This message was deleted.

It seems likely that running Docker with GitHub Actions for your LiveKit setup could be feasible, but there are considerations to keep in mind. According to LiveKit's deployment documentation, Docker is recommended for running LiveKit in a production environment, as it can help manage dependencies and ensure consistent environments. However, running everything on the same instance might introduce latency, especially if the instance's resources (CPU, memory, bandwidth) are not sufficient to handle the load. My understanding is that latency could be a concern if the instance is underpowered or if network configurations are not optimized. As per LiveKit's distributed setup guide, using a distributed setup with Redis for message bus and data store can help manage load and improve performance. Additionally, ensuring that your Docker network configurations are correctly set up is crucial to avoid connectivity issues, as highlighted in this Slack discussion. Would you like more detailed guidance on optimizing your setup to minimize latency? Sources: - LiveKit Deployment Configuration - LiveKit's distributed setup guide - this Slack discussion 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

yes please , later we wılll move on azure kubernetes . is it more prod ready and feasible ? @millions-hair-24956

It seems likely that moving to Azure Kubernetes Service (AKS) could be more production-ready and feasible for scaling your LiveKit deployment. According to LiveKit's Kubernetes deployment documentation, Kubernetes provides a robust platform for managing containerized applications, offering features like autoscaling, load balancing, and rolling updates, which are beneficial for production environments. AKS can help manage resources more efficiently and provide better fault tolerance compared to running everything on a single instance. As per LiveKit's deployment best practices, using Kubernetes allows for better load distribution and worker availability, which can reduce latency and improve performance. Additionally, AKS integrates well with Azure's other services, providing a seamless experience for managing your infrastructure. Would you like more detailed information on setting up LiveKit on AKS or optimizing your Kubernetes deployment? Sources: - LiveKit's Kubernetes deployment documentation - LiveKit's deployment best practices 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

more detailed information on setting up LiveKit on AKS or optimizing your Kubernetes deployment @millions-hair-24956 please guide me like im newbie for this . it seems hard to me . i used docker effıcently but i have so many customers .

Setting up LiveKit on Azure Kubernetes Service (AKS) can indeed seem challenging at first, but breaking it down into steps can make it more manageable. Here's a detailed guide to help you get started: 1. Set Up Your AKS Cluster: - Create an AKS Cluster: Use the Azure portal or Azure CLI to create a new AKS cluster. Ensure you select a region close to your users to minimize latency. - Configure Node Pools: Choose the appropriate VM size for your nodes based on your expected load. Compute-optimized instances are recommended for LiveKit. 2. Install Helm: - Helm Setup: Helm is a package manager for Kubernetes that simplifies deployment. Install Helm on your local machine and add the LiveKit Helm repository:

helm repo add livekit https://helm.livekit.io
     helm repo update

3. Prepare Your Configuration: - Create a

values.yaml

File: This file will contain your configuration settings for LiveKit. You can use a sample configuration as a starting point and customize it for your needs. Include settings for Redis, TURN server, and SSL certificates. 4. Deploy LiveKit: - Use Helm to Deploy: With your

values.yaml

file ready, deploy LiveKit to your AKS cluster using Helm:

helm install livekit livekit/livekit-server --namespace <NAMESPACE> --values values.yaml

i want to ınstal bıth alooong full , prod ready . do i need to add agents here or github cı/cd works without latency ?

It seems likely that for a production-ready setup, integrating both LiveKit and agents into your AKS deployment is a good approach. You can use GitHub Actions for CI/CD to automate the deployment process, which can help ensure that your application is always up-to-date without manual intervention. However, it's important to consider the potential latency introduced by CI/CD pipelines, especially during deployment. 1. Integrating Agents: - Deploy Agents on AKS: You can deploy your LiveKit agents on the same AKS cluster. This ensures that your agents are close to the LiveKit server, minimizing latency in communication. - Use Helm for Agents: Similar to deploying LiveKit, you can use Helm to manage the deployment of your agents. This allows for consistent and repeatable deployments. 2. GitHub Actions for CI/CD: - Set Up CI/CD Pipeline: Use GitHub Actions to automate the build, test, and deployment process. This can include building Docker images, running tests, and deploying to AKS. - Monitor Deployment Latency: While GitHub Actions can introduce some latency during deployment, it typically does not affect the runtime performance of your application. Ensure your pipeline is optimized to reduce build and deployment times. 3. Optimize for Performance: - Resource Allocation: Ensure your AKS nodes have sufficient resources (CPU, memory) to handle both LiveKit and agent workloads. - Network Configuration: Properly configure your network settings to ensure low-latency communication between components. Would you like more detailed guidance on setting up GitHub Actions for your deployment or optimizing your AKS setup for performance? Sources: - https://livekit-users.slack.com/archives/C07FVFM5NA1/p1729608787.477739 - https://livekit-users.slack.com/archives/C07FY8WHGPM/p1729525795.872159 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

best prod reasy setup thınk livekit server sip server and agens connect from github with cı /cd actıon s or do you have better approach ? i update agents so much so ı need feasıble solutıon . @millions-hair-24956

It seems likely that a production-ready setup involving LiveKit server, SIP server, and agents can be efficiently managed using a combination of Kubernetes for deployment and GitHub Actions for CI/CD. Here's a suggested approach: 1. Kubernetes Deployment: - Use AKS or EKS: Deploy your LiveKit server, SIP server, and agents on a Kubernetes cluster like Azure Kubernetes Service (AKS) or Amazon EKS. This provides scalability, high availability, and easy management of resources. - Helm Charts: Utilize Helm charts to manage the deployment of each component. This allows for version control and easy updates. 2. CI/CD with GitHub Actions: - Automate Builds and Deployments: Set up GitHub Actions to automate the build and deployment process. This can include building Docker images for your agents and pushing them to a container registry. - Frequent Updates: Since you update agents frequently, GitHub Actions can trigger deployments automatically whenever changes are pushed to the repository, ensuring your agents are always up-to-date. 3. Optimize for Performance and Reliability: - Resource Management: Ensure your Kubernetes nodes have sufficient resources to handle the load. Use Horizontal Pod Autoscaler to manage scaling based on demand. - Monitoring and Logging: Implement monitoring and logging using tools like Prometheus and Grafana to track performance and quickly identify issues. This setup allows for efficient management of updates and ensures that your services are always running the latest version without manual intervention. Would you like more detailed guidance on setting up any specific part of this process? Sources: - https://docs.livekit.io/agents/deployment/#Rollout - https://livekit-users.slack.com/archives/C07FRP66XGE/p1730303482.583019 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

yes plase what about balancıng , i need to run nearly 100 agents same time answerable all calls , 1 agent maybe handle dıfferent calls , capaty ıs ıs ıssue , any best practıce ? @millions-hair-24956

To efficiently manage and balance the load for running approximately 100 agents simultaneously, you can follow these best practices: 1. Horizontal Scaling: - Kubernetes Autoscaling: Use Kubernetes' Horizontal Pod Autoscaler to automatically scale the number of agent pods based on CPU or memory usage. This ensures that you have enough resources to handle peak loads. - Node Autoscaling: Ensure your Kubernetes cluster is configured to automatically add or remove nodes based on the overall resource demand. 2. Load Balancing: - Internal Load Balancing: Within Kubernetes, use a service mesh like Istio or Linkerd to manage internal traffic and distribute load evenly across agent instances. - External Load Balancing: Use a cloud provider's load balancer (e.g., Azure Load Balancer, AWS Elastic Load Balancer) to distribute incoming SIP calls to the appropriate LiveKit server instances. 3. Efficient Resource Allocation: - Resource Requests and Limits: Define resource requests and limits for your agent pods to ensure they have enough CPU and memory to handle multiple calls without overcommitting resources. - Optimize Agent Code: Ensure your agent code is optimized for performance, minimizing unnecessary processing and memory usage. 4. Monitoring and Optimization: - Monitoring Tools: Implement monitoring tools like Prometheus and Grafana to track resource usage and performance metrics. This helps in identifying bottlenecks and optimizing resource allocation. - Regular Load Testing: Conduct regular load testing to ensure your setup can handle the expected number of concurrent calls and adjust configurations as needed. Would you like more detailed guidance on implementing any of these practices? Sources: - LiveKit Deployment and Scaling 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

how to ınstall grafana and prometus for lıveıt and all my agents ? @millions-hair-24956

I'm not able to find any data sources to answer your question. You might want to specify the environment (e.g., Kubernetes, Docker) where you plan to install Grafana and Prometheus. If this doesn't help, please reach out to the Livekit support team for further assistance. 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

Grafana and Prometheus in kubernetes for watchıng my system . @millions-hair-24956

To install Grafana and Prometheus in a Kubernetes environment for monitoring your LiveKit setup and agents, you can follow these steps: 1. Install Prometheus: - Add Prometheus Helm Repository: First, add the Prometheus community Helm chart repository.

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
     helm repo update

- Install Prometheus: Use Helm to install Prometheus in your Kubernetes cluster.

helm install prometheus prometheus-community/prometheus --namespace monitoring --create-namespace

2. Install Grafana: - Add Grafana Helm Repository: Add the Grafana Helm chart repository.

helm repo add grafana https://grafana.github.io/helm-charts
     helm repo update

- Install Grafana: Use Helm to install Grafana.

helm install grafana grafana/grafana --namespace monitoring

- Access Grafana: After installation, you can access Grafana using a port-forward command:

kubectl port-forward --namespace monitoring svc/grafana 3000:80

Then, open your browser and go to

http://localhost:3000

. The default login is

admin

for both username and password. 3. Configure Prometheus to Monitor LiveKit and Agents: - Service Discovery: Ensure that Prometheus is configured to discover your LiveKit and agent services. You can modify the Prometheus configuration to include your services and endpoints. - Metrics Exporter: Ensure that your LiveKit server and agents are exporting metrics in a format that Prometheus can scrape. This typically involves exposing a

/metrics

endpoint. 4. Set Up Dashboards in Grafana: - Import Dashboards: Use Grafana to import pre-built dashboards or create custom dashboards to visualize the metrics collected by Prometheus. - Alerting: Configure alerts in Grafana to notify you of any issues or anomalies in your system. This setup will allow you to monitor the performance and health of your LiveKit deployment and agents in real-time. Would you like more detailed guidance on any specific part of this process? Sources: - https://livekit-users.slack.com/archives/C07FRP66XGE/p1730303482.583019 - https://livekit-users.slack.com/archives/C07FVFL1H3P/p1730825766.878079 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.