A 24/7 YouTube stream can run from a Google Cloud VM in Mumbai or Delhi using an encoder that sends RTMP or RTMPS to YouTube. Google’s managed Live Stream API is a separate route: Mumbai is listed as supported for the API, while Delhi is not, and an active API channel may be restarted after 24 hours.
Your choice is mainly about how much of the broadcast you want Google to manage versus how much control you want over the encoder and its recovery. Neither a region name nor a cloud service guarantees stream quality; test the full path, and design for interruptions before you depend on it overnight.
Choose between a VM encoder and the Live Stream API
With a self-managed Compute Engine VM, you run an encoder such as FFmpeg or another RTMP-capable programme and point it at YouTube’s ingest URL and stream key. You decide how the source loops, how the encoder is supervised and what it should do after a failure. In return, you are responsible for keeping the input available, checking logs, monitoring the process and restoring the broadcast when something stops.
Google’s managed Live Stream API is a different product, not simply a VM with an encoder already installed. It accepts SRT or RTMP input, processes that input into HLS or DASH, and can write output files to Cloud Storage. Its remote RTMP distribution feature is relevant when you want to pass the resulting stream to YouTube. That workflow involves configuring the API’s input, channel, storage and distribution; it is not the same as copying a YouTube key into an encoder on a VM.
The API can be useful when its managed ingest, transcoding and distribution model matches your workflow. It also introduces product-specific location constraints, active-channel billing and a restart condition after 24 hours. A VM gives you more direct control of the encoder process, but that control comes with operational work. You need to select a VM shape based on the codec, resolution and encoding load, then test it with your actual content; there is no universal machine size established by the regional availability information.
| Question | Self-managed VM encoder | Live Stream API |
|---|---|---|
| Where can you run it in India? | Compute Engine lists Mumbai and Delhi | The checked API location list includes Mumbai, not Delhi |
| What handles encoding? | You configure and operate the encoder | The API accepts an input and can transcode it into supported outputs |
| Who owns recovery? | You supervise the encoder and source, and implement restart behaviour | You monitor the API workflow and plan around possible channel restart after 24 hours |
| How does it reach YouTube? | Encoder sends to YouTube using the Studio URL and key | Configure remote RTMP distribution to YouTube |
| What should you cost? | VM runtime and other selected resources | Active channel time and outputs, along with any related resources |
For a single pre-recorded loop, a VM may be easier to reason about if you already know how to operate an encoder and want to control its process. If you specifically need managed transcoding or API-based channel workflows, the API may fit better, provided its supported location and restart behaviour work for your design. For a broader view of a hosted playout approach, see how a cloud playout service can run a continuous YouTube stream.
Select Mumbai or Delhi for a VM
Compute Engine has Indian regions in Mumbai (asia-south1) and Delhi (asia-south2). Either can host a self-managed encoder VM, subject to the resources and machine types available for your project. That does not mean either region is always the right choice: you should consider where your source material sits, where your viewers are, what other cloud resources your workflow needs, and what the chosen machine can sustain.
If your files or supporting services are already in one region, keeping the VM nearby can simplify the path between them. Google’s location guidance also recommends considering the location of the input, channel and storage when working with the managed API. For a VM, the same practical question applies even though you are not creating those API resources: extra copying or transfer steps can complicate a workflow and make failures harder to diagnose.
Do not choose Mumbai solely because it is supported by the Live Stream API, or Delhi solely because it is a Compute Engine region. Regional availability is a product fact, not a prediction of viewer playback quality, encoder stability or YouTube ingest performance. Configure the encoder, send a representative test and inspect stream health from the actual account and source you intend to use.
The encoder’s work matters more than the region label. A VM must decode or read the source, encode it at the selected settings and sustain outbound traffic. Test the actual resolution, frame rate, audio and motion level. A quiet devotional image with a continuous music bed and a news loop with frequent cuts do not impose identical workloads. The test should use your real loop or a faithful sample, rather than assuming that a machine which starts the encoder will necessarily run it comfortably for days.
Check supported regions for the Live Stream API
Google publishes a supported-location list for the Live Stream API. In the India entries checked for this article, Mumbai (asia-south1) appears on that list. Delhi (asia-south2) appears in the Compute Engine region list, but not in the API’s supported-region table. Keep those lists separate when planning: being able to create a VM in a region does not make that region available for every Google Cloud product.
Check the Live Stream API location documentation immediately before creating resources. The list can change, and the resources’ locations cannot be changed after creation. Check the locations of the input endpoint, channel and storage bucket together, rather than creating one resource first and discovering later that the rest of the intended design must sit elsewhere.
A Mumbai API deployment can still be a poor fit if your workflow depends on an unsupported resource location, a particular distribution path or an operational arrangement you cannot monitor. Conversely, a Delhi VM is not ruled out for a self-managed encoder just because the managed API location list does not include Delhi. The product you are deploying determines which location list matters.
Google’s API quota documentation also describes up to 10 simultaneously running channels and up to 20 inputs as default regional allocation, subject to project quotas and possible changes. Treat these as API allocation details, not as an encoder capacity estimate for a VM. If you plan several parallel channels, check the project’s current quotas rather than assuming the defaults will fit.
Connect an encoder to YouTube ingest
For either a VM encoder or an API remote-distribution workflow, the YouTube side begins in YouTube Studio. Open Create, then Go Live, and create or schedule a stream in Live Control Room. YouTube provides a server URL and stream key for an external encoder. Keep the key private: anyone who obtains it may be able to send content to that broadcast. First-time live-stream activation can take up to 24 hours, according to YouTube, so do not leave account activation until the planned launch night.
Use YouTube’s current encoder settings guidance for the target format. For RTMP(S), YouTube’s recommendations include H.264 video, constant bitrate (CBR), and a two-second keyframe interval; do not exceed four seconds. YouTube recommends RTMPS, which encrypts the stream to and through Google’s servers. Prefer it when the encoder supports it and use the server URL shown in Studio rather than copying an ingest address from an old configuration.
Bitrate is a setting to match to your resolution and frame rate, not a proxy for quality on its own. YouTube’s H.264 guidance lists 5 Mbps as a minimum and 14 Mbps as recommended for 1080p30; for 1080p60 it lists 6 Mbps minimum and 17 Mbps recommended. These are YouTube encoder recommendations, not a guarantee that a given VM or source connection can sustain them. The source feed and VM’s outbound capacity both need headroom for the configured rate.
For a basic FFmpeg workflow, the important operational pieces are the input, video and audio encoding settings, the destination URL and protected key, plus a loop or input-recovery strategy. Do not place the stream key in a public script, screenshot or shared log. If you use a graphical encoder, save a known-good profile and document where its credentials are stored. In either case, record how you can stop and restart the encoder without accidentally creating a second broadcast or sending to the wrong scheduled event.
If you are looping a file, check that its beginning and end join as intended and that the audio does not click or fall silent at the boundary. The file’s metadata or unusual timestamps can affect playback in some workflows; this guide to removing metadata before a YouTube loop stream is relevant when you are diagnosing a file-related issue. It is not a substitute for testing the encoded output in Live Control Room.
Plan recovery for the 24-hour API constraint
For the Live Stream API, build the 24-hour condition into the architecture. Google Cloud’s quotas and limits documentation says that after 24 hours in any streaming state other than STOPPED or STOPPING, a channel may be restarted. “May” matters: do not make the design depend on one uninterrupted API session lasting beyond that point, and do not assume the exact viewer-visible behaviour without testing it.
A production plan needs to notice the relevant channel or distribution state, determine whether the output is still reaching YouTube, and restore the intended path if the restart interrupts it. Decide who or what checks those signals, what alert reaches an operator, and what the operator should do. A restart plan is incomplete if it only says “restart the channel” but leaves unclear whether the input is still available, the YouTube event is live, or the distribution destination is correct.
For a VM encoder, the API’s specific 24-hour channel condition does not apply, but a continuous process still needs recovery. The VM can remain available while the encoder exits, the input file becomes unreadable, a network connection drops, disk space runs low or credentials are changed. Use process supervision or another deliberate restart mechanism, and alert on failure rather than relying on someone to notice a silent stream. Automatic restarts can help, but test what happens when the encoder repeatedly fails so that a broken configuration does not create an endless cycle without useful diagnosis.
There is also a YouTube event and archive consideration. YouTube says broadcasts under 12 hours are automatically archived; that statement does not establish that one 24-hour broadcast will produce a complete archive. If a complete replay is important, check YouTube’s current guidance and verify the result in a test. You may decide to schedule shorter programme blocks, but account for what viewers will see during transitions and how you will restart the ingest.
If your recurring problem is keeping a file-based loop alive while your own computer is off, a hosted route such as StreamNeo removes the need to maintain a local encoder process, leaving you to prepare the file and YouTube channel and check the resulting broadcast. It does not change YouTube’s account requirements or make content rights and stream health irrelevant.
Test the continuous stream before relying on it
A short test should exercise the same path you expect to use at night: the real source file or feed, the chosen region, encoder settings, YouTube destination and monitoring. Start the encoder, check the preview in Live Control Room, then confirm that the stream is live as intended. Look at the stream-health indicators and listen to the audio instead of treating a running process as proof that viewers receive a good signal.
For a VM, test the loop boundary, source restart and encoder restart. Simulate a dropped input or stopped process if you can do so safely, then confirm that your alert fires and recovery does not require a person to guess what happened. Record the useful evidence: timestamps, process logs, YouTube health messages and what the viewer saw. That makes it easier to distinguish a source problem from an ingest or configuration problem on a later night.
For the API, test a channel restart and its effect on the remote RTMP output and YouTube event in a non-critical window. Confirm which component needs a manual action, which transitions are automated and whether the alert arrives where someone will see it. Since the API may restart an active channel after 24 hours, a test that ends well before that point cannot validate the recovery procedure. Do not stage the first recovery test during a devotional programme, local news loop or other broadcast that cannot tolerate an avoidable interruption.
The source itself deserves a separate check. A long file can contain a black frame, silence or an unintended slate that only becomes obvious after a loop. For a prerecorded lesson, compare the source and encoded preview, and use the troubleshooting advice in this guide to avoiding repeated black frames in a 24/7 lesson stream. If you stream music, verify that the audio continues cleanly through the entire loop and that you have the necessary rights; a cloud location does not settle a content claim.
Run the test with representative movement and sound. A static image with quiet audio may not reveal encoder load or audio problems that appear in the actual programme. If you change the machine type, encoding profile, source file or output route, repeat the test; a change in one component can alter the behaviour of the whole chain. There is no single test length that proves a stream will never fail, so decide what failure modes matter and exercise those deliberately.
Choose an architecture for your operating needs
Write down what must continue when nobody is at the keyboard. For a small devotional station, that might mean a single audio-and-image loop, an alert if the audio disappears, and a documented way to restart the broadcast. For a news loop, it may mean a named person checks the output before each scheduled content change. Those needs often tell you more than a simple preference for “managed” or “cloud VM”.
Use a VM when you want to control the encoder and source loop directly, can maintain the operating system and process, and are prepared to implement and test monitoring and recovery. Choose between Mumbai and Delhi using the VM workflow’s location needs and the resources you will use; do not infer quality from geography alone. Keep a backup of the encoder profile and a clear, private way to retrieve the stream key.
Consider the Live Stream API when its managed input, transcoding and distribution workflow fits your needs and its supported location is acceptable. For an India deployment based on the checked list, that means planning around Mumbai rather than assuming Delhi is available. Model the active-channel period and number of outputs when estimating costs, and include the 24-hour restart case in the operating procedure. If your team cannot monitor or respond to that workflow, its managed components do not remove the need for a recovery owner.
Cost cannot be reduced to one transfer line or a generic hourly estimate. Google lists VM-to-YouTube transfer among specific Google-product transfers with no charge, but that does not make VM runtime, disks, source storage, logging or other selected resources free. For Live Stream API, channel charges accrue while a channel is active, and an active channel can incur charges even without input; remote distribution streams are additional outputs. Check current pricing for your configuration and include how long channels remain active, output count, resolution and codec in the calculation.
For another cloud-region comparison aimed at Indian devotional channels, see the Azure VM alternatives discussion. The useful comparison is operational: what you must configure, what you must observe, where your resources can be placed and how you will recover. No provider or region should be treated as a guarantee of availability or viewer experience.
Before committing, compare the operating options on the pricing page. When the file and channel are ready, start free — 24-hour trial, no card.
FAQ
How do I stream 24/7 on YouTube from Google Cloud?
Run an RTMP- or RTMPS-capable encoder on a Compute Engine VM, then use the server URL and stream key supplied in YouTube Studio. Configure a loop or continuous input, supervise the process, and test alerts and recovery before relying on it. A managed Live Stream API workflow is also possible, but its channel restart condition needs a deliberate plan.
Which Google Cloud region in India should I use for a YouTube stream?
For a self-managed VM encoder, Compute Engine lists Mumbai and Delhi, so choose based on the location of your resources and the workflow you can test. The Live Stream API’s checked India location list includes Mumbai but not Delhi. Do not use region availability as a guarantee of stream quality.
Can I use a Google Cloud VM as a YouTube live encoder?
Yes. You can run an encoder on a VM and connect it to the YouTube ingest URL and key from Studio. You still have to configure the encoder, keep its source available, monitor it and handle failures; Google does not prescribe a universal VM size for every stream.
Will a Live Stream API channel run uninterrupted beyond 24 hours?
Do not plan on one uninterrupted API session beyond 24 hours. Google says an active channel may be restarted after 24 hours in a streaming state other than STOPPED or STOPPING. Build monitoring and recovery into the workflow and test what viewers see during the restart.