tracing instrumentation for PostgreSQL, SSE Client for Flashbots Relayer Data, written in go, Header Block - A middleware plugin for Traefik to block request and response headers which regex matched, A rootless container system written in Go following along Liz Rice's presentation at the goto conference, Lifecycle management of OS2mo entities using the GraphQL API, GSP761 Developing a REST API with Go and Cloud Run, A simulation to show what happens if to switch in Monty Hall problem using Go, Ability to swap out skate.ea graphics with custom ones, Resource: default monitoring by Kubernetes, Custom: metrics that are not recorded by k8s but is related to its Objects.

Kubernetes autoscaler for pods that consume RabbitMQ GitHub onfido/k8srabbitpodautoscaler: Kubernetes autoscaler for pods that consume RabbitMQ. In this example, we are using minikube as our local cluster setup. Some key topics covered by this guide are. Kubernetes has a wonderful feature called horizontal pod autoscaling that allows scaling of pods in your deployment based on the load that the.

Configuring the Horizontal Pod Autoscaler to autoscale your app is done by creating a HorizontalPodAutoscaler resource. keda_metrics_adapter_scaler_errors_total The total number of errors for all telescopes in the cluster, keda_metrics_adapter_scaler_errorsScaledObject Expander errors grouped by each trigger in, keda_metrics_adapter_scaler_metrics_value from ScaledObject Of each trigger in the KEDA The index value of the retractor. In this case ,ScaledObject zapier-worker-celery tell KEDA Extend On the following triggers zapier-worker-celery Deployment of . This monitoring and alarm setting helps us master the information from KEDA Any errors in the controller and extender . Why had climate change not been proven beyond doubt for so long? When there is a need to setup autoscaling in the kubernetes cluster, in response to CPU and Memory utilization, it is pretty easy to set up as both metrics are supported metric by Horizontal Pod Autoscaler(HPA).

This will generate the necessary artifacts ExternalSecretexternal-secrets controller ,https://github.com/external-secrets/kubernetes-external-secrets By getting from Vault[9] Get secrets from , From a ExternalSecret Object Kubernetes Secret)TriggerAuthenticationsScaledObject, Used to configure For services KEDA Automatic scaling . Monitoring principles and available metrics are mostly relevant when Prometheus and Grafana are used.

It provides event driven scale for any container running in Kubernetes GitHub. I was originally built by SoundCloud and then handed over to CNCF for maintenance and further development. For now KEDA supports 36 different scalers my example is. How To Use Css To Set A Radial Gradient 'Overlay' To A Div? Use the queue metrics gathered in prometheus to scale a pod based on Rabbitmq is clustered to the namespace and is on version 3.7.17. You can see that the current Replica count is 1 since the metric value is under target. Making statements based on opinion; back them up with references or personal experience. There is a potential solution by collecting RabbitMQ metrics in Prometheus, creating a custom metrics server, and configuring HPA to use these metrics. The entire autoscaling mechanism is based on metrics that represent the current load of an. Generally speaking , More tasks lead to more processing , Produce more CPU Usage quantity , Finally trigger the automatic expansion and contraction of our working device . Keep track of all key RabbitMQ. and once there are too much to tell k8s to autoscale?

Monitoring allows results processes and. The Custom Pod Autoscaler Framework is a way to allow people to create and use custom scalers similar to the Horizontal Pod Autoscaler in Kubernetes.

Autoscaler allows to scale an application using Rabbit MQ length as a metric. KEDA Is a single purpose lightweight component , Can be added to any Kubernetes In the cluster .KEDA By extending the Horizontal Pod Autoscaler[5], And according to the scaler Provide external indicators , stay Kubernetes All automatic scaling and reloading are completed in .

We use it in Kubernetes Start the private of the service on Helm chart in , We have added a pair based on KEDA Support for automatic scaling .

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Basic setup of HPA based on CPU utilization you.

These messages are then consumed by a NodeJS worker.

After some thorough search I got to know about Prometheus Adapter and its role in the architecture.

Because of our worker From many RabbitMQ The host reads messages from the queue , So we need to base on multiple RabbitMQ The ready message of the queue on the host is extended .

Gets the messages queue on RabbitMQ for the current deployment's queue. It seems to work well , Except for some marginal situations . In our case, rabbitmqs management service collects metrics but they are not compliant for Prometheus. How To Make An Interactive Radar Chart In R Shiny?

We start by creating a golang web-server that publishes messages to a rabbitmq queue. I got to know about why we need to use Prometheus to use metrics, then I learnt about exporters and there role in this metric capturing setup. You can use docker-compose command to build the web-server and Worker node images as theyll be used in cluster. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. End user guest author Ratnadeep Debnath,Zapier Website Reliability Engineer. Kubernetes Horizontal Pod Autoscalers HPA definitely can help you to save a lot of money. Setting up Syslog Forwarding; Logging Formats; Metrics.

Autoscale a deployment based on a custom metric from prometheus RabbitMQ GitHub arielb135/HPAwithprometheusandRabbitMQ: Autoscale.

Find 18 ways to say MONITORING along with antonyms related words and example sentences at Thesaurus.com the world's most trusted free thesaurus.

To make things easy and save ourselves from writing manifest files, well use helm charts for deployment.

Monitoring is the systematic process of collecting analyzing and using information to track a programme's progress toward reaching its.

https://github.com/kubernetes-incubator/custom-metrics-apiserver, https://github.com/onfido/k8s-rabbit-pod-autoscaler, Code completion isnt magic; it just feels that way (Ep. RabbitMQ, Kubernetes : Messages in Queue not getting persisted between container restarts, even after an added volume, Dynamically creating pods with kubernetes by a queue, Autoscaling in GKE based on RabbitMQ Queue Size, Is "Occupation Japan" idiomatic?

A simple nodejs application that connects to rabbitmq queue anc consumes messages.

Above ScaledObject Medium rabbitmq Triggers use the of triggers authenticationRef Mentioned in TriggerAuthentication To certify rabbitmq host , by scaler collect rabbitmq Indicators of . You need to create a docker image with given Dockerfile and use deploy.yaml to create a service account and deployment.

We are slowly updating Zapier Application to use KEDA. The adapter gathers the names of available metrics from Prometheus at By default in IBM Cloud Private HPA is enabled to auto scale based on CPU. Verify HPA.

To ensure that the system operates as expected , We use custom Prometheus Rule alerts when something goes wrong . If the metric readings are above this value and currentReplicas maxReplicas HPA will scale up. thank KEDA The team is lovely and helpful . be the number of messages within a specific a RabbitMQ queue.

This makes KEDA Become a flexible and safe choice , Can be combined with any number of other Kubernetes Run with an application or framework . We have the choice to create either custom or external metrics using this metrics adapter.

We use External type as Queue length is not monitored by Kubernetes and is not related to Kubernetes Objects. Verify exported metrics and deploy HPA 4. Our goal is to automatically scale the ConsumerApp based off of the if your HPA is able to get the appropriate Prometheus metrics. A Health check is the most basic aspect of monitoring.

other CNCF projects and actively contributes to some of these.

Where do the metrics come from? Since all objects talk to API-server, adapter exposes these metrics to API server. So are HPA is created and is ready to scale our worker deployment. Provides CMDLine Args and Env args, Go module to build a decisional tree from a json, Algorand-MultiSig - An open source repo that allows Algorand devs to easily spin up an application that enables multi-sig signing, Gojest is like jest(nodejs) in golang, Press the `F` key to focus on your first error, A Go application for Rust game servers operating with Pterodactyl, Compares recent (07.2022) GPUs in performance and price (German market), A CLI tool to check the status of URLs on webpages, Reverse proxy to ethereum nodes.

How we will achieve HPA for RabbitMQ Metric?

Now Prometheus server can pull metrics from this exporter.

Every event.

What we need to do now is to serve Helm Configure the auto scaling part in the value . In order to keep up with Zapier The changing workload in , We need to use message backlog backlog To extend the worker . k8srabbitpodautoscaler: An opensource project for autoscaling based on RabbitMQ queue size.

Prometheus Operator: The Prometheus Operator provides Kubernetes native deployment and management of Prometheus and related monitoring components. k8rabbitpodautoscaler will.

Deploy Custom Metrics Stackdriver adapter 2.

Share. Monitoring and KPIs for PreProvisioned VMware Tanzu RabbitMQ for VMs. You can check for different available exporter here. Once our application is up, we proceed with rabbitmq exporter and prometheus adapter. So, How can we scale on custom metric? Ideally , We hope that CPU and RabbitMQ Expand our worker.

Using Rabl To Handle Model Creation/Update? They can censor Merge these changes , And use it as 2.4.0 edition [8] Part of the release . monitoring definition: 1. present participle of monitor 2. to watch and check a situation carefully for a period of time. Connect and share knowledge within a single location that is structured and easy to search.

Path: Rabbitmq|Cluster|clustername |Nodes|nodename |Queues|. We use Helm[6] stay Kubernetes Deployed in the cluster KEDA. He spends a lot of time tinkering with Kubernetes and

Find centralized, trusted content and collaborate around the technologies you use most.

Unfortunately, Kubernetes native HPA does not support scaling based on RabbitMQ queue length out of the box.

If the worker is waiting I/O When you're free , Then we may have more and more news backlog , And based on CPU Your autoscaler may miss these messages . This situation can lead to communication congestion , And dealing with Zap Introducing delays in tasks . 464), How APIs can take the pain out of legacy system headaches (Ep.

There are three types of metrics available. I will continue building such project in order to learn more and more about it. Monitoring is a periodically recurring task already beginning in the planning stage of a project or programme. rev2022.7.20.42632. organization. Key.

We use a kube-prometheus-stack chart by prometheus-community. Announcing the Stacks Editor Beta release!

The architecture behind Zapier's Zap History pages. We are collecting 2 metrics, http_request_total and request_status to monitor number of request on and status returned by each route respectively.

We start by deploying our Kube-prometheus-stack first.

The application consume messages from rabbitmq. I didnt know that Ill have to use Prometheus as a metric server cause rabbitmqs management image exposed the need metrics on /api/metrics route. Autoscaling is an approach to automatically scale up or down workloads based on the resource usage.

KEDA can.

Video courses designed to help you become a better Zapier user.

How to auto-scale Kubernetes Pods based on number of tasks in celery task queue? You can create a Kubernetes HPA in just one. We are Python Did a lot of Blocking I/O[3] We were using the Python Compiling worker Event based loops are not used in . Partition Indicator.

Flow control limitting message rate on single queue. Calculates the amount of desired pods and scales the deployment if required. External: metrics that are not related to k8s Objects. Or maybe set the autoscale to follow message rate? Next deploy our RabbitMQ server, Web-Server and NodeJs worker using manifest files. An open source observability tool for Kubernetes applications, This script will find all of the configuration version left in TFC, Trivial proxy server that logs requests and responses to stdout, List Process In Table, Search and Filter by Name, PID, PPID, User. We use prometheus-rabbitmq-exporter helm chart to make deployment process easy. The 30 Fastest Growing Business Apps in 2018. It provides flexibility to set an interval of polling RabbitMQ queue and decides the number of message per pod. stay Zapier[1],RabbitMQ[2] yes Zap The core of processing .

Get Buffer From Rackspace Download Using Pkgcloud, Apexchart: Radar Chart Problem With Showing Xaxis Labels, Chart.Js Radar Pointlabel Options Not Working. To install Prometheus in our cluster we used the. besides ,KEDA There is also a very active and helpful contributor community .

KEDA It's based on Kubernetes Event driven autoscaler , Designed to make automatic scaling very simple . I can't predict the exact amount of cpu so I don't want to use it as autoscale limit, though I did set the prefetch to something that looks normal. I have used https://github.com/onfido/k8s-rabbit-pod-autoscaler for the config.

Scientifically plausible way to sink a landmass, Man begins work in the Amazon forest as a logger, changes his mind after hallucinating with the locals. You could either use Horizontal Pod Autoscaler with custom metrics, which need to be provided by some custom metrics API server (boilerplate: https://github.com/kubernetes-incubator/custom-metrics-apiserver).

Kubernetes has a wonderful feature called horizontal pod autoscaling that allows scaling of pods in your deployment based on the load that. HPA is commonly used with metric like CPU or Memory to scale our pods.

Well email you 1-3 times per weekand never share your information.

How To Move Messages From One Queue To Another In Rabbitmq, How To Render Rabl Template With Status Code Rails +3, Format For Connecting To Rackspace Via Cyberduck Cli. However, this is a lot of work and why reinvent the wheel when theres KEDA. But the problem is HPA doesnt do scaling directly on a custom metric. We've been Kubernetes Installed in cluster KEDA, And start choosing to use KEDA Auto scale . Based on a few parameters both in the configuration and the message received the exchange will decide on the right target queue for the message.

Is there a way to follow the number of messages in the queue,

This means that we could have a fleet of workers idling on blocking I/O with low CPU profiles while the queue keeps growing unbounded, as low CPU usage would prevent autoscaling from kicking in. John was the first writer to have joined golangexample.com. Deploying the Custom Metrics Adapter; Deploying an application with scale your Google Kubernetes Engine GKE workloads based on metrics available in.

Kubernetes Horizontal Pod Autoscalers HPA definitely can help you to save Kubernetes Workers Autoscaling based on RabbitMQ queue size. Prometheus and Stackdriver exporters 3.

I tried all three kinds of HPA, Resource,Custom and External and understood when to use which type. In this article, I will show you how to scale your Kubernetes deployment in response to change in a load of your RabbitMQ queue. He spent a lot of time studying Kubernetes And others CNCF project , And actively participate in some of these projects . Node metrics; Queue metrics; Clusterwide metrics Prometheus and Grafana are one highly recommended option. Get productivity tips delivered straight to your inbox. This seems like it would be a. I am trying to follow this guide https://nuvalence.io/buildingak8sautoscalerwithcustommetrics/ to enable autoscaling based on rabbitmq. Most of the service does not support Prometheus metrics out of box and need a middleware to do so.

Here we have created a deployment role with required deployment access of your k8 cluster.

KEDA provides an autoscaling infrastructure that allows you to very easily autoscale your applications based on your criteria. He is a passionate advocate of open source technology throughout the organization .

Rabbitmq: Does Unbinding Queues From Exchanges Affect Chartjs 3.5.0 Radar Chart Converting The Labels To Images. I wasn't able to find much content on this which didn't involve using an external source such as StackDriver. The metrics-agent collects allocation metrics from a Kubernetes cluster system and sends the metrics to cloudability, A service that listens to the Kubernetes API server and generates metrics about the state of custom resource objec, Instant Kubernetes-Native Application Observability, Discover expired TLS certificates in the services of a kubernetes cluster, A collactz conjecture service running in kubernets, A Kubernetes custom controller written in GO, Application for managing Kubernetes installations in Proxmox VE, A simple tool to see the status of Kubernetes cluster setup with hetznerctl / utopia-planitia.

Basing your HPA off those metrics alone could actually cause more harm than good. keda_metrics_adapter_scaled_object_errorsScaledObject error , for example ,scaler error ,TriggerAuthentication Lack of secrets , Need to expand to the largest copy, etc . Stay informed on health and performance by monitoring global connections consumers queues and much more. These metrics are exposed by. Or use a custom autoscaler (probably outdated: https://github.com/onfido/k8s-rabbit-pod-autoscaler). Ratnadeep Debnath yes Zapier A website Reliability Engineer .

However , This is a lot of work , When there is KEDA[4] When , Why start a new stove . Luckily Kubernetes allows you to create custom metrics. The metrics reported provide an overview of the performance of the queues in each cluster node. So you either provide the metrics to HPA or you run some application that has the metrics and sends scaling requirements to the kubernetes API. Hire a Zapier Expert to help you improve processes and automate workflows. Now the final setup is to create our HPA. Ask questions, share your knowledge, and get inspired by other Zapier users. Prerequisites. Kubernetes Autoscaling in Production: Best Practices for Cluster in and out based on demand efficiency and a number of other metrics. I'm mentioning RabbitMQ but that's just an example. https://kubedex.com/autoscaling/. A basic knowledge of Red Hat.

A.

What is the metrics registry?

Monitoring medicine the observation of a disease condition or one or several medical parameters over time Baby monitoring Biomonitoring of toxic chemical. For a long time, we scaled with CPU-based autoscaling using Kubernetes native Horizontal Pod Autoscale (HPA), where more tasks led to more processing, increasing CPU usage, and triggering our workers' autoscaling. A book on rust data structures and algorithms, It is difficult to observe http / 2 traffic, but ebpf can help, mysql_ Help command / generic search / help usage (official DOC), mysql_ Permission assignment / user and host authorization / user permission view, Automatic scaling based on CPU and rabbitmq, When pod Of CPU The utilization rate is 82%, When rabbitmq-1 In the host celery Queued Ready The number of messages is 180 Stripe time, When rabbitmq-2 In the host celery Queued Ready The number of messages is 180 Stripe time, KedaMetricsServerDown When keda-operator-metrics-server Downtime 1m Is triggered by, KedaScalerErrorsHigh When keda_metrics_adapter_scaler_errors_total > 0 by 1m Is triggered, KedaScaledObjectErrorsHigh When keda_metrics_adapter_scaled_object_errors > 0 by 1m Is triggered, up{job=keda-operator-metrics-apiserver} This means KEDA Whether the service is started and running.

kubernetes workers autoscaling based on rabbitmq queue size
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