For a stable, known set of renditions, protocols and DRM settings, pre-rendered (pass-through) delivery is the simpler architecture: the origin serves files that were packaged before any viewer asked for them. When one stored source has to reach several protocols, DRM schemes or manifest shapes, just-in-time packaging fits better, because the origin assembles the manifest at request time. The cost is runtime compute and one more component in the delivery path. Before choosing, separate two operations that are often merged under the word “dynamic”: transforming an asset from URL parameters, and packaging existing renditions into a manifest. The official architecture guidance covered here supports the second; it does not compare arbitrary URL transformation APIs.
What the two approaches are choosing between
HLS is HTTP-based adaptive streaming. In Apple’s overview of the protocol, an encoder creates several variants at different bit rates, resolutions and quality levels, divides each into media segments, and produces a playlist for each variant. A master playlist points to the variant playlists and carries playback-control tags. The encoder or automation scripts then upload the playlists and segments to a web server or CDN. The chain a player follows is:
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- The master playlist, which lists the available variants.
- Each variant playlist, which lists the media segments for one rendition.
- The media segments themselves, which the player downloads in sequence.
Both architectures produce this same chain. They differ in when the playlists and segments are produced, and by whom.
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Pre-rendered (pass-through) delivery
Here “pre-rendered” means the content is already packaged for delivery before any request arrives. A pass-through origin, such as Amazon S3 in AWS’s example, stores those files and serves them without transforming them. AWS’s Streaming Media Lens, part of the AWS Well-Architected Framework, describes this pattern. The protocol, DRM and manifest shape are fixed by whatever was stored.
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Dynamic delivery: transformation versus just-in-time packaging
The word “dynamic” covers two different runtime operations:
- URL-driven transformation creates or selects a derived asset based on parameters in a delivery URL.
- Just-in-time packaging assembles the requested streaming protocol or manifest at request time from existing renditions.
The official guidance consulted substantiates just-in-time packaging. It does not provide a vendor-neutral evaluation of arbitrary URL transformation APIs, so claims about a particular transformation product should be checked against that product’s own documentation. Treating the two as one architecture leads to mixing up their cost and latency characteristics.
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Side-by-side comparison
| Decision axis | Pre-rendered / pass-through | Dynamic / just-in-time packaging |
|---|---|---|
| Where the work occurs | Encoding and packaging happen before requests; the origin serves prepared files. | The origin packages or assembles outputs at request time. |
| Flexibility | Output formats, DRM and manifest structure must be prepared and stored in advance. | One stored source can be packaged for several protocols, with DRM inserted during assembly, according to AWS guidance. |
| Runtime path | A simpler origin path. AWS identifies pass-through as suitable for limited compatibility requirements and lowest latency. | Adds runtime compute and a component to the delivery path. The flexibility can support diverse clients and advanced features. |
| Storage | Each protocol and DRM combination may need its own prepared output. AWS warns this can multiply storage. | A shared source can reduce duplicated packaged outputs, at the cost of runtime compute. |
| Workload fit | Reasonable when output requirements are stable and limited. | Worth considering when clients, protocols, DRM, manifest filtering or time-shift features need output that is generated dynamically. |
These are qualitative design characteristics from AWS architecture guidance, not measured benchmarks. AWS says the origin choice should reflect live versus VOD delivery, viewer count, latency targets and format diversity.
What the trade-off looks like in day-to-day operation
The table shows the design trade-off. The operational difference is who does the work when requirements change. With pre-rendered delivery, adding a DRM scheme or a new manifest shape means re-packaging and re-storing every affected output, then verifying each one. With just-in-time packaging, the same change is made once in the packaging layer, but every request depends on that layer being available and fast enough. Pass-through is the lower-risk path when the output set is stable; dynamic packaging is the lower-maintenance path when it is not.
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Choosing between them
- Count the outputs you need. If the protocols, DRM schemes and manifest shapes are few, known and unlikely to change, pre-rendered delivery is the default.
- Check the client mix. If different players need different manifests or DRM from one stored source, just-in-time packaging becomes the candidate.
- List the manifest features. The CloudFront guidance ties time-shifted viewing, manifest filtering and LL-HLS blocking playlist requests to query strings. If you need any of them, plan a manifest path that can process parameters and make sure the CDN forwards them.
- Set the latency target. Lowest latency favors the simpler origin path. If a dynamic origin is required, measure the delay it adds rather than assuming it is negligible.
- Separate live from VOD. Live playlists change and need short cache lifetimes; VOD outputs do not. Give each path its own cache policy.
CDN policy is part of the architecture
Do not apply one cache policy to every object. Google Cloud’s Media CDN routing example separates manifest and segment origins and assigns each its own TTL. In that example, live HLS and DASH manifests get a five-second TTL because they change regularly, and segments get a one-day TTL. Google presents these as example values in its documentation, not defaults. Tune each policy to how often the object actually changes and to your service’s cache behavior.
TTL by object type
| Object | Value in the vendor example | Basis |
|---|---|---|
| Live HLS or DASH manifest | Five-second TTL | Google Cloud Media CDN routing example; manifests change regularly. |
| Media segments | One-day TTL | Google Cloud Media CDN routing example. |
| VOD manifests | Not stated in the consulted sources | Set from how often the playlist changes in your workflow. |
Query strings that change the output
Manifest request parameters can change what the player receives, so the CDN must forward them where they matter. AWS’s CloudFront guidance for live and VOD delivery calls out the following cases:
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| Feature | What the CDN must do | If it does not |
|---|---|---|
| Time-shifted viewing | Forward the query string. | The feature may not work correctly. |
| Manifest filtering | Forward the query string. | The feature may not work correctly. |
| LL-HLS blocking playlist requests | Forward _HLS_msn and _HLS_part. |
The blocking requests may not work correctly. |
Low-latency HLS and incomplete objects
Google’s caching documentation describes open-ended byte-range requests. These let a CDN cache and deliver CMAF chunks while they are still being written. The behavior is conditional on the origin supporting streaming objects before they are fully written. Confirm that capability with your origin before designing an LL-HLS path around it. An origin that serves only completed objects cannot support this pattern.
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A question that often appears in community forums asks how to set TTL on dynamic HLS manifests so that edge-cached .m3u8 files do not cause player desyncs during live transitions. The consulted sources do not establish a universal TTL, and they do not show that caching manifests causes desyncs in general. The only concrete value is the five-second live manifest example above, which is illustrative rather than a fix.
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The general principle follows from how playlists work. A manifest cached for longer than the playlist changes can give players a segment list that lags the live edge. A very short TTL reduces that lag but sends more requests to the origin. A practical starting point is to set the live manifest TTL close to your encoder’s playlist update interval, then test the transitions you actually run, such as rendition changes and source switches, under realistic load.
Vendor figures on size reduction
- Google Cloud’s Media CDN documentation, “Enable dynamic compression” (consulted in 2026), gives 60% to 85% as a typical reduction in response size in typical cases.
- The same documentation says HLS and DASH playlists often undergo a total size reduction exceeding 90%.
These are vendor-published figures about compressing responses. They say nothing about the latency or cost of pre-rendered versus dynamic delivery, and they should not be read as a comparison between the two architectures.
How to compare two architectures fairly
The official sources consulted do not publish a controlled, like-for-like benchmark of these alternatives, and no independent comparative study of their relative cost or latency was found. Any numeric comparison has to come from a workload test you describe in full, not from reading architecture descriptions.
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- Build both pipelines from the same source: one pre-rendered and one using just-in-time packaging.
- Run one representative live workload and one VOD workload against each, with the same client set, the same formats and DRM requirements, and the same CDN configuration.
- Record startup latency, manifest request latency, origin compute and load, cache hit behavior, storage footprint and failure modes.
- Repeat the live runs through transitions and through origin slowdowns, and log what the player experiences at each point.
Troubleshooting common symptoms
- Different parameters return identical manifests. The CDN is probably not forwarding the query strings that change the output. Check the table of query-string features above.
- LL-HLS blocking requests do not behave as expected. Confirm that
_HLS_msnand_HLS_partare forwarded, and that the origin supports streaming incomplete objects. - Live viewers see stale playlists after a transition. Compare the manifest TTL with the playlist update interval; a TTL longer than the update interval is the usual suspect.
Sources referenced
- Apple Developer, “About HTTP Live Streaming”
- AWS, “Streaming Media Lens” in the AWS Well-Architected Framework
- AWS, “Deliver video streaming with CloudFront and AWS Media Services”
- Google Cloud, “Configure service routes” (Media CDN)
- Google Cloud, “Configure caching behavior” (Media CDN)
- Google Cloud, “Enable dynamic compression” (Media CDN), consulted in 2026
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