The concept of edge computing is simple. It’s about bringing computing and storage capabilities to the edge, to be in close proximity to the devices, applications, and users that generate and consume the data. Reflecting the rapid growth of 5G infrastructure, the demand for edge computing will continue to accelerate in today’s era of hyper-connectivity.
Everywhere you look, the demand for low latency experiences continues to rise, driven by technologies including IoT, AI/ML, and AR/VR/MR. While latency reduction, bandwidth costs, and network resilience are key factors, another discreet but equally important reason is compliance with data privacy and governance policies, which prohibit the transfer of sensitive data to central cloud servers for processing.
Instead of relying on distant cloud data centers, edge computing architecture optimizes bandwidth usage and reduces round-trip latency costs by processing data at the edge, ensuring that end users Have a positive experience with apps that are always fast and always available.
Forecasts predict that the global edge computing market will become an $18 billion space in just four years, expanding rapidly from what was a $4 billion market in 2020. Spurred by digital transformation initiatives and the With the proliferation of IoT devices (more than 15 billion will be connected to enterprise infrastructure by 2029, according to Gartner), innovation at the edge will capture the imaginations and budgets of companies.
Therefore, it’s important for enterprises to understand the current state of edge computing, where it’s headed, and how to devise a future-proof edge strategy.
Simplifying the management of distributed architectures
The first edge computing deployments were custom hybrid clouds with applications and databases running on on-premises servers backed by a cloud back-end. Typically, a rudimentary batch file transfer system was responsible for transferring data between the cloud and on-premises servers.
In addition to the capital costs (CapEx), the operating costs (OpEx) of running these distributed on-premises server installations at scale can be overwhelming. With the batch file transfer system, edge applications and services may be running out of stale data. And then, there are cases where hosting a server rack on-premises is not practical (due to space, power, or cooling limitations on offshore oil rigs, construction sites, or even airplanes).
To alleviate OpEx and CapEx concerns, the next generation of edge computing deployments must take advantage of edge managed infrastructure offerings from cloud providers. AWS Outposts, AWS Local Zones, Azure Private MEC, and Google Distributed Cloud, to name a few prime examples, can significantly reduce the operational overhead of managing distributed servers. These cloud edge locations can host storage and compute on behalf of multiple on-premises locations, reducing infrastructure costs while providing low-latency access to data. Additionally, edge computing deployments can take advantage of the high-bandwidth and ultra-low-latency capabilities of 5G access networks with managed private 5G networks, with offerings like AWS Wavelength.
Because edge computing is all about distributing data storage and processing, every edge strategy must consider the data platform. You will need to determine if and how your database can accommodate the needs of your distributed architecture.
Future-proof edge strategies with a perimeter-ready database
In a distributed architecture, data storage and processing can occur at multiple levels: in central cloud data centers, at cloud edge locations, and at the client/device level. In the latter case, the device could be a mobile phone, desktop system, or custom embedded hardware. From the cloud to the client, each level offers greater guarantees of service availability and responsiveness than the previous level. Co-locating the database with the application on the device would ensure the highest level of availability and responsiveness, without relying on network connectivity.
A key aspect of distributed databases is the ability to keep data consistent and synchronized at these various levels, subject to network availability. Data synchronization is not about bulk transfer or duplication of data across these distributed islands. It is the ability to transfer only the relevant subset of data at scale, in a way that is resilient to network outages. For example, in retail, only store-specific data may need to be transferred downstream to store locations. Or, in healthcare, it may only be necessary to send aggregated (and anonymized) patient data from hospital data centers.
Data governance challenges are exacerbated in a distributed environment and should be a key consideration in an edge strategy. For example, the data platform should be able to facilitate the implementation of data retention policies down to the device level.
Edge computing at PepsiCo and BackpackEMR
For many companies, a distributed database and data synchronization solution is critical to a successful edge computing solution.
Consider PepsiCo, a Fortune 50 conglomerate with employees around the world, some of whom operate in environments where Internet connectivity is not always available. Your sales reps needed an offline-ready solution to do their job properly and more efficiently. PepsiCo’s solution took advantage of an offline-first database that was integrated into the applications its sales reps must use in the field, regardless of Internet connectivity. Whenever an Internet connection is available, all data is automatically synced to the organization’s edge infrastructure, ensuring data integrity so applications meet stringent security and governance requirements.
BackpackEMR healthcare company provides software solutions for mobile clinics in underserved rural communities around the world. Often these remote locations have little to no access to the internet, impacting their ability to use traditional cloud-based services. BackpackEMR’s solution uses an integrated database within its patient care applications with peer-to-peer data synchronization capabilities that BackpackEMR teams leverage to share patient data between devices in real time, even without an internet connection.
By 2023, IDC predicts that 50% of new enterprise IT infrastructure deployed will be at the edge, rather than in corporate data centers, and that by 2024, the number of applications at the edge will increase 800%. As enterprises rationalize their next-generation application workloads, it is imperative to consider edge computing to augment cloud computing strategies.
Priya Rajagopal is Director of Product Management at Couchbase, a provider of a leading modern database for business applications that 30% of the Fortune 100 companies depend on. With more than 20 years of experience creating software solutions, Priya is co-inventor of 22 technology patents.
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