Once upon a time, personal computers dominated our desks and were our lifeblood; hours of scrolling through eBay items without squinting was a joy. Now we mainly use them to access Cloud-based ‘productised’ services such as Office 365, Facebook, Amazon and a bit of online banking.
These Cloud-based services are the virtual embodiment of centralisation; after all, productisation is a one size fits all offering (albeit with a few configurable widgets to make us feel special). With all this Big Data held in one place we’re able to derive business intelligence on a scale previously unimaginable, matched only by our initial security fear levels (although these have largely dissipated now).
As a concept, moving to Cloud isn’t simple even before you consider the many practicalities (which is why our Cloud Plug and Playbook gives you as much clarity and control as possible). For organisations using time-sensitive data there’s more to consider and it’s worth taking a look at slightly ‘edgier’ solutions during the complex transformation programme Discovery process.
So, what is edge computing?
Edge computing is more about location than technology; if speed matters, then so does distance. With origins in content delivery networks created in the late 1990s to serve web and video content from servers close to users, edge optimises internet devices and web applications by bringing computing closer to the source of the data.
Edge is used to process time-sensitive data, while cloud computing is used to process data that is not time-driven. Rather than sending all data collected by Internet of things (IoT) sensors directly to the Cloud, data is processed by the device itself within the network, or by a local computer or server (instead of being transmitted to a data centre). Only relevant data, or information conveniently bundled is sent which reduces latency and bandwidth issues. Besides latency, edge is preferred over Cloud in remote locations, where there is limited or no connectivity to a centralised location.
Security challenges are a bit different with Edge as data travels between different distributed nodes connected through the internet and requires special encryption mechanisms independent of the Cloud.
Benefits
Edge computing creates new and improved ways for industrial and enterprise-level organisations to maximise operational efficiency, improve performance and safety, and automate all core business processes. It should be seen as complementary to Cloud services, as it has different benefits:
Better data management. Relocating data that is critical to business performance means data is logically separated to where it’s needed most, it forces a data review/clean-up, and encourages real-time data processing that allows you to respond faster and more effectively to business changes.
Lower costs. Edge offers a cost-effective route to scalability by combining co-location services with regional edge computing data centres. This also enables companies to target a specific market without investing in expensive infrastructure expansion. Growth costs are eased as each new device added doesn’t impose substantial bandwidth demands. By reducing the volume of data being transported around your system landscape, storage requirements and consequently costs are reduced. Connections over shorter distances should also help bring them down further.
Reliable, uninterrupted connection. Edge ensures ‘always on’ availability and applications can be used effectively in remote locations. With data transfer happening over shorter connection lines, reliability is organically improved. Transfers happen faster and with reduced interruptions meaning throughput increases and latency decreases.
Improved security practices. Edge computing allows you to remove sensitive data at source rather than sending it to a centralised data warehouse. Lower transfer rates of sensitive data mean better data security.
Centralised Cloud computing architecture makes it especially vulnerable to power outages and Distributed denial of service (DDoS) attacks (where an existing network resource is overwhelmed with traffic from other compromised resources within the network). Edge computing distributes processing, storage, and applications across a wide range of devices and data centres, which makes it difficult for any single disruption to take down the entire network.
Although edge creates an increased cyberattack surface by locating computing resources closer to data sources and IoT edge devices, it’s easier to implement security protocols to seal off any weak points without shutting down the entire network.
The ownership of the data collected shifts from service providers to end-users, and it provides better data sovereignty/geographical legislation (GAIA-X vs. the US CLOUD Act). Aitemology® NED Paul Kearney gives an example: “I work with a MedTech company that is proud to shout about their patients’ personal data being held on a renowned database server in a country of their choice. It’s still in the Cloud but somewhere a bit ‘edgier’ than out in the ether, which makes their GDPR managers happy.”
How intelligent is your business?
According to Gartner, less than 10% of enterprise-generated data is created and processed at the edge right now, but they predict this will grow to 75% by 2025. IDC predicts that by 2023, more than half of new enterprise IT infrastructure deployed will be at the edge rather than corporate data centres, and the number of apps at the edge will increase 800% by 2024.
Organisations need to think of ‘edge’ as an extension of Cloud rather than a replacement. Dave McCarthy, research director in IDC’s worldwide infrastructure practice focusing on edge strategies says: “A centralised approach to infrastructure has limitations. Instead, enterprises are now looking at edge computing as a way to distribute workloads to locations where they run best. This could be metro-level co-location facilities such as remote and branch offices, or industry-specific locations like factories, warehouses, hospitals, and retail stores.”
To harness the combination of Cloud and edge computing, workloads must be containerised and distributed across multiple Cloud as-a-service, edge servers, and edge devices. This is called ‘edge intelligence’.
The things every organisation should be thinking about, whether before, during or after a move to Cloud, are:
- How am I using (or going to use) Cloud and are the benefits of edge greater?
- How are my applications developed and platformed, or re-platformed?
- Do I properly understand the limitations of edge with regards to how my applications are architected and run?
- Where is my edge?
- What am I doing in my edge?
- Where am I storing all this new data?
- How can I best use this data?
Aitemology® is the creator of a unique methodology (aitemology®) that forms the basis of the digital and business transformation Plug and Playbook series (Cloud, Change, Consult, Productise). Consisting of a ‘how to’ primer underpinned by a large number of specific/dedicated aitems® (policies, processes, technical products, reports, templates) organisations are able to follow their chosen transformation process step by step from start to finish (including all technical and non-technical elements) with convenience, clarity and control.
aitemology.com
Recent Comments