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Best Google Cloud VM Size for a 24/7 YouTube Channel in India

For relaying an already encoded stream, e2-standard-2 is a practical starting point in Mumbai or Delhi. Real-time encoding needs workload-specific testing, and the full 24/7 bill depends on region, disk, and network use.
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For a VM that only relays an already encoded stream, start with a Compute Engine e2-standard-2 in Mumbai or Delhi, then verify it against your actual continuous workload. It has 2 vCPUs and 8 GB of memory. If the VM must capture, compose, decode, or encode video in real time, there is no universally supported VM-size answer: benchmark the complete video pipeline before relying on it around the clock.

Choose the VM size by what it does

The important distinction is whether the instance forwards a finished video stream or processes video before sending it to YouTube. Google describes the E2 family as cost-optimized general-purpose machines, but that does not establish how a particular instance will perform with every encoder, format, and production workload. Google’s E2 machine-type documentation lists the available configurations and their resources.

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VM workload Starting point What to verify
Relay or stream copy: the video is already encoded and the VM forwards it without re-encoding e2-standard-2: 2 vCPUs and 8 GB memory CPU and memory use, sustained stream continuity, and whether the real ingest and upload paths remain stable
Software encoding, decoding, overlays, or other real-time video processing No universal size is established; test the exact workload Codec, resolution, frame rate, encoder settings, overlays, other processes, CPU headroom, and stream health
Capture and production, such as a camera or gameplay feed with overlays and audio Workload-dependent; the title does not specify enough to prescribe a size Every capture, composition, audio, and encoding task running on the instance

A small shared-core VM is not automatically a safer low-cost choice for an always-active stream process. Google’s E2 documentation says e2-small sustains 0.5 vCPU and e2-medium sustains 1 vCPU, although the guest sees two vCPUs. Do not judge these types by the guest-visible vCPU count alone; use one only after observing the actual workload.

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What e2-standard-2 does—and does not—tell you

For a relay, e2-standard-2 is a conservative starting point, not a performance guarantee. Run the stream with your actual source, software, and target output, and check that the CPU has headroom while the stream remains continuous. A workload that only forwards an encoded feed is materially different from one that also decodes, overlays, or re-encodes it.

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YouTube automatically transcodes live streams into multiple viewer output formats. That downstream service does not remove the work your own VM must do to capture, compose, or encode its outgoing feed. Keep the creator-side processing load separate from YouTube’s viewer-side distribution when sizing the machine. YouTube’s live streaming overview describes the platform workflow.

Set the stream target before estimating network capacity

YouTube’s live-encoder recommendations depend on codec, resolution, and frame rate. Its H.264 guidance includes these recommended bitrate ranges:

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Output YouTube-recommended H.264 bitrate range
720p at 30 fps 3–8 Mbps
1080p at 30 fps 5–14 Mbps
1080p at 60 fps 6–17 Mbps

These are YouTube encoder settings, not Compute Engine sizing benchmarks. Check the recommendation for your exact codec and output before planning bandwidth. YouTube Help advises: “Have enough bandwidth: The total bitrate that you’re streaming cannot exceed the amount of upload bandwidth available. Leave a bit of room (20% recommended).” It also warns that a connection disruption could break the stream. Treat the 20% as YouTube’s published operational guidance, not as a guarantee that a particular VM or network will be stable. YouTube’s live encoder settings and streaming tips cover bitrate and connection preparation.

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Pick an Indian region, then compare the real setup

Google lists E2 availability in both Mumbai (asia-south1) and Delhi (asia-south2). Choose between them based on where your stream source and operators are, and compare observed latency and service availability for your own setup. Regional availability alone does not show which location will deliver better latency or reliability for a particular channel. Google Cloud’s regions and zones list shows location availability.

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Estimate the full 24/7 cost, not just the VM rate

Google Cloud presents machine prices by region and consumption model and directs customers to its Pricing Calculator for estimates. Configure the region and billable resources you intend to use, and include 24/7 runtime, the boot disk, network use, and any attached resources. A VM hourly rate alone is not the total bill; without those choices and a billing date, a single all-in INR estimate would be misleading. Rates and currency conversion can change. Google Cloud’s Compute Engine pricing page links to the calculator.

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When a VM is the wrong tool for a prerecorded loop

If your goal is simply to keep uploaded prerecorded videos looping as a YouTube live stream, rather than to run a custom capture or encoding pipeline, StreamNeo is the first alternative to consider: it runs from the cloud, streams uploaded video at its original quality up to 4K 60fps for one flat price per slot, and offers the first day free.

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Or let it run in the cloud

With StreamNeo, upload a recording or build a playlist, add your YouTube stream key once, and go live. It loops uploaded videos from the cloud, so your computer and home connection do not need to stay on. It supports the uploaded quality up to 4K 60fps at one price per slot, and automatically recovers if YouTube drops the stream. The first day is free with no card required. Monthly pricing is $9.99 per month. Start your free day with StreamNeo.

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