> 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/stream-sizing.md). # Stream sizing When considering sizing for Stream it is important to understand that the traffic mix at customer sites varies widely. Some customers have traffic mixes that skew towards larger flows (think file transfers), and some will skew towards smaller flows. Performance will be lower when the traffic mix skews towards smaller flows as there will be more metadata to process. The below are guidelines for average traffic mixes and should not be considered absolute. Throughput refers to the amount of traffic observed by Sensors that forward metadata to the Vectra platform. **Virtual Appliances:**
Hypervisor / CloudVM TypeCoresMemoryStorage~ Performance
VMwarevSphere 6.5 or later28 GB100 GBUp to 2.5 Gbps
VMwarevSphere 6.5 or later48 GB150 GB2.5 to 5 Gbps
VMwarevSphere 6.5 or later816 GB150 GB5 to 10 Gbps
VMwarevSphere 6.5 or later1664 GB150 GB10 to 20 Gbps
Hyper-VWindows Server 2016 w/ HW v8 or higher28 GB100 GBUp to 2.5 Gbps
Hyper-VWindows Server 2016 w/ HW v8 or higher48 GB150 GB2.5 to 5 Gbps
Hyper-VWindows Server 2016 w/ HW v8 or higher816 GB150 GB5 to 10 Gbps
Hyper-VWindows Server 2016 w/ HW v8 or higher1664 GB500 GB10 to 20 Gbps
KVMStandard PC (Q35 + ICH9, 2009)28 GB100 GBUp to 2.5 Gbps
KVMStandard PC (Q35 + ICH9, 2009)48 GB150 GB2.5 to 5 Gbps
KVMStandard PC (Q35 + ICH9, 2009)816GB150 GB5 to 10 Gbps
KVMStandard PC (Q35 + ICH9, 2009)1664 GB500 GB10 to 20 Gbps
AWSc5.xlarge48 GB50 GBUp to 5 Gbps
AWSc5.2xlarge816 GB50 GB5 to 10 Gbps
AWSc5.4xlarge1632 GB50 GB10 to 20 Gbps
AzureStandard_DS4_v2828 GB50 GBUp to 10 Gbps
AzureStandard_DS5_v21656 GB50 GB10 to 20 Gbps
GCPe2-standard-4416 GB50 GBUp to 5 Gbps
GCPe2-standard-8832 GB50 GB5 to 10 Gbps
GCPe2-standard-161664 GB50 GB10 to 20 Gbps
**Vectra M Series Physical Appliances:** The M series physical appliances can support up to \~75 Gbps of throughput. {% hint style="info" %} **Please Note:** * Contact your account team or Vectra support for guidance on special situations, abnormal traffic mixes, or throughput needs outside of what is documented above. * Vectra recommends that Stream VMs are configured to use storage local to the hypervisor and are not stored on a SAN. Stream VMs require extremely high throughput from their disk storage and this throughput cannot normally be sustained by SAN systems without impact to other SAN users. * Please see [VMware deployment details and considerations](/deployment/ndr-virtual-cloud-appliances/vmware-vsensor/vmware-deployment-details-and-considerations.md) for guidance on supported CPUs, storage/SANs, networking requirements, vMotion, Enhanced vMotion compatibility, and unsupported hypervisors. While Sensor and VMware specific, this article applies to Stream VMs as well. The general guidance in the article also applies to Hyper-V and KVM deployments. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.vectra.ai/deployment/stream/stream-sizing.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.