For a single, already-encoded video that FFmpeg will loop and send to YouTube without re-encoding, start with an Oracle Cloud Infrastructure (OCI) VM.Standard.A1.Flex instance configured with 1 OCPU and 6 GB of memory. Treat that as a low-cost trial configuration, not a proven 24/7 production size: no workload-specific benchmark establishes how long it will sustain a particular stream. Test with your actual media and settings before relying on it continuously.
The key sizing question is whether FFmpeg copies the encoded streams or decodes and re-encodes them. Copying usually avoids the encoding workload; transcoding, filters, multiple simultaneous streams, or strict uptime targets call for measurement and potentially more resources. A1.Flex is Arm-based, so verify your operating system image and FFmpeg build support before deploying.
Which OCI instance should you start with?
For one pre-encoded video looped with FFmpeg stream-copy, a reasonable place to begin is VM.Standard.A1.Flex with 1 OCPU and 6 GB RAM. This is a starting allocation for a trial, not an Oracle recommendation, a measured FFmpeg benchmark, or a guarantee that the stream will run continuously without interruption.
The available information does not establish a universal OCPU or memory requirement for a YouTube loop. Source resolution, codecs, bitrate, frame rate, filtering, output settings, concurrent streams, region, and the required interruption rate all affect the answer. Measure the actual workload rather than treating a shape name or its maximum specifications as proof of performance.
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First decide whether FFmpeg copies or re-encodes
Stream-copy a compatible, already-encoded file
FFmpeg’s -stream_loop input option repeats an input. Streams are transcoded unless you specify -c copy; stream-copy sends the encoded audio and video onward without encoding them again. That distinction matters more to initial sizing than the source video’s resolution alone. See the FFmpeg documentation for the options and their behavior.
Copying does not mean every workload is identical: the input streams must be usable for the intended output, and network delivery still has to be sustained. Check the FFmpeg log and YouTube’s live-stream status while testing, rather than assuming that successful process startup proves a stable stream.
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Re-encode or apply computationally expensive filters
When FFmpeg decodes and re-encodes, or applies demanding filters, resource demand can vary substantially with codec, resolution, frame rate, bitrate, and filter chain. There is no reliable fixed OCPU figure without those details and a representative test. If you need re-encoding, test the exact command and media, then scale based on observed CPU, memory, and network use.
Run more than one stream
Multiple concurrent streams add workload. Test the intended number of simultaneous inputs and outputs, including the most demanding media and filters you expect to use. Do not assume that an allocation suitable for one copied stream will also serve multiple streams or transcoding.
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What A1.Flex specifications do—and do not—tell you
Oracle identifies VM.Standard.A1 as Arm-based OCI Ampere A1 compute using an Ampere Altra Q80-30 processor. Oracle says each OCPU corresponds to one hardware execution thread and lists a maximum frequency of 3.0 GHz. Its shape reference lists A1.Flex from 1 to 76 OCPUs, up to 472 GB of memory, and maximum network bandwidth of 1 Gbps per OCPU up to 40 Gbps. Those are shape limits, not the resources or performance of every instance. Your allocation determines its configured resources; a small instance does not receive the shape’s maximums. Consult Oracle’s Compute Shapes reference.
For a one-OCPU allocation, do not read the 40 Gbps shape ceiling as the instance’s network allocation. The published per-OCPU relationship and maximum describe the shape; they do not establish the throughput you will actually sustain to YouTube from a particular region. Validate network behavior in your own stream test.
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Check Arm compatibility before creating the instance
A1.Flex is Arm-based. Oracle’s instance creation guide says Ampere A1/A2 shapes do not support Windows. Before choosing A1, confirm that the operating system image, FFmpeg build, codec libraries, and any scripts or dependencies you need work on Arm. Oracle’s guide to creating an instance identifies A1 as Arm-based and explains the Windows limitation.
If a required package or codec workflow is unavailable for your chosen image and architecture, this shape may not fit even if the nominal CPU and memory appear sufficient. Resolve compatibility before investing time in deployment.
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What the Always Free allowance covers
Oracle’s current Always Free resources documentation gives each tenancy 1,500 A1 OCPU-hours and 9,000 GB-hours per month—equivalent for Always Free tenancies to 2 OCPUs and 12 GB of memory. The pool can be allocated to one 2-OCPU instance or up to two 1-OCPU instances, with memory allocated within the entitlement. It is a monthly allowance, not an unlimited instance entitlement. Always Free compute instances must be created in the tenancy’s home region. See Oracle’s Always Free resources documentation.
Oracle notes that an “out of host capacity” error when creating an Always Free compute instance indicates a temporary lack of Always Free shapes in the home region. Trying another availability domain or waiting may help, but neither guarantees immediate capacity. Check your own tenancy’s limits and region before planning paid scale-out: Oracle says service limits vary by account type and scope, and a published limit is not the same as available host capacity. See Oracle’s service limits reference.
When hardware acceleration changes the decision
A GPU is not a default requirement for a CPU-only stream-copy loop. If you need hardware encoding, first verify that the selected OCI configuration actually provides the required hardware device and that your FFmpeg build, encoder or decoder, and driver support it. FFmpeg documents that hardware acceleration depends on all of those components and can be unavailable or add overhead in some workflows. The A1 information here does not establish that A1 provides a GPU; do not assume that it does.
How to size and validate your stream
- Record the workload. Note the input resolution, video and audio codecs, frame rate, bitrate, whether you will use
-c copyor re-encode, any filters, and the number of simultaneous streams. - Check compatibility. Confirm that your selected OCI image, FFmpeg build, codec libraries, and scripts support Arm if you plan to use A1.Flex.
- Start with a trial allocation. For one pre-encoded stream-copy loop, try 1 OCPU and 6 GB RAM as an initial configuration—not as a production guarantee.
- Run the real command and media. Test the intended output settings and observe CPU, memory, and network use, along with FFmpeg logs and YouTube’s stream status. Include the filters, concurrency, and media that represent your heaviest expected use.
- Adjust against evidence. If measurements show sustained resource pressure or the stream is unstable, change the allocation or simplify the workload, then repeat the test. Establish the interruption rate you can tolerate before calling the setup production-ready.
- Recheck account and regional constraints. Verify the tenancy’s applicable service limits, home-region placement for Always Free compute, and actual capacity before depending on a particular allocation.
Common sizing and setup mistakes
- Assuming every loop re-encodes: FFmpeg can stream-copy when you specify
-c copy. Confirm what your command does before sizing for encoding. - Treating the 40 Gbps maximum as your instance bandwidth: it is an A1.Flex shape ceiling, not the allocation of every instance or a measured route to YouTube.
- Choosing A1 without checking architecture: A1 is Arm-based, and Oracle says Ampere A1/A2 do not support Windows. Confirm your image and software compatibility first.
- Reading Always Free as a dedicated two-OCPU promise: the documented entitlement is a monthly pool, instances must be in the tenancy’s home region, and capacity may be temporarily unavailable.
- Assuming a successful launch proves 24/7 reliability: no cited workload-specific benchmark establishes sustained performance for your exact media and settings. Run a representative test and monitor it.
- Adding hardware acceleration without checking support: the device, driver, FFmpeg build, and selected method all need to work together; acceleration is not guaranteed to help every workflow.
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