Server-Based Computing

Introduction to Server-Based Computing

Server-based computing refers to a centralized model where end-user devices access computing resources, applications, and data that are hosted on remote servers. Instead of programs and files being stored locally on desktops or laptops, everything resides in a data center accessed over a network. This approach offers important benefits but also comes with drawbacks to consider.

Definition and Overview

With server-based computing, desktop clients act primarily as input/output devices for software running on back-end servers. Processing, storage, printing, and other workflow elements are handled in a data center rather than on local devices. The end user leverages thin client hardware or remoting protocols to connect.

Server-based computing relies on centralized infrastructure in data centers to deliver shared services and data to many end users connecting remotely.

This model allows IT teams to deliver services, standardize environments, enforce policy, and manage upgrades and security centrally. Server-based computing also enables on-demand scalability to support more users without provisioning new devices.

Core components include centralized data storage, virtualization, workload distribution across servers, and streaming application delivery. Network connectivity ties everything together between client and server.

History and Evolution

Mainframe computers in the mid-20th century were early examples of server-based environments accessed via dummy terminals. However, the concept did not gain broader traction until the 1990s with the rollout of services like America Online (AOL) and the popularization of the World Wide Web.

Vendors began offering software distribution platforms and virtualization to facilitate server-based services. Improved networks, cheaper server hardware, and bandwidth-heavy applications accelerated adoption in the 2000s with the rise of cloud computing.

Technologies like virtual desktop infrastructure (VDI), remote desktop services (RDS), and workspace streaming have expanded implementation use cases. Reliance on this computing model continues to increase dramatically.

Benefits and Drawbacks

Server-based computing offers noteworthy advantages but also some limitations to factor:

• Centralized data storage and backup
• Streamlined IT management
• Universal accessibility
• Scalability
• Business continuity
• Enhanced security
• Decreased client resource needs
• Flexibility and mobility

• Dependence on network availability
• Contention for shared resources
• Limited offline functionality
• Upfront infrastructure investments
• Multi-user performance lags

Understanding this tradeoff is key for organizations evaluating server-based approaches.

How Server-Based Computing Works

Server-based environments rely on a client-server framework where remote desktops and devices connect to centralized IT infrastructure over a LAN or WAN. Specialized software and algorithms enable robust functionality despite limited local processing.

Client-Server Model

Server-based computing employs a classic client-server model. Users leverage lightweight client devices and protocols to access applications hosted on back-end servers or server infrastructure.

This splits up computing tasks between local and remote tools based on their roles:

• Initiate requests for services
• Handle user interface and input/output
• May process lightweight logic
• Stream data from servers

• Store programs and data
• Run resource-intensive applications
• Process rendering, encoding, etc.
• Manage access controls and licensing

Separating front-end and back-end responsibilities delivers simplified management, shared services, and centralized infrastructure.

Thin clients and thick clients represent two endpoint implementation strategies:

Thin Clients

Thin clients only provide essential connectivity, using individual servers for applications, processing, and storage. Screens, keyboards, and network adapters make up their hardware.

Thin clients don’t need local hard drives or active cooling. With fewer components, they easily connect users while simplifying security patches and upgrades. Most processing happens on servers.

Thick Clients

Thick clients have more onboard compute resources, like multicore CPUs and GPUs. This allows them to handle certain rendering or visualization tasks locally via installed software, reducing server demands.

But they cost more, have higher failure rates, complicate management, and may access both local and remote applications. Achieving standardization is difficult.

Virtualization and Cloud Computing

Virtualization now plays a major role in delivering server-based services. By abstracting server hardware and resources, virtual machines allow workloads to share infrastructure.

Cloud computing takes this a step further by provisioning shared technology resources on-demand over the internet. Cloud IaaS, PaaS, and SaaS offerings all leverage massive server farms with enormous scales of computing power and storage capacity.
These technologies enable server-based computing at the global scale to drive flexibility and efficiency.

Centralized Data Storage

Instead of local file servers or PC hard drives, server-based infrastructures utilize centralized SAN, NAS, hyper-converged, software-defined, or cloud storage. Endpoint connectivity protocols facilitate access.

This approach simplifies backup/recovery, pooling of capacity, storage tiers, security policy enforcement, and data lifecycle management without heavy client-side assets.

Application Streaming

Optimized streaming allows the execution of intensive applications remotely without needing the full client-side software footprint. Tasks are split to reduce bandwidth demands.

Each time a user opens an application, they connect to a fresh virtual instance dedicated to that session. Files and settings often persist across logins depending on the platform and application architecture.

Key Components and Technologies

Several core infrastructure building blocks and innovations underpin server-based environments and performance.

Servers

Servers provide the computing foundation for delivering shared services, saving files, streaming applications, and running virtual desktops. They require scalable CPUs, abundant RAM, fast storage, and redundant power supplies.

Rack servers are easily added into standardized data center environments. High core counts aid virtualization, while fast SSD cache speeds delivery to many concurrent users.

Network Infrastructure

A fast, resilient, low-latency network is mandatory for good server-based computing user experiences. Slow speeds or congestion make applications laggy and unresponsive.

Topologies usually include multilink connectivity, meshed high-speed switches, Wi-Fi controllers, and ample bandwidth per endpoint from ISPs (1 Mbps per user or more). Quality of service tools improve delivery.

Virtualization Software

Hypervisors like VMware ESXi, Microsoft Hyper-V, Citrix XenServer, and tools for containerization allow abstraction and sharing of server resources between client sessions. This makes scaling manageable.

Automation ensures load balancing between servers and provisions new resources quickly during surges, optimizing consolidation ratios. Templates standardize desktops.

Bandwidth and Latency Considerations

While networks accelerate, applications and user loads grow fast too. When designing server computing capacity, overprovision bandwidth by at least 25-50% more than peak needs to account for future growth.

Latency under 150 ms makes apps feel responsive. WAN optimization and edge computing minimize lag by positioning key data closer to end users. Caching also improves performance.

Implementation in Organizations

Enterprise implementation options feature pros and cons around flexibility and control. Security and costs are key decision factors too when transitioning services into server environments.

On-Premises vs Cloud-Hosted

Server-based infrastructure can be built internally using enterprise data centers, or externally leveraging public cloud platforms. Blending both strategies has become more popular for accommodating variable workloads.

On-premises investments allow full customization and avoid recurring fees, but require sizable capital outlays especially early on. Public clouds offer subscription-based operating expenditures and elastic capacity.

Regulatory factors around data jurisdiction, privacy laws, or industry constraints may dictate one direction or the other when choosing deployment venues.

End User Experience

Well-designed server computing platforms feel responsive to end users, facilitating remote knowledge work. Employing thin clients enhances consistency; thick clients improve speed for complex tasks.

WAN optimization, quality assurance testing, and help desk support ensure solid experiences for a distributed workforce. User self-service also eases IT burdens.

Profile management synchronizes settings across sessions. Single sign-on and standard desktop images aid productivity by allowing staff to access apps quickly from any device.

Security and Compliance

Consolidating data into centralized repositories simplifies applying cybersecurity controls, like multifactor access requirements, data loss prevention tools, and network monitoring. Routine patches are rolled out faster.

However, compromised credentials could give attackers deeper access across shared systems. Carefully restricting permissions and auditing activity is crucial.

Cloud usage may require additional management to confirm regulatory alignment on issues like data jurisdiction, privacy rules, and platform certifications.

Cost Savings

While launching server-based services necessitates large initial infrastructure investments, over time increased utilization efficiency, smaller software/hardware refresh cycles, and avoiding future capital purchases generate considerable cost reductions and labor savings.

Other savings come from consolidating help desk troubleshooting, leveraging automation, rightsizing hardware needs, and consuming compute resources on-demand from cloud platforms. Replacing PC refresh cycles with thin client improvements creates long-term savings.

Use Cases and Applications

Many usage scenarios can benefit from server-based computing. Some examples include:

Call Centers

Call center productivity relies on fast, reliable access to central customer databases. Server-based virtual desktops allow remote support reps seamless connectivity. Shared infrastructure curbs costs while the organization scales.

Software Development

Centralized development environments allow programmers to mimic production infrastructure accessed anywhere. Streamlined provisioning facilitates testing. Lower capacity endpoints keep costs reasonable despite processing complexity.

Computer Labs

Serving temporary users from a common server pool improves the availability of specialty software. Students can access high-compute tools like CAD, data science notebooks, or compilers without local installations.

Disaster Recovery

Backing up data remotely and accessing virtual desktops from unaffected sites maintains business continuity when disasters strike. Users shift locations rather than required local failover infrastructure.

Challenges and Issues

While adopting server-based computing enables simplification plus greater mobility and flexibility, dependencies on networks – along with other inherent drawbacks – can hinder success if not adequately addressed upfront.

Dependence on Connectivity

Heavy reliance on WAN/LAN connectivity makes uptime critical. Instability or outages severely impede end-user workflows and productivity. Redundant links, alternative authentication methods, and continuity planning help bridge gaps.

Multi-User Resource Contention

Shared infrastructure contention from simultaneous users creates resource starvation risks under heavy workloads. Careful monitoring and capacity planning – with overprovisioning margins to accommodate inevitable growth – help substantially.

Limited Local Processing Power

Thin client devices lack local computing horsepower for handling intensive creative, design, analytical, or scientific tasks. This can constrain capabilities or necessitate supplemental thick client solutions.

Initial Infrastructure Investments

Procuring server hardware, networking upgrades, and virtualization software licenses demands major upfront capital expenses before factoring in the technical staff for implementation. Transitioning fully to a server-based model calls for organizational commitment across budget cycles. Cost reductions materialize later to offset these platform costs through improved utilization efficiency.

Trends and Future Directions

Continued technology improvements around automation, cloud adoption, and connectivity speed offer opportunities to enhance server computing capabilities while minimizing pain points customers still encounter.

Emergence of DaaS

Desktop-as-a-Service (DaaS) builds on virtual desktop infrastructure (VDI) by allowing fully cloud-hosted environments rather than local server ownership. This streamlines management overhead for delivering desktop experiences.

Increasing Adoption of SaaS

Software-as-a-Service (SaaS) replaces traditional software purchasing with subscription models for accessing apps over the internet. It provides a logical transition for shifting services into server environments and public cloud platforms.

Growth in Edge Computing

Edge computing reduces latency by positioning key data closer to users. As 5G networks roll out, this trend will alleviate previous constraints around server proximity and real-time application responsiveness over distances.

Better Management Capabilities

Advancements in intelligent provisioning, usage insights, and automation will simplify server-based computing delivery while enhancing consistency, compliance, and problem resolution. Techniques like AI ops (AIOps) show particular promise here.

Conclusion

Review of Server-Based Computing

The server-based computing model offers compelling advantages around mobility, business agility, resilience, and total cost of ownership. Transitioning from decentralized approaches enables access to scalable, secure enterprise-grade infrastructure.

However, dependencies on connectivity pose business continuity risks if outages arise. Upfront platform costs also represent a barrier, although long-term utilization efficiency gains combined with falling server prices are improving affordability.

Ongoing technology improvements around virtualization, the cloud, edge computing, and automation will provide easier paths to server computing adoption while curbing disadvantages.

Key Takeaways for Businesses

Any organization evaluating server-side solutions should focus on user experience benchmarks, tools integration, storage architecture, continuity safeguards, and staged transitional strategy.

Prioritizing latency, quality assurance, and functionality early in testing will highlight performance gaps needing remediation beforehand Goals should emphasize delivering responsive, consistent, and intuitive services.

Approaching modernization efforts gradually in phases allows for smoothing out issues at a smaller scale while freeing up existing local hardware for only the most demanding use cases where needed. For many enterprises today, server-centric setups represent the optimal approach to balancing productivity, budgets, and administrative overhead.

FAQs

What are some examples of server-based computing?

Some common examples include web-based email, cloud storage services, SaaS applications like Office 365 or Salesforce, and virtual desktop infrastructure (VDI).

What are the main benefits of server-based computing?

Key benefits include central data storage, easier application management, universal accessibility, scalability, business continuity, security, lower client-side computing requirements, and flexibility.

What are some alternatives to server-based computing?

Alternatives include peer-to-peer networking, standalone desktop applications, local storage, on-premises infrastructure, and edge computing approaches.

Is server-based computing more secure?

Generally, yes – centralized security management, regular updates, controlled access, encryption capabilities, and professional IT oversight improve security. But poor configurations or compromised credentials can undermine these protections.

What does the future look like for server-based computing?

Server-based computing will likely continue growing in popularity. Emerging trends like DaaS, SaaS, intelligent automation, and 5G connectivity will enable more centralized, flexible computing with lower latency. Hybrid models blending cloud and local computing resources may prevail.