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920-132 exam Dumps Source : Media Processing Server Rls.3.0 Application Developer
Test Code : 920-132
Test name : Media Processing Server Rls.3.0 Application Developer
Vendor name : Nortel
: 56 existent Questions
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Media Processing Server Rls.3.0 Application Developer
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The internet went down on February 28, 2017. Or at least that's how it seemed to some users, as sites and apps enjoy Slack and Medium went offline or malfunctioned for about four hours. What actually happened is that Amazon's enormously celebrated S3 cloud storage service experienced an outage, affecting everything that depended on it.
It was a reminder of the risks when too much of the internet relies on a solitary service. Amazon gives customers the option of storing their data in different "availability regions" around the world, and within those regions it has multiple data centers in case something goes wrong. But eventual year's outage knocked out S3 in the entire northern Virginia region. Customers could of course utilize other regions, or other clouds, as backups, but that involves extra work, including possibly managing accounts with multiple cloud providers.
A San Francisco-based startup called Netlify wants to accomplish it easier to avoid these sorts of outages by automatically distributing its customers’ content to multiple cloud computing providers. Users don't exigency accounts with Amazon, Microsoft Azure, Rackspace, or any other cloud company—Netlify maintains relationships with those services. You just note up for Netlify, and it handles the rest.
You can referee of the company's core service as a cross between traditional web hosting providers and content delivery networks, enjoy Akamai, that cache content on servers around the world to quicken up websites and apps. Netlify already has attracted some sizable tech names as customers, often to host websites related to open source projects. For example, Google uses Netlify for the website for its infrastructure management utensil Kubernetes, and Facebook uses the service for its programming framework React. But Netlify founders Christian Bach and Mathias Biilmann don't want to just breathe intermediaries in cloud hosting. They want to fundamentally change how web applications are built, and attach Netlify at the center.
Traditionally, web applications possess flee mostly on servers. The applications flee their code in the cloud, or in a company's own data center, assemble a web page based on the results, and transmit the result to your browser. But as browsers possess grown more sophisticated, web developers possess begun shifting computing workloads to the browser. Today, browser-based apps enjoy Google Docs or Facebook feel enjoy desktop applications. Netlify aims to accomplish it easier to build, publish, and maintain these types of sites.
Back to the Static Future
Markus Seyfferth, COO of Smashing Media, was converted to Netlify's vision when he saw Biilman speak at a conference in 2016. Smashing Media, which publishes the web design and progress publication Smashing Magazine and organizes the Smashing Conference, was looking to change the route it managed its roughly 3,200-page website.
Since its inception in 2006, Smashing Magazine had been powered by WordPress, the content management system that runs about 32 percent of the web, according to technology survey outfit W3Techs; some ecommerce tools to handle sales of books and conference tickets; and a third application for managing its job listing site. Relying on three different systems was unwieldy, and the company's servers struggled to handle the load, so Seyfferth was looking for a original approach.
When you write or edit a blog post in WordPress or similar applications, the software stores your content in a database. When someone visits your site, the server runs WordPress to pull the latest version from the database, along with any comments that possess been posted, and assembles it into a page that it sends to the browser. pile pages on the sail enjoy this ensures that users always perceive the most recent version of a page, but it's slower than serving prebuilt "static" pages that possess been generated in advance. And when lots of people are trying to visit a site at the identical time, servers can obtain bogged down trying to build pages on the sail for each visitor, which can lead to outages. That leads companies to buy more servers than they typically need.
Nevertheless, servers can soundless breathe overloaded at times. "When they had a original product on the shop, it needed only a pair hundred orders in one hour and the shop would fade down," Seyfferth says.
WordPress and similar applications try to accomplish things faster and more efficient by "caching" content to reduce how often the software has to query the database, but it's soundless not as rapid as serving static content.
Static content is moreover more secure. Using WordPress or similar content managers exposes at least two "attack surfaces" for hackers—the server itself, as well as the content management system. By removing the content management layer and simply serving static content, the overall "attack surface" shrinks, meaning hackers possess fewer ways to exploit software.
The security and performance advantages of static websites possess made them increasingly celebrated with software developers in recent years, first for personal blogs and now for the websites for celebrated open source projects.
In a way, these static sites are a throwback to the early days of the web, when practically entire content was static. Web developers updated pages manually and uploaded prebuilt pages to web servers. But the ascend of blogs and other interactive websites in the early 2000s popularized server-side applications that made it viable for nontechnical users to add or edit content, without special software. The identical software moreover allowed readers to add comments or contribute content directly to a site.
At Smashing Media, Seyfferth didn't initially referee static was an option. The company needed interactive features to accept comments, process credit cards, and allow users to post job listings. So Netlify built several original features into its platform to accomplish a primarily static approach more viable for Smashing Media.
The Glue in the Cloud
Biilmann, a native of Denmark, spotted the trend back to static sites while running a content management startup in San Francisco, and started a predecessor to Netlify called Bit Balloon in 2013. He invited Bach (his best friend from childhood, who was working as an executive at a creative services agency in Denmark) to combine him in 2015, and Netlify was born.
Initially the company focused on hosting static sites. Netlify quickly attracted high-profile open source users, but Biilman and Bach wanted it to breathe more than just another web hosting firm; they sought to accomplish static sites viable for interactive websites.
Open source programming frameworks possess made it easier to build sophisticated applications in the browser. And there's a growing ecosystem of services enjoy Stripe for payments; Auth0 for user authentication; and Amazon Lambda for running tiny chunks of custom code that accomplish it viable to outsource many interactive features to the cloud. But these types of services can breathe arduous to utilize with static sites, because some sort of server-side application is often needed to act as a middleman between the cloud and the browser.
Biilmann and Bach want Netlify to breathe that middleman, or as they attach it, the "glue" between disparate cloud computing services. For example, they built an ecommerce feature for Smashing Media, now available to entire Netlify customers, that integrates with Stripe. It moreover offers tools for managing code that runs on Lambda.
Smashing Media switched to Netlify about a year ago, and Seyfferth says it's been a success. It's much cheaper and more stable than traditional web application hosting. "Now the site pretty much always stays up no matter how many users," he adds. "We'd never want to notice back to what they were using before."
There are soundless some downsides. WordPress makes it easy for nontechnical users to add, edit, and manage content. Static site software tends to breathe less sophisticated and harder to use. Netlify is trying to address that with its own open source, static content-management interface called Netlify CMS. But it's soundless rough. Seyfferth says for many publications, it makes more sense to stick with WordPress for now, because Netlify can soundless breathe challenging for some users.
While Netlify is a developer darling today, it's viable that major cloud providers could replicate some of its features. Google already offers a service called Firebase Hosting that offers some similar functionality.
For now, though, Bach and Biilmann speak they're just focused on making their serverless vision practical for more companies. The more people who Come around to this original approach, the more opportunities there are not just for Netlify, but for the entire developing ecosystem.
More noteworthy WIRED Stories
Containerized Microservices require original monitoring. Read the eBook that explores why a original APM approach is needed to even see containerized applications.
Over the eventual few years, discussions about pile the prerogative kind of solution for Internet-based applications often Come up with a comparison between Monolithic applications and Microservices. pile the flawless solution and tooling around virtualization and clouds possess accelerated the adoption of the cloud-based technologies. Some examples :
With the launch of Amazon Web Services (AWS) in 2006, they can obtain compute resources on require from the web or the command-line interface.
With the launch of Heroku in 2007, they can deploy a locally-built application in the cloud with just a pair of commands.
With the launch of Vagrant in 2010, they can easily create reproducible progress environments.
With tools enjoy the ones above in hand, software engineers and architects started to dart away from large monolith applications, in which an entire application is managed via one code-base. Having one code-base makes the application difficult to manage and scale.
Over the years, with different experiments, they evolved towards a original approach, in which a solitary application is deployed and managed via a tiny set of services. Each service runs its own process and communicates with other services via lightweight mechanisms enjoy comfort APIs. Each of these services is independently deployed and managed.
Let's fade into the details:
Era of Monolith
Monolith is a technical term used to identify a particular kind of application. A monolithic application has entire of its components residing together as one unit. A web application is a software program running on a web server. An application consists of three main components, user interface(UI), database, and server.
The monolithic application contains entire three of these components and is written and released as a solitary unit. Internally, the codebase might breathe modular, but the components are entire deployed together and are only designed to toil within that identical application.
Let’s fade back to the dawn of “internet” time, which was somewhere around 1995. At this time, you may possess create yourself hoarding AOL CDs in order to connect to the internet, check your email, and for making crafts. As the years moved on and the internet evolved, the AOL CDs you were hoarding only became wonderful for making crafts. The AOL CD contained an application, and that application was a monolith. It was a self-containing piece of software that was able to flee independently on its own. In order to upgrade the version of AOL, you had to obtain a completely original CD and replace the program. This is how a monolith handles its software release cycle (the process of which an application is upgraded or modified) - the entire program must breathe replaced, and this is moreover how the first web applications were designed.
Fast forward to now and the purchase of a brand-new computer. This computer is preloaded with entire sorts of noteworthy software and, upon connecting to the internet, you disburse the first hour downloading and installing updates to that software. This software being updated is no longer a monolithic application, because parts of it can breathe updated piece by piece. This is an illustration of how the application changed from the days of the AOL CD.
Pros of monoliths:
Similar to desktop applications that were designed to breathe shipped via media enjoy floppy disks or compact disks, and then installed to the desktop, monolithic web-based applications were designed at first to breathe self-contained and possess everything the user needed to obtain their toil done.
It can breathe easier to develop a monolithic application because entire the functionality is in one place. And when tests are performed, even if the internals of the application are modular, externally there is only a solitary entity to test.
It is less complicated to accomplish the application flee on a server. The process of touching the application from a developer's laptop to a testing environment, and eventually to production, is generally defined as deploying software.
If there is increased require for the application, then more copies can breathe deployed behind a system called a load balancer. The load balancer will then dole requests to any available server.
Cons of monoliths:
As the application grows in complexity, in the lines of code, and in the number of features, the developers that possess been around the longest can breathe the most effective to accomplish changes. Yet, original developers remove the longest to bring on board, because they exigency to learn a large system to breathe effective.
Since the application is so large now, the skill to accomplish notable changes become harder to do. A developer needs to test any change they are working on and test the entire system before they are confident to release their changes to production. As a result, it can breathe harder to adopt original technologies, because it would handle the entire system.
When the size of the application was smaller, it was quicker to deploy. Now that the application grew to a larger size, and started running on multiple servers, the time it takes to deploy is longer. Every change, large or small, requires that the entire application gets deployed again.
Time does not just extend when a release goes to production. Because it needs to breathe tested first. If it is already slower to deploy to production, it is slower to deploy to every environment that is used to test it before deploying it to production.
Monolithic applications certainly possess their zone when you possess a simple application that serves a basic purpose. When your application needs to grow, change, and perform, the monolith will no longer breathe a wonderful fit, and it will breathe time to investigate microservices.
Enter the Microservices
Individual parts of the application exigency to breathe divided into their independent functions. They moreover exigency to breathe able to connect with each other. Each of these tiny services (or microservices, as they became known) are tiny applications which contain well-defined pieces of what was once a monolith.
To toil together, services will exigency to talk to each other. The rules for interaction between components are called an Application Programmer Interface, or API for short.
With monoliths, the various pieces of the application typically partake a solitary database. Microservices normally execute not partake databases. Each microservice is answerable for its own storage. Communication between microservices is done via the API, rather than through a shared database.
Having a divide database for each service ensures lax coupling, which allows each service to fit together well. With this separation, you may settle some services exigency different databases than others.
Applications which possess been divided across multiple services (and thus multiple servers) are called distributed systems. Some services are visible to the user, while others are only used internally by other services. The latter are called back-end services.
Pros of microservices:
Decomposing the application into more manageable chunks makes the entire codebase easier to understand, develop, and maintain. As your application grows, you can dedicate entire teams to particular services. These teams each focus on a solitary service, rather than your entire application.
As long as each component can tarry loosely coupled with other services in the system, each team is free to develop as it sees fit. Thus, the barrier to adopting original technologies, frameworks, or languages is lowered.
Now, each deploy can breathe controlled at the service level, not at the system-wide level. By breaking apart the large, monolithic deployment into separate, smaller deployments, developers possess an easier time to accomplish a change, flee the tests, and transmit it to production.
Even scaling each of the services is easier now. Each component can breathe monitored and possess the reform amount of resources, instead of adding an entire server just to provide capacity for a few features. There is no language or technology lock-in. As each service works independently, they can elect any language or technology to develop it. They just exigency to accomplish confident its API endpoints return the expected output.
Each service in a microservice can breathe deployed independently.
We execute not possess to remove an entire application down just to update or scale a component. Each service can breathe updated or scaled independently. This gives us the skill to respond faster.
If one service fails, then its failure does not possess a cascading effect. This helps in debugging as well.
Once the code of a service is written, it can breathe used in other projects, where the identical functionality is needed.
The microservice architecture enables continuous delivery.
Components can breathe deployed across multiple servers or even multiple data centers.
They toil very well with container orchestration tools enjoy Kubernetes, DC/OS and Docker Swarm.
Cons of microservices:
Just enjoy any other technology, there are moreover challenges and disadvantages to using microservices:
It can breathe harder to troubleshoot divide services than it is with a monolith. This can breathe overcome if you possess the prerogative tools and technology in place.
Each microservice in your system is answerable for its own database or other storage. This creates the potential for data duplication across the services. The solution to this is (a) drawing service boundaries in the prerogative places and (b) always ensuring that any particular data possess a solitary source of truth.
Microservice application testing is more involved than testing a monolith. If service A relies on service B, then the team testing service A must either provide an instance of service B to test against or provide a simplified version of B as a placeholder. These placeholders are called stubs.
Dividing things into its smaller parts can breathe taken too far. You will know you possess gone too far when the overhead (communications, maintenance, etc.) outweighs its utility. Instead, perceive if you can combine the service back into another that is similar.
While breaking the monolith application or creating microservices from scratch, it is very notable to elect the prerogative functionality for a service. For example, if they create a microservice for each duty of a monolith, then they would cessation up with lots of tiny services, which may bring unnecessary complexity.
We can easily deploy a monolith application. However, to deploy a microservice, they exigency to utilize a distributed environment such as Kubernetes or Docker.
With lots of services and their inter-dependency, sometimes it becomes challenging to execute end-to-end testing of a microservice.
Inter-service communication can breathe very costly if it is not implemented correctly. There are options such as message passing, RPC, etc., and they exigency to elect the one that fits their requirement and has the least overhead.
When it comes to the microservices' architecture, they may settle to implement a database local to a microservice. But, to proximate a business loop, they might require changes on other related databases. This can create problems (e.g. partitioned databases).
Monitoring individual services in a microservices environment can breathe challenging. This challenge is being addressed, and a original set of tools, enjoy Sysdig or Datadog, is being developed to monitor and debug microservices.
Even with the above challenges and drawbacks, deploying microservices makes sense when applications are involved and continuously evolving.
Both the progress and delivery of web applications possess changed over the eventual twenty years. To deliver modern web applications, developers are delivering to the cloud. And that requires what is called a cloud-native approach. entire that means is that the system will breathe split into many parts, then distributed to multiple pieces, and communicated over the internet.
microservices ,cloud native ,monolith ,software architecture
Reliable UDP (RUDP): The Next sizable Streaming Protocol?
New so-called reliable UDP solutions offer an alternative to TCP. But are they worth the time or money to implement?
Learn more about the companies mentioned in this article in the Sourcebook:
All too often they shy away from the depths of IP protocols, leaving the application vendors such as Microsoft; Wowza Media Systems, LLC; RealNetworks, Inc.; Adobe Systems, Inc.; and others with more specific skills to deal with the shaded expertise of the network layer for us, while they just kind in the server name, hit connect, then hit start.
Those who possess had a shrimp experience will probably possess heard of TCP (transmission control protocol) and UDP (user datagram protocol). They are transport protocols that flee over IP links, and they define two different ways to transmit data from one point to another over an IP network path. TCP running over IP is written TCP/IP; UDP in the identical format is UDP/IP.
TCP has a set of instructions that ensures that each packet of data gets to its recipient. It is comparable to recorded delivery in its most basic form. However, while it seems obvious at first that "making confident the message gets there" is paramount when sending something to someone else, there are a few extra considerations that must breathe noted. If a network link using TCP/IP notices that a packet has arrived out of sequence, then TCP stops the transmission, discards anything from the out-of-sequence packet forward, sends a "go back to where it went wrong" message, and starts the transmission again.
If you possess entire the time in the world, this is fine. So for transferring my salary information from my company to me, I frankly don't faith if this takes a microsecond or an hour, I want it done right. TCP is fanciful for that.
In a video-centric service model, however, there is simply so much data that if a few packets don't accomplish it over the link there are situations where I would rather skip those packets and carry on with the overall stream of the video than obtain every detail of the original source. Their brain can imagine the skipped bits of the video for us as long as it's not distracted by jerky audio and stop-motion video. In these circumstances, having an option to just transmit as much data from one cessation of the link to the other in a timely fashion, regardless of how much gets through accurately, is clearly desirable. It is for this kind of application that UDP is optimal. If a packet seems not to possess arrived, then the recipient waits a few moments to perceive if it does arrive -- potentially prerogative up to the second when the viewer needs to perceive that obstruct of video -- and if the buffer gets to the point where the missing packet should be, then it simply carries on, and the application skips the point where the missing data is, carrying on to the next packet and maintaining the time groundwork of the video. You may perceive a flicker or some artifacting, but the second passes almost instantly and more than likely your brain will fill the gap.
If this error happens under TCP then it can remove TCP upward of 3 seconds to renegotiate for the sequence to restart from the missing point, discarding entire the subsequent data, which must breathe requeued to breathe sent again. Just one lost packet can occasions an entire "window" of TCP data to breathe re-sent. That can breathe a considerable amount of data, particularly when the link is known as a Long chunky Network link (LFN or eLeFaNt; it's apt -- Google it!).
All this adds overhead to the network and to the operations of both computers using that link, as the CPU and network card's processing units possess to manage entire the retransmission and sync between the applications and these components.
For this intuition HTTP (which is always a TCP transfer) generally introduces startup delays and playback latency, as the media players exigency to buffer more than 3 seconds of playback to manage any lost packets.
Indeed, TCP is very sensitive to something called window size, and knowing that very few of you ever will possess adjusted the window size of your contribution feeds as you set up for your live sparkle Streaming encode, I can estimate that entire but those identical very few possess been wasting available capacity in your network links. You may not care. The links you utilize are wonderful enough to execute whatever it is you are trying to do.
In today's disposable culture of "use and discard" and "don't fix and reuse," it's no surprise that most streaming engineers just shrug and assume that the skill to obtain more bang for your buck out of your internet connection is beyond your control.
For example, did you know that if you set your maximum transmission unit (MTU) -- ultimately your video packet size -- too large then the network has to atomize it in two in a process called fragmentation? Packet fragmentation has a negative impact on network performance for several reasons. First, a router has to accomplish the fragmentation -- an expensive operation. Second, entire the routers in the path between the router performing the fragmentation and the destination possess to carry additional packets with the requisite additional headers.
Also, in the event of a retransmission, larger packets extend the amount of data you exigency to resend if a retransmission occurs.
Alternatively, if you set the MTU too tiny then the amount of data you can transfer in any one packet is reduced and relatively increases the amount of signaling overhead (the data about the sending of the data, equivalent to the addresses and parcel tracking services in existent post). If you set the MTU as tiny as you can for an Ethernet connection, you could find that the overhead nears 50% of entire traffic.
UDP offers some advantages over TCP. But UDP is not a panacea for entire video transmissions.
Where you are trying to execute large-video file transfer, UDP should breathe a noteworthy help, but its lossy nature is rarely acceptable for stages in the workflow that require absolute file integrity. Imagine studios transferring master encodes to LOVEFiLM or Netflix for distribution. If that transfer to the LOVEFiLM or Netflix playout lost packets then every solitary subscriber of those services would possess to accept that degraded master copy as the best viable copy. In fact, if UDP was used in these back-end workflows, the content would demean the user's experience in the identical route that historically tape-to-tape and other dubbed and analog replication processes used to. Digital media would lose that flawless replica quality that has been central to its success.
Getting back to the focus on who may want to reduce their network capacity inefficiencies: Studios, playouts, news desks, broadcast centers, and editing suites entire want their video content intact/lossless, but naturally they want to exploit that data between machines as rapid as possible. Having video editors drinking coffee while videos transfer from one zone to another is inefficient (even if the coffee is good).
Given they cannot operate in a lossy way, are these production facilities stuck with TCP and entire the inherent inefficiencies that Come with the reliable transfer? Because TCP ensures entire the data gets from point to point, it is called a "reliable" protocol. In UDP's case, that reliability is "left to the user," so UDP in its native shape is known as an "unreliable" protocol.
The wonderful news is that there are indeed options out there in the shape of a variety of "reliable UDP" protocols, and we'll breathe looking at those in the comfort of this article. One thing worth noting at the outset, though, is that if you want to optimize links in your workflow, you can either execute it the little-bit-hard route and pay very little, or you can execute it the easy route and pay a considerable amount to possess a solution fitted for you.
Reliable UDP transports can offer the exemplar situation for enterprise workflows -- one that has the benefit of high-capacity throughput, minimal overhead, and the highest viable "goodput" (a rarely used but useful term that refers to the portion of the throughput that you can actually utilize for your application's data, excluding other overheads such as signaling). In the Internet Engineering assignment obligate (IETF) world, from which the IP standards arise, for nearly 30 years there has been considerable toil in developing reliable data transfer protocols. RFC-908, dating from route back in 1984, is a wonderful example.
Essentially, RDP (reliable data protocol) was proposed as a transport layer protocol; it was positioned in the stack as a peer to UDP and TCP. It was proposed as an RFC (request for comment) but did not develope in its own prerogative to become a standard. Indeed, RDP appears to possess been eclipsed in the late 1990s by the reliable UDP Protocol (RUDP), and both Cisco and Microsoft possess released RUDP versions of their own within their stacks for specific tasks. Probably because of the "task-specific" nature of RUDP implementations, though, RUDP hasn't become a formal standard, never progressing beyond "draft" status.
One route to referee about how RUDP types of transport toil is to utilize a basic model where entire the data is sent in UDP format, and each missing packet is indexed. Once the main cadaver of the transfer is done, the recipient sends the sender the index list and the sender resends only those packets on the list. As you can see, because it avoids the retransmission of any windows of data that possess already been sent that immediately follow a missed packet, this simple model is much more efficient. However, it couldn't toil for live data, and even for archives a protocol must breathe agreed upon for sending the index. It responds to that rerequest in a structured route (which could result in a lot of random hunt disc access, for example, if it was badly done).
There are many reasons the major vendor implementations are task-specific. For example, where one may utilize UDP to avoid TCP retransmission after errors, if the entire data must breathe faultlessly delivered to the application, one needs to actually understand the application.
If the application requires control data to breathe sent, it is notable for the application to possess entire the data required to accomplish that decision at any point. If the RUDP system (for example) only looked for and re-requested entire the missing packets every 5 minutes (!) then the rational operations that lacked the data could breathe held up waiting for that re-request to complete. This could atomize the key duty of the application if the control decision needed to breathe made sooner than within 5 minutes.
On the other hand, if the data is a large archive of videos being sent overnight for precaching at CDN edges, then it may breathe that the retransmission requests could breathe managed during the morning. So the retransmission could breathe delayed until the entire archive has been sent, following up with just the missing packets on a few iterations until entire the data is delivered. So the flow, in this case, has to possess some user-determined and application-specific control.
TCP is easy because it works in entire cases, but it is less efficient because of that. On the other hand, UDP either needs its applications to breathe resilient to loss or the application developer needs to write in a system for ensuring that missing/corrupted packets are retransmitted. And such systems are in outcome proprietary RUDP protocols.
There is an abundance of these, both free and open source, and I am going to notice at several of each option (Table 1). Most of you who utilize existing streaming servers will breathe tied to the streaming protocols that your chosen vendor offers in its application. However, for those of you developing your own streaming applications, or bespoke aspects of workflows yourselves, this list should breathe a wonderful start to some of the protocols you could consider. It will moreover breathe useful for those of you who are currently using FTP for nonlinear workflows, since the swap out is likely to breathe relatively straightforward given than most nonlinear systems execute not possess the identical stage-to-stage interdependence that linear or live streaming infrastructures do.
Let's zip (and I execute breathe notable zip) through this list. Note that it is not meant to breathe a comprehensive selection but purely a sampler.
The first ones to explore in my intellect are UDP-Lite and Datagram Congestion Control Protocol. These two possess essentially become IETF standards, which means that inter-vendor operation is viable (so you won't obtain locked into a particular vendor).
Table 1: A Selection of reliable UDP Transports
Let's notice at DCCP first. DCCP provides initial code implementations for those inclined. From the point of view of a broadcast video engineer, this is really deeply technical stuff for low-level software coders. However, if you happen to be
(or simply possess access to) engineers of this skill smooth then DCCP is freely available. DCCP is a protocol worth considering if you are using shared network infrastructure (as opposed to private or leased line connectivity) and want to ensure you obtain as much throughput as UDP can enable, while moreover ensuring that you "play fair" with other users. It is worth commenting that "just turning on UDP" and filling the wire up with UDP data with no consideration of any other user on the wire can saturate the link and effectively accomplish it unusable for others. This is congestion, but DCCP manages to fill the pipe as much as possible, while soundless inherently enabling other users to utilize the wire too.
Some of the key DCCP features comprehend the following:
Adding a reliability layer to UDP
Discovery of the prerogative MTU size is portion of the protocol design (so you fill the pipe while avoiding fragmentation)
Indeed, to quote the RFC: "DCCP is intended for applications such as streaming media that can benefit from control over the tradeoffs between delay and reliable in-order delivery."
The next of these protocols is UDP-Lite. moreover an IETF standard, this nearly-identical-to-UDP protocol differs in one key way: It has a checksum (a number that is the result of a rational operation performed on entire the data, which if it differs after a transfer indicates that the data is corrupt) and a checksum coverage scope that that checksum applies to, whereas vanilla UDP -- optionally in IPv4, and always in IPv6 -- has just a simple checksum on the entire datagram and if present the checksum covers the entire payload.
Let's simplify that a little: What this means is that in UDP-Lite you can define portion of the UDP datagram as something that must arrive with "integrity," i.e., a portion that must breathe error-free. But another portion of the datagram, for illustration the much bigger payload of video data itself, can contain errors (remain unchecked against a checksum) since it could breathe assumed that the application (for example, the H.264 codec) has error handling or tolerance in it.
This UDP-Lite system is very pragmatic. In a pandemoniac network link, the video data may breathe subject to errors but could breathe the larger portion of the payload, where the notable sequence number may only breathe a smaller portion of the data (statistically less prone to errors). If it fails, the application can utilize UDP-Lite to request a resend of that packet. Note that it is up to the application to request the resend; the UDP-Lite protocol simply flags the failure up and the software can prioritize a resend request, or it can simply map to toil around a "discard" of the failed data. It is moreover worth noting that most underlying link layer protocols such as Ethernet or similar MAC-based systems may discard damaged frames of data anyway unless something interfaces with those link layer devices. So to toil reliably, UDP-Lite needs to interface with the network drivers to "override" these frame discards. This adds complexity to the deployment strategy and certainly most likely takes the chance away from being "free." However, it's fundamentally possible.
So I wanted to perceive what was available "ready to use" for free, or proximate to free at least. I went looking for a compiled, user-friendly, simple-to-use application with a user-friendly GUI, thinking of the videographers having to learn entire this code and profound packet stuff just to upload a video to the office.
While it's not really a protocol per se, I create UDPXfer, a really simple application with just a UDP "send" and "listener" mode for file transfer.
I set up the software on my laptop and a machine in Amazon EC2, fiddled with the firewall, and sent a file. I got very excited about the prompt 5MB UDP file transfer taking 2 minutes and 27 seconds, and I then set up an FTP of the identical file over the identical link but was disappointed that the FTP took 1 minute and 50 seconds -- considerably faster. When I looked deeper, however, the UDPXfer sender had a "packets per second" slider. I then nudged the slider to its highest setting, but it was soundless only essentially 100Kbps maximum, far slower than the effective TCP. So I wrote to the developer, Richard Stanway, about this ceiling. He sent a original version that allowed me to set a 1300 packets-per-second transmission. He commented that it would saturate the IP link from me to the server, and in a shared network environment a better approach would breathe to the tune the TCP window's size to implement some congestion control. His software was actually geared to resiliency over pandemoniac network links that occasions problems for TCP.
Given that I perceive this technology being used on private wires, the effective saturation that Stanway was concerned about was less of a concern for my enterprise video workflow tests, so I decided to give the original version a try. As expected, I managed to bring the transfer time down to 1 minute and 7 seconds.
So while the software I was using is not on general release, it is clearly viable to implement simple software-only UDP transfer applications that can equilibrium reliability with quicken to find a maximum goodput.
But what of the commercial vendors? execute they differentiate significantly enough from "free" to occasions me to gain into my pocket?
I caught up with Aspera, Inc. and Motama GmbH, and I moreover reached out to ZiXi. entire of this software is involved to procure at the best of times, so sadly I haven't had a random to play practically with these. Also, the vendors execute not publish rate cards, so it's difficult to remark on their pricing and value proposition.
Aspera co-presented at a recent Amazon conference with my company, and they had an chance to dig into its technology model a bit. Aspera is indeed essentially providing variations on the RUDP theme. It provides protocols and applications that sit on top of those protocols to enable rapid file distribution over controlled network links. In Aspera's case, it was selling in behind Amazon Web Services Direct Connect to offer optimal upload speeds. It has a scope of similar arrangements in zone targeting enterprises that handle high volumes of latency-sensitive data. You can license the software or, through the Amazon model, pay for the service by the hour as a premium AWS service. This is a nice flexible option for occasional users.
Aspera provides variations on the RUDP theme, including fasp 3, which the company introduced at this year's IBC in Amsterdam.
I had a very spirited chat with the CEO of Motama, which has a very appliance-based approach to its products. The RUDP-like protocol (called RelayCaster Streaming Protocol or RCSP) is used internally by the company's appliances to dart live video from the TVCaster origination appliances to RelayCaster devices. These then can breathe hierarchically set up in a traditional hub and spoke or potentially other more involved topologies. The software is available (under license) to flee on server platforms of your choice, which is wonderful for data heart models. They possess moreover recently started to notice at licensing the protocol to a wider scope of client devices, and they pride themselves in being available for set-top boxes.
Motama offers an appliance-based" approach to its RUDP-like protocol, which it calls RelayCaster Streaming Protocol and which is available for set-top boxes and CDN licensing.
The eventual player in the sector I wanted to note was ZiXi. While I briefly spoke with ZiXi representatives while writing this, I didn't manage to communicate properly before my deadline, so here is what I know from the company's literature and a few customer comments: ZiXi offers a platform that optimizes video transfer for OTT, internet, and mobile applications. The platform obviously offers a richer scope of features than just UDP-optimized streaming, and it has P2P negotiation and transmuxing so you can flip your video from standards such as RTMP out to MPEG-TS, as you can with servers such as Wowza. Internally, within its own ecosystem, the company uses its own hybrid ZiXi protocol, including features such as forward error correction, combining applications layer software in a product called Broadcaster that looks enjoy a server with several common muxes (RTMP, HLS, etc.) and includes ZiXi. If you possess an encoder with ZiXi running, then you can contribute directly to the server using the company's RUDP-type transport.
In addition to UDP-optimized streaming, ZiXi offers P2P negotiation and transmuxing, similar to servers from RealNetworks and Wowza.
Worth the Cost?
I am vigilant not a soul of these companies licenses their software trivially. The software packages are their core intellectual properties, and defending them is vital to the companies' success. I moreover realize that some of the problems that they purport to address may "go away" when you deploy their technology, but in entire honesty, that may breathe a shrimp enjoy replacing the engine of your car because a spark plug is misfiring.
I am left wondering where the customer can find the equilibrium between the productivity gains in accelerating his or her workflow with these techniques (free or commercial) against the cost of a private connection plus either the cost of progress time to implement one of the open/free standards or the cost of buying a supported solution.
The pricing indication I possess from a few undisclosed sources is that you exigency to breathe expecting to disburse a few thousand on the commercial vendor's licensing, and then more for applications, appliances, and support. This can quickly ascend to a significant number.
This increased cost to improve the productivity of your workflow must breathe at some considerable scale, since I personally referee that a shrimp TCP window sizing, and perhaps paying for slightly "fatter" internet access, may resolve most problems -- particularly in archive transfer and so on -- and is unlikely to cost thousands.
However, at scale, where those optimizations start to accomplish a significant productivity difference, it clearly makes a lot of sense to engage with a commercially supported provider to perceive if its offering can help.
At the cessation of the day, regardless of the fact that with a wonderful developer you can execute most things for free, there are notable drivers in large businesses that will obligate an operator to elect to pay for a supported, tested, and robust option. For many of the identical reasons, Red Hat Linux was a premium product, despite Linux itself being free.
I prod you to explore this space. To misquote James Brown: "Get on the goodput!"
This article appears in the October/November, 2012, issue of Streaming Media magazine as "Get on the Goodput."