1. Edge Computing
Edge computing, according to Gartner, refers to “a distributed computing topology where information processing is located close to the edge, where things and people produce or consume that information.” Cloudflare defines it as “a networking philosophy focused on bringing computing as close to the source of data as possible.” while TechTarget explains that is “a distributed information technology (IT) architecture in which client data is processed at the periphery of the network, as close to the originating source as possible.”
In cloud computing, resources and devices are managed through distant centralized networks or hyperscale cloud data centers that might be miles away from the core network; edge computing, on the other hand, enables data generation, management, and storage to be handled locally.
The edge approach provides the following benefits:
- Latency reduction
- Cloud load offsetting
- Running fewer processes in the cloud
- Increased deployment efficiency of a wide array of applications
- Decreased amount of long-distance communication between client and serve
- Excellent alternative for time-sensitive data
- Practical option where the connection is limited or non-existent
2. Scalable AI
Software Engineering Institute defines scalable AI as “the ability of algorithms, data, models, and infrastructure to operate at the size, speed, and complexity required for the mission.” This term puts emphasis on the system’s capacity to increase or decrease at scale, according to different needs or requirements.
Scalable AI architecture prepares organizations for rapid growths or sudden shifts such as new product launch, customer base expansion, or sudden increase in online sales. It also ensures fast decision speed under pressure, reliable throughput, and no lag time during crucial activities.
AI scalability has three dimensions:
- Administrative Scalability: a scalable system remains manageable regardless of the number of organizations that have access to it
- Geographic Scalability: a scalable system remains intact and useful regardless of the physical distance of users and resources
- Load Scalability: a scalable system has the overall computing power to increase its performance as needed
3. Serverless Computing
IBM defines the term as “a cloud computing execution model“ that provisions computing resources on demand and offloads all responsibility for common infrastructure management tasks (e.g., scaling, scheduling, patching, provisioning, etc.) to cloud providers and tools, allowing engineers to focus their time and effort on the business logic specific to their applications or process.”
To distinguish serverless computing from other computing models, here are its core attributes:
- This computing model runs machine resources in a stateless container, on-demand, and on a per-request basis.
- Serverless computing requires no operation and management of infrastructure, enabling developers to focus on new functionality, improve features, and optimize code
- In the serverless model, end users are charged only for the resources being used, never paying for idle capacity.
4. Multi Cloud
Multi-cloud, according to VMWare, is the use of “more than one public cloud service provider for virtual data storage or computing power resources, with or without any existing private cloud and on-premises infrastructure.”
This refers to the distribution, utilization, and management of applications, assets, software, and other cloud resources across several cloud environments. The goal of a multi-cloud architecture is to enable an organization not to have too much dependency on any single cloud provider or instance.
Multi-cloud service providers may host three types of services:
- Infrastructure as a Service (IaaS)
- Platform as a Service (PaaS)
- Software as a Service (SaaS)
5. Containerization
Containerization is a form of OS (operating system) virtualization to deploy and run applications in individual, standardized, isolated spaces called ‘containers’ – all using the same shared OS but without the need for systems or VMs (virtual machines) for each app. Taken from the logistics terms packaging container, a container is a fully encapsulated, independent, and portable computing environment.
Key benefits of containerization include:
- Seamless storage, retrieval, and transfer of images to satisfy traffic demands without losing potential visitors
- Able to run different types of applications on the same hardware node
- Maximum utilization and high application density of server resources
- Optimized CPU and memory usage with automatic vertical scaling of the current load
- Application upgrades and deployments can be done without issues
6. SASE (Secure Access Service Edge)
Gartner defines SASE as “a security framework prescribing the conversions of security and network connectivity technologies into a single cloud-delivered platform to enable secure and fast cloud transformation.”
The SASE security model provides the following benefits:
- Cost savings: No need to purchase and manage multiple point products
- Flexibility: Implementation and delivery of security services such as credential theft prevention, data loss prevention, DNS security, sandboxing, threat prevention, web filtering, and next-generation firewall policies
- Increased performance: Fast connection, instant access to apps, corporate data, and internet resources globally
- Reduced complexity: Consolidation of IT infrastructure into a cloud-based network security service model
- Zero Trust: Complete session protection when applications, devices, and users connect both online and offline
7. Strict Data Privacy Laws
Legislation is being created and passed to follow the lead of the European Union’s General Data Protection Regulation (GDPR) in terms of putting an end to the wild west of information sharing and taking seriously issues such as cybersecurity, data breaches, and privacy.
By 2023, personal information of at least 65% of the world’s population will be covered under a privacy regulation.
- Consumers expect companies to make their third-party service providers accountable in terms of keeping private data from exposure.
- Over 50% of customers would patronize businesses that put high value to protecting consumer data.
- By 2022, more than $8 billion privacy-driven investment will be made for improving data sharing practices and compliance.
- Organizations to fully transition to a more long-term remote workforce will have to modernize their infrastructure, keep up with regulatory requirements, and uphold strong cybersecurity rules against data storage issues.
Looking Ahead
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