My name is GM Kolethras. I’m the product marketing specialist here at Haivision. And I’m joined here today by John Lawrence, who is our product manager for Kraken. We’ll be giving you an introduction and overview of the Kraken product. We’ll start by identifying challenges in ISR and defense workflows and address how Kraken solves these problems– from a product overview and highlighting Kraken’s key features and benefits, to discussing Kraken’s target use cases, as well as product offerings that address a variety of deployment options.
In a nutshell, here are four challenges that we’ve identified in ISR and defense workflows. John, can you give us a bit more context on each of these points?
Yeah, absolutely. In defense workflows, unpredictable and limited bandwidth is a universal issue. You’re often dealing with beyond-line-of-sight networks, satellite networks, bandwidth is at a premium. And so Kraken being able to compress and send out high quality video is really beneficial to ISR and defense workflows. And that touches on the next point, video quality and latency.
Maintaining high quality video at very low bandwidths and at low latency is critical for enabling these workflows. And then, of course, downstream compatibility– if you’re not compatible with the downstream systems, your video is not going to be seen by anybody. So solving that problem is crucial. And then, of course, preserving KLV metadata– your video without that KLV metadata in context, just isn’t going to cut it. So preserving KLV metadata, and then as we’ll talk later, providing some advanced KLV processing capabilities has really helped ingrain Kraken in these workflows.
Excellent. Thanks so much. So looking at Kraken, it’s a software-based transcoding, stream routing, and encoding solution that aggregates feeds and optimizes transport of live full motion video and metadata. At a high level, we’re going to look at all the things that Kraken is capable of doing, from transcoding and stream routing, to metadata processing and encoding. John, why don’t you start things off with transcoding?
Yeah, certainly, GM. So, I mean, transcoding, I think that’s what everybody knows Kraken for, so taking in an already compressed video stream and then manipulating it in some way through re-encoding that video stream. And by manipulating, that may be re-encoding it using a different codec– you can see the formats listed here on the top of the slide– or it could be encoding it to further reduce the bit rate, could be downscaling the resolution or the frame rate, or changing other encoding parameters as required by a downstream system.
Excellent. Now stream routing isn’t necessarily something that people usually associate with Kraken, but it’s becoming more and more relevant in ISR and defense applications. Why is it so important?
This is really important. And as you mentioned, it’s not really the initial use case that Kraken was targeted at. But it’s something that we’re seeing more and more of. Oftentimes, you’ll see SRT listed here. There may still be systems within these workflows that don’t support SRT, so Kraken
can take in the SRT streams and then flip them to transport stream over UDP. In that same vein, Kraken can also take multicast, flip that to unicast or vice versa. Oftentimes, we see that type of capability used for bridging together multiple networks.
And then the last two bullet points here on the top section– so Kraken can also be used within this stream routing context for what we call container flipping. The more technical term sometimes you’ll hear is transmuxing. So we see these types of RTSP or RTMP sources come in. And then Kraken can be used to, again, container flip those streams to transport stream over UDP or SRT so that we can maintain an interoperability with the downstream systems involved in these workflows.
We focused a lot on video and bandwidth. But let’s not forget about metadata, which also consumes bandwidth and is something to keep in mind. Where does Kraken’s metadata processing feature come in?
We’ve added some advanced processing, metadata processing capability to Kraken. Specifically, we’re going to talk about the filtering and decimation. What we really use these for is to reduce the amount of bandwidth that’s going to be allocated to metadata. And that, in turn, allows us to allocate more of that bandwidth to video. And, of course, then we get better quality video.
So the filtering and decimation– filtering, just like it sounds. It’s filtering out metadata tags or fields that are not needed within certain workflows. Decimation– really think of that in the same way you would decimating or downscaling a frame rate. It’s just reducing the rate of the metadata scaling out at. An example I always like to give is if you have 60-frame-per-second video, and you have a set of metadata with every single frame, for situational awareness, that’s overkill. Maybe you need one set of metadata every second. So the decimation feature can be used to accomplish that.
OK. John, we talked a lot about Kraken being able to transcode previously encoded streams, but what about uncompressed video?
Kraken actually can function as a baseband encoder. Kraken as a VM even can provide that capability. We have a couple of different ways to do that. So Kraken can make use of analog or SDI capture cards. It also can receive SDI video using a small SFP device to actually take in the SDI signal and then compress that as a transport stream or any of the other formats that Kraken supports.
OK. Now that we’ve talked a lot about what Kraken is actually capable of doing, let’s look at instances in workflows where Kraken excels. So here are some of the target use cases. John, let’s start with ISR backhaul.
I think this is what most people probably think of, the type of workflow most people think of when they think of Kraken. So it’s taking already compressed video that’s coming from an encoder on a platform and then, kind of like we talked about a couple of slides ago, manipulating that video in some way. So perhaps we need, as this slide really shows, we need to further compress that stream to send it over a satellite link.
And maybe that further compression is accomplished taking in an H.264 stream and then re-encoding it as H.265. Or it could be maintaining the same codec but just reducing the bit rate.
OK. So we see the stream here going from satellite to an IP network. And then the next step in the process would be monitoring and recording.
OK. So, in this use case, we typically see Kraken involved to ingest H.265 streams and then encode them as– or transcode them to H.264 streams. And that it’s typically for use with web-based viewing and recording systems that don’t support H.265.
OK. And the third use case we have is a relatively new one for Kraken– critical infrastructure. Tell us all about it.
So it’s very interesting. And it is a new use case. It’s a new market, new customer type. But interestingly enough, it’s very similar to the ISR backhaul use case. The differences or the formats of the incoming streams, the type of unmanned error system that’s in play, as well as the type of network that streams are being sent over, you’ll see here we’re actually now able to use the public internet. So we’ve come up with a cloud-based Kraken solution in the Azure cloud.
So this particular slide kind of highlights a workflow that we support for the oil and gas industry. So they use commercial drones that send out RTMP streams to Kraken on their local network where they flip that RTMP to a transport stream over SRT so that they can reliably get those streams up into the cloud. And then once they’re in the cloud, they can take advantage of the full set of Kraken features to transcoding it, route streams, and basically get those streams through HMP or other systems that may even be cloud-based systems for recording and distribution.
So I think that’s good timing because we see here that there are two different versions of Kraken in this workflow– one on-premise as well as Kraken VM in the cloud. Let’s look at the different Kraken offerings.
So you’ll see in this table here’s the various Kraken offerings that we have. You’ll notice they all support transcoding and stream routing. The Kraken VM, as we mentioned previously, also supports baseband encoding. The VM is really targeted, of course, for third party hardware. And this is where if there’s a ruggedization requirement, we can deploy on customer hardware that can meet those requirements.
Kraken Edge is for space-constrained applications, as you can see on the slide. But that’s space-constrained applications where there is not a ruggedization requirement or requirement to operate at high temperatures. And then Azure, of course, is our cloud-based solution. And the traditional Kraken server appliance is for the data center or operations center use case.
Excellent. If you have any further questions or want to know a little bit more about these features, the Kraken data sheet is available for download on our website. If you have further questions or want to get in touch with our sales team, you can reach out at [email protected] And I think that, with that, we can look at the takeaways from Kraken, the four pillars, if you will, on Kraken’s importance and relevance in these markets.
So the four pillars as GM mentioned, so compressing video to take advantage of the available bandwidth and maximize that bandwidth and also to ensure interoperability with all the various downstream systems, oftentimes, legacy systems. And then, of course, preserving KLV metadata for use in those systems.
Awesome. John, thanks so much for taking the time today to go over Kraken with us. We’ll see you again.
All right. Thanks a lot, GM.