Edge Computing: 2022 will be a pivotal year for edge adoption

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Edge Computing: 2022 will be a pivotal year for edge adoption

Diksha Nerurkar

@dikshanasscom-in

July 12, 2022

Cloud Computing

314

Edge computing is rapidly emerging as a central technology for digital transformation, esp. in the context of Ind 4.0. From the time when there was a lack of clarity about what “Edge” really means to the time when edge computing was seen as a threat to the cloud model to today, where edge computing is a continuation of the cloud, this technology has come a long way.

While the exact market size varies depending on which research firm you refer to, there is no doubt that the global edge computing market has been growing at a 35%+ CAGR. And with the advent of 5G, especially private 5G networks, the adoption is expected to further accelerate.

We have been tracking the edge computing market and as part of the NASSCOM Cloud Advocacy Program, we recently concluded a webinar where we explored current trends, use cases, challenges of managing a distributed environment and what it takes to build an edge strategy.

Here are key takeaways:

What is Edge?

Organizations shifting from a homogeneous, centralized, scalable environment (cloud) to a more heterogeneous, decentralized environment (edge)
Edge computing facilitates compute, storage, networking at/near the data source where it is generated or consumed. As sucht, the definition of hybrid cloud is getting extended to the infrastructure at the edge

Edge computing use cases

Manufacturing (Industrial process monitoring, predictive maintenance, Ind 4.0, digital factory)
BFSI (real-time facial recognition for smooth customer onboarding, fraud detection and prevention)
Automobiles (charging stations, collision avoidance)
Smart infrastructure: Smart homes, smart cities, smart buildings
Mobility: Drones, automated guided vehicles (AGVs), traffic routing
Retail, communications, utility, agriculture, healthcare, transportation, construction, pharma, and more

Trends

Telcos are bringing their network-centric capabilities esp. in multi-access or MEC to the edge
Edge workloads – AI workloads and data analytics, content delivery networks (CDNs) are more mature, i.e. in production stage; AR/VR, computer vision, mobility are in the PoC or Proof of Value stages
Key driving factors: Advent of Industrial IoT, 5G network, increase in the number of intelligent applications, the growing load on cloud infrastructure and the emerging area of metaverse
5G will be a key enabler of near real-time experiences (high speed-very low latency) along with edge (localized data processing)
Cloud-native technologies will be applied at the edge – automation, orchestration (Kubernetes), containerization, etc.
With large-scale roll out of edge, manageability from a central console, both from an orchestration perspective and monitoring & management perspective, is going to be important. We see technology being developed with self-diagnosing, self-monitoring and self-healing capabilities to manage such large scale of devices – where there is no manual intervention
Security will be a critical aspect. There are different trust boundaries, threat vectors and different approaches by firms for security, monitoring, vulnerability assessment, risk mitigation in a heterogeneous edge environment
Multiple complexities to be considered while deploying edge: managing & monitoring, securely onboarding devices, roll out of devices, patches, over-the-air updates to name a few
Technology architecture must be designed to ensure seamless flow of data between the edge, cloud and datacentre keeping in mind the inflow of the data, load balancing, security aspects; also, memory, processing capabilities and scalability

Skills needed

Systems design (how everything fits together), data exchange formats (JSON), networking (measure & manage performance of computer networks, implement efficient communication protocols, etc.)
Architecture: Cloud-native and edge-native architecture, microservices architecture; DevOps; CI/CD; Site Reliability Engineering (SRE)
Security: Network security (firewalls), data protection (authentication, encryption) and certifications
Database & analytics: Data storage & optimization

Edge Computing strategy: Use cases will drive edge adoption & define the technology/components used

Have a discovery phase and do a gap analysis to define edge and then build an edge portfolio
Define what kind of workloads, latency is needed; what kind of hardware will be used and what kind of network connectivity is needed
Bring in a unified control and management plane for on-prem, edge and cloud
Choosing the right components will be critical as also services and integration
Culture: Adopt a hybrid mindset; IT-OT teams need to work together
Define the outcomes you seek

You can watch the webinar here: https://www.youtube.com/watch?v=aRqumPOdBcI

NASSCOM reports on Edge Computing:

#edgecomputing #IoT #emergingtech #cloudcomputing #5G

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Diksha Nerurkar

Practice Lead - Strategy Group (Cloud, Future of Work)

I lead nasscom's Cloud Advocacy Program and the Future of Work initiative

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