> For the complete documentation index, see [llms.txt](https://docs.vectra.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vectra.ai/deployment/stream.md). # Stream - [Introduction and requirements](https://docs.vectra.ai/deployment/stream/introduction-and-requirements.md): Introduction to Stream deployment, licensing steps, and connectivity requirements. - [Stream sizing](https://docs.vectra.ai/deployment/stream/stream-sizing.md): Sizing guidelines for Stream VMs and M-Series appliances. - [Preparing to deploy Stream](https://docs.vectra.ai/deployment/stream/preparing-to-deploy-stream.md): Download Stream images and collect deployment inputs, including Brain details and Sensor Registration Tokens (SRTs). - [Deployment](https://docs.vectra.ai/deployment/stream/deployment.md): Platform-specific Stream deployment guides as part of overall Stream deployment and configuration process. - [VMware Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/vmware-stream-deployment.md): Deploy Stream on VMware using an OVA via vCenter/vSphere or via the Brain CLI provisioning command. - [Hyper-V Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/hyper-v-stream-deployment.md): Deploy Stream on Hyper-V using the provided VHD and PowerShell deployment script. - [KVM Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/kvm-stream-deployment.md): Deploy Stream on KVM using the image tarball and \`vectra-stream.sh\`, with basic \`virsh\` troubleshooting tips. - [AWS Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/aws-stream-deployment.md): Deploying Stream in AWS environments using and image from the AWS Marketplace. - [Azure Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/azure-stream-deployment.md): Deploying Stream in Azure using a image from the Azure Marketplace. - [GCP Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/gcp-stream-deployment.md): Deploy Stream in GCP using \`gcloud infra-manager\` with aVectra-provided template and image shared to you from Vectra. - [M-Series Stream deployment](https://docs.vectra.ai/deployment/stream/deployment/m-series-stream-deployment.md): Quick-start steps to deploy Stream on a physical M-Series appliance, then pair and enable publishing. - [Initial CLI configuration](https://docs.vectra.ai/deployment/stream/initial-cli-configuration.md): Connect to the Stream CLI and configure static IP, gateway, DNS, and password changes if not using DHCP or changes are needed after initial deployment. - [Pairing Stream appliances](https://docs.vectra.ai/deployment/stream/pairing-stream-appliances.md): How to pair Stream appliances with your Vectra Brain appliance. - [Metadata filtering and publishing](https://docs.vectra.ai/deployment/stream/metadata-filtering-and-publishing.md): How to configure options for metadata filtering and the destination publisher of your choice. - [Publisher specific guidance](https://docs.vectra.ai/deployment/stream/publisher-specific-guidance.md): Instructions for specific publishers that you are using to receive Stream data. - [Elastic, Syslog, and Kafka](https://docs.vectra.ai/deployment/stream/publisher-specific-guidance/elastic-syslog-and-kafka.md): Details for Elastic, Syslog, and Kafka Stream publishers. - [ELK integration](https://docs.vectra.ai/deployment/stream/publisher-specific-guidance/elk-integration.md): Integrate Vectra Stream custom content with Elastic, Logstash, and Kibana deployments. - [Splunk integration](https://docs.vectra.ai/deployment/stream/publisher-specific-guidance/splunk-integration.md): This article is meant to be used by customers who will be integrating Vectra Steam metadata into their Splunk installation. --- # Agent Instructions This documentation is published with GitBook. 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