Showing posts with label Analysys Mason. Show all posts
Showing posts with label Analysys Mason. Show all posts

Tuesday 31 May 2022

Transitioning from Cloud-native to Edge-Native Infrastructure

We have looked at what we mean by cloud-native in an earlier post here. Recently we also looked at edge-native infrastructure here. While we have been debating between cloud and edge for a while, in a new presentation (embedded below), Gorkem Yigit, Principal Analyst, Analysys Mason argues that the new, distributed IT/OT applications will drive the shift from cloud-native to edge-native infrastrcuture.

The talk by Gorkem on '5G and edge network clouds: industry progress and the shape of the new market' from Layer123 World Congress 2021 is as follows:

A blog post by ADVA has a nice short summary of the image on the top that was also presented at a webinar earlier. The following is an extract from that blog post: 

The diagram compares hyperscale (“cloud-native infrastructure”) on the left with hyper-localized (“edge-native infrastructure”) on the right.

  • Computing: The traditional hyperscale cloud is built on centralized and pooled resources. This approach enables unlimited scalability. In contrast, compute at the edge has limited scalability, and may require additional equipment to grow applications. But the initial cost at the edge is correspondingly low, and grows linearly with demand. That compares favorably to the initial cost for a hyperscale data center, which may be tens of millions of dollars.
  • Location sensitivity and latency: Users of the hyperscale data center assume their workloads can run anywhere, and latency is not a major consideration. In contrast, hyper-localized applications are tied to a particular location. This might be due to new laws and regulations on data sovereignty that require that information doesn’t leave the premises or country. Or it could be due to latency restrictions as with 5G infrastructure. In either case, shipping data to a remote hyperscale data center is not acceptable.
  • Hardware: Modern hyperscale data centers are filled with row after row of server racks – all identical. That ensures good prices from bulk purchases, as well as minimal inventory requirements for replacements. The hyper-localized model is more complicated. Each location must be right-sized, and supply-chain considerations come into play for international deployments. There also may be a menagerie of devices to manage.
  • Connectivity: Efficient use of hyperscale data centers depends on reliable and high-bandwidth connectivity. That is not available for some applications. Or they may be required to operate when connectivity is lost. An interesting example of this case is data processing in space, where connectivity is slow and intermittent.
  • Cloud stack: Hyperscale and hyper-localized deployments can host VMs and containers. In addition, hyper-localized edge clouds can host serverless applications, which are ideal for small workloads.
  • Security: Hyperscale data centers use a traditional perimeter-based security model. Once you are in, you are in. Hyper-localized deployments can provide a zero-trust model. Each site is secured as with a hyperscale model, but each application can also be secured based on specific users and credentials.

You don’t have to choose upfront

So, which do you pick? Hyperscale or hyper-localized?

The good news is that you can use both as needed, if you make some good design choices.

  • Cloud-native: You should design for cloud-native portability. That means using technologies such as containers and a micro-services architecture.
  • Cloud provider supported edge clouds: Hyperscale cloud providers are now supporting local deployments. These tools enable users to move workloads to different sites based on the criteria discussed above. Examples include IBM Cloud Satellite, Amazon Outposts, Google Anthos, Azure Stack and Azure Arc.

You can also learn more about this topic in the Analysys Mason webinar, “From cloud-native to edge-native computing: defining the cloud platform for new use cases.”. You can also download the slides from there after registration.

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Monday 4 October 2021

Are there 50 Billion IoT Devices yet?

Detailed post below but if you are after a quick summary, it's in the picture above.

Couple of weeks back someone quoted that there were 50 billion devices last year (2020). After challenging them on the number, they came back to me to say that there were over 13 billion based on GSMA report. While the headline numbers are correct, there are some finer details we need to look at.

It all started back in 2010 when the then CEO of Ericsson announced that there will be 50 Billion IoT Devices by 2020. You could read all about it here and see the presentation here. While it doesn't explicitly say, it was expected that the majority of these will be based on cellular technologies. I also heard the number 500 Billion by 2030, back in 2013.

So the question is how many IoT devices are there today and how many of these are based on mobile cellular technologies?

The headline number provided by the GSMA Mobile Economy report, published just in time for MWC 2021, is 13.1 billion in 2020. It does not provide any further details on what kind of connectivity these devices use. I had to use my special search skills to find the details here.

As you can see, only 1.9 billion of these are based on cellular connections, of which 0.2 billion are based on licensed Low Power Wide Area (licensed LPWA, a.k.a. LTE-M and NB-IoT) connections. 

Ericsson Mobility Report, June 2021, has a much more detailed breakdown regarding the numbers as can be seen in the slide above. As of the end of 2020, there were 12.4 billion IoT devices, of which 10.7 billion were based on Short-range IoT. Short-range IoT is defined as a segment that largely consists of devices connected by unlicensed radio technologies, with a typical range of up to 100 meters, such as Wi-Fi, Bluetooth and Zigbee.

Wide-area IoT, which consists of segment made up of devices using cellular connections or unlicensed low-power technologies like Sigfox and LoRa had 1.7 billion devices. So, the 1.6 billion cellular IoT devices also includes LPWAN technologies like LTE-M and NB-IoT.

I also reached out to IoT experts at analyst firm Analysys Mason. As you can see in the Tweet above, Tom Rebbeck, Partner at Analysys Mason, mentioned 1.6 billion cellular (excluding NB-IoT + LTE-M) and 220 million LPWA (which includes NB-IoT, LTE-M, as well as LoRa, Sigfox etc.) IoT connections.

I also noticed this interesting chart in the tweet above which shows the growth of IoT from Dec 2010 until June 2021. Matt Hatton, Founding Partner of Transforma Insights, kindly clarified that the number as 1.55 billion including NB-IoT and LTE-M.

As you can see, the number of cellular IoT connections are nowhere near 50 billion. Even if we include all kinds of IoT connectivity, according to the most optimistic estimate by Ericsson, there will be just over 26 billion connections by 2026.

Just before concluding, it is worth highlighting that according to all these cellular IoT estimates, over 1 billion of these connections are in China. GSMA's 'The Mobile Economy China 2021' puts the number as 1.34 billion as of 2020, growing to 2.29 billion by 2025. Details on page 9 here.

Hopefully, when someone wants to talk about Internet of Thing numbers in the future, they will do a bit more research or just quote the numbers from this post here.

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