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For a YouTube stream that continuously encodes video and keeps CPU busy, start by evaluating an EC2 C7i instance: AWS classifies C7i as compute-optimized and lists video encoding among its suitable workloads. T3 is burstable and may fit variable CPU demand, but sustained use above its baseline can consume credits and incur additional charges. AWS does not publish an apples-to-apples T3-versus-C7i benchmark for a specific YouTube encoder setup, so test the exact instance size, encoder settings, and network path before relying on either one.
What matters when choosing an EC2 instance for YouTube
The instance has to do more than reach YouTube. For a self-managed stream, the host runs the encoder, maintains the connection to YouTube’s ingest endpoint, and may also handle other processing in your workflow. Choose for the actual workload: sustained CPU demand, memory, outbound network behavior, and the cost of running the host over time.
A family name alone does not determine whether a stream will be stable. Instance sizes within both families differ, and AWS’s published specifications are not application-level performance results. Validate your chosen size using the codec, resolution, frame rate, bitrate, encoder, and destination path you plan to use.
T3 vs. C7i at a glance
| Factor | T3 | C7i |
|---|---|---|
| Best fit | Variable workloads that can benefit from burstable CPU capacity. | Compute-heavy workloads; AWS specifically names video encoding as a suitable use. |
| CPU behavior | Earns CPU credits below its baseline and spends them above baseline. T3 starts in Unlimited mode by default; sustained high utilization may result in additional charges under AWS’s terms. | Fixed-performance compute-optimized instances, a better starting point for consistently high CPU use. |
| Size-specific examples | t3.medium: 2 vCPUs, 4 GiB memory, 20% baseline per vCPU. t3.2xlarge: 8 vCPUs, 32 GiB, 40% baseline per vCPU. | c7i.large: 2 vCPUs, 4 GiB memory. c7i.8xlarge: 32 vCPUs, 64 GiB. c7i.48xlarge: 192 vCPUs, 384 GiB. |
| Published network figures | These examples are listed with up to 5 Gbps (t3.medium) and up to 2.78 Gbps (t3.2xlarge) network burst bandwidth. | These examples are listed with up to 12.5 Gbps (c7i.large and c7i.8xlarge) and up to 50 Gbps (c7i.48xlarge) network bandwidth. |
| Benchmark for a specific YouTube setup | AWS does not provide a T3-versus-C7i benchmark for a specified encoder, codec, resolution, frame rate, or YouTube ingest configuration. | |
Specifications and behavior are described on AWS’s T3 instance page and C7i instance page. The figures above are examples, not guarantees for every size or streaming application.
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When T3 can make sense
T3 uses CPU credits to let an instance run above its CPU baseline for periods of time. It earns credits while running below baseline and spends them when running above it. AWS defines one CPU credit as one vCPU running at 100% utilization for one minute. That design can suit variable workloads, but an encoder that stays busy for long periods may consume credits continuously.
AWS says T3 instances start in Unlimited mode by default. That setting allows CPU use above baseline, but sustained high use can have additional charges under AWS’s terms. Check the current T3 documentation and billing details for your size and account before treating burst capacity as a free sustained-performance allowance. T3 sizes also vary in vCPU count, memory, baseline, and network burst bandwidth; do not assume the t3.medium figures apply to a larger or smaller size.
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When C7i is the stronger starting point
C7i is AWS’s compute-optimized family, and AWS lists video encoding among its suitable workloads. Its fixed-performance positioning makes it a more appropriate initial candidate than a burstable T3 when encoding keeps CPU consistently high. Larger C7i sizes provide substantially more total CPU and memory, though they may be more capacity than a single encoder needs.
AWS’s instance-type guidance recommends fixed-performance instances for consistently high CPU workloads such as video encoding. That is guidance about workload fit, not proof that a C7i size will meet a particular stream’s requirements. Consult AWS’s instance-type guidance and test an appropriately sized instance with your real encoding settings.
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Network bandwidth: why “up to” is not a stream guarantee
AWS’s published network numbers vary by instance size and traffic path. Some smaller instances marked “up to” can burst above a baseline using network I/O credits. AWS also documents constraints for traffic routed through an internet gateway. Those qualifications matter for a stream that must sustain outbound traffic, even if its bitrate is far below the instance’s headline maximum.
Do not equate an instance’s advertised network bandwidth with confirmed throughput to YouTube. Validate sustained outbound performance in the AWS Region and along the path you intend to use, while monitoring the encoder and stream for dropped frames or connection interruptions. AWS explains the relevant limits in its EC2 network bandwidth documentation.
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How to choose and validate a size
- Establish the workload. Record the video codec, resolution, frame rate, target bitrate, encoder software and settings, and whether the host performs any additional packaging or processing.
- Decide whether CPU demand is sustained. If encoding is consistently CPU-heavy, begin with a fixed-performance C7i candidate. If demand is intermittent, T3 may be worth evaluating, but account for its CPU baseline, credit behavior, Unlimited mode, and any applicable surplus charges.
- Compare exact sizes, not family labels. Check each candidate’s vCPU count, memory, baseline where applicable, and network characteristics in AWS documentation. A family-level recommendation cannot select the right size for every encoder.
- Test the actual stream path. Run the encoder with the intended settings and send it to the intended YouTube ingest destination. Observe CPU use, encoder output, dropped frames, reconnects, and sustained outbound performance over a representative period.
- Review cost after the test. Include instance runtime, any T3 surplus CPU charges, and other services in the streaming architecture. Revisit the size if it is consistently over- or under-provisioned.
Budget for the whole streaming setup
An EC2 instance’s hourly price is only one part of a live-streaming bill. AWS’s live-streaming planning guidance treats encoding and packaging separately from distribution, so account for the services and data paths your design actually uses. AWS’s Live Streaming on AWS planning guide is a configuration-specific planning resource, not a universal quote for a YouTube stream.
Prices also depend on Region, operating system, size, and billing terms. The T3 page’s displayed price context is Linux/Unix in US East (Northern Virginia); it should not be read as a global price. Check current AWS pricing for your selected configuration and Region, and include the possible T3 credit charges when comparing a burstable host with C7i.
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Or let it run in the cloud
If the goal is to keep uploaded videos playing on a YouTube channel around the clock, rather than to operate and monitor an EC2 encoder yourself, StreamNeo is a managed alternative. Upload your recording or build a playlist, add your YouTube stream key once, and go live; the cloud service loops the uploaded videos without requiring your computer or home connection to stay on.
- Nothing has to stay powered on at home.
- Videos stream as uploaded, at any quality up to 4K 60fps, for one flat price per slot.
- Automatic recovery if YouTube drops the stream.
- The first day is free with no card required; one free day is available per account.
The monthly price is $9.99 per month. StreamNeo is for looping uploaded videos to YouTube, not going live from a camera. Start your free StreamNeo day.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
