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Serverless computing has received considerable recognition in the technology community recently and may become the norm going forward.
While serverless doesn't imply there will be no servers present. Rather, this architecture provides developers or service users with an abstraction layer over servers, operating systems, and infrastructure resources.
Serverless architecture makes server management hassle-free and your vendor handles everything. Undoubtedly, this trend represents an important evolution within cloud technology.
Serverless Computing: What Is It?
Assuming our serverless application has been developed and deployed onto servers after being designed, there are usually two costs involved with its deployment: CAPEX refers to upfront expenses associated with capacity planning, hardware/software installations on servers, procurement of required supplies while OPEX are operating expenses.
Both may be partially alleviated using cloud technology but the financial burden persists. Nonetheless serverless computing eliminates such challenges altogether by eliminating low-level configuration details as well as infrastructure overhead for user interface.
Serverless computing refers to an execution model in the cloud whereby providers bill users for allocating compute resources and storage for specific code pieces as needed, freeing users of responsibility associated with maintaining servers themselves.
While no servers themselves exist within serverless environments, providers handle all aspects related to provisioning and maintenance for them on behalf of user experience allowing for greater freedom and productivity when building infrastructure for applications that rely on serverless technologies such as serverless.
Event-driven design and development in serverless computing provide for flexible resource usage.
Code is only called upon request from users and rather than paying an up-front monthly fee, they only pay for services they actually utilize based on what their design process dictates - while resources remain intact due to no server access restrictions or usage issues.
Simply stated, serverless computing resources involve uploading a function and specifying its required resources before uploading to Amazon, Microsoft or Google Cloud functions for configuration/set up by these providers.
This leaves nothing for users to worry about because everything is handled serverlessly by these cloud providers in terms of provisioning/decommissioning servers as per fluctuation demand fluctuations - for the end user authentication it all remains transparent.
What Distinguishes Serverless Computing From Paas?
PaaS is similar to FaaS or serverless computing in that many of its advantages can also be found in it. Both services eliminate the requirement to manage server hardware and software separately while still offering unique advantages based on application development, deployment and scaling needs.
These main distinctions highlight some important considerations between them when choosing which service best meets your requirements.
PaaS enables applications to be developed normally and deployed as one unit. Then scale is performed across the board for its deployment, so an extra load may require running multiple instances of it simultaneously.
FaaS is an application made up of numerous, independent functions. FaaS providers host each function according to how often it's being called up, scaling them accordingly. You don't pay extra to keep multiple instances running continuously like with PaaS.
Important Serverless Computing Principles
Event-Driven Design (EDD): Event-Driven Design (EDD) in serverless apps uses small pieces of code known as functions that can be activated based on events like HTTP requests, data changes or tasks being scheduled - this promotes both modularity and scalability for serverless services.
Auto-Scaling: Serverless architecture's key advantage lies in its capacity for autoscaling cloud providers dynamically allocate resources according to demand in your app, thus eliminating manual scaling requirements and providing more cost-efficient results than manual solutions.
Pay-Per-Use Model: With a serverless pay-as-you-go pricing model, costs for compute resources used by your functions may fluctuate according to actual use versus being pre-allocated potentially providing savings and cost reduction opportunities especially with application code variable workloads.
Models Of Serverless Computing
Serverless infrastructures encompass two primary concepts.
Functions As A Service (FaaS)
FaaS operates through events. Additionally, serverless architectures use serverless architectures as ongoing asynchronous tasks with application developers writing server-side logic directly onto it unlike conventional architectures though it operates entirely stateless compute containers managed by third parties that trigger events when needed (AWS Lambda being one such FaaS service provider).
FaaS offerings don't rely on any specific framework or library when developing them - instead they consist of standard language and environment applications written using any programming language imaginable - from Javascript, Go, Python or any JVM language (Java Scala Clojure etc) up to AWS Lambda functions compiled for Unix processes as part of deployment artifact.
Backend As A Service (BaaS)
Backend as a Service allows clients to communicate directly with its data layer via authentication layer, without needing server-side custom logic being written rather it relies on client interaction for interaction and connection to be successful.
Which Core Technologies Underlie The Serverless Model?
Three technological components comprise serverless computing:
- An automatically scalable execution platform.
- A scalable code execution workflow system.
- An event routing engine for pub/sub.
Clients can run code without storing data thanks to serverless computing platforms. Thus, in the majority of instances, it provides services for -
- Databases
- Keepsake
- Function-as-a Service (FaaS)
Important Attributes And Advantages Of Serverless Computing
Some advantages of serverless computing architecture may also include:
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No server management: When it comes to maintaining and managing their servers, service users do not have a say in this matter.
Serverless platforms offer integrated services which are fully managed, automatically scalable, fault-tolerant and support elasticities provided by cloud service providers that make developer activity much more productive than ever before.
- Event-driven computing: Serverless computing allows for event-driven application solution scaling by adapting business logic as soon as a particular event triggers, for instance when files are uploaded into data storage a certain piece of code will run automatically.
- High availability: Serverless framework applications typically feature built-in fault tolerance and availability features for increased uptime and continuity.
- Pay as you go model: Serverless computing provides users with a cost structure to avoid paying for instances when no code is being utilized by their machine.
- Faster availability in the market: Thanks to serverless model models' inherent characteristics that increase productivity, which speed up time-to-market for services or products more rapidly.
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Scalability: To enable growth and scalability, the serverless architecture uses flexibility as its cornerstone.
Users can utilize whatever services are necessary from cloud platforms regardless of their business size; users will no longer have to endure lengthy data migration processes as their business expands.
- More focused job: Developers can be more productive when writing code as they no longer must deal with infrastructure and maintenance tasks instead they are freed up to concentrate on offering their chosen service in more depth.
Cloud Development Hurdles
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Security concerns: To give cloud vendors control of serverless architecture services is certainly a boon, yet this raises security issues relating to application data.
With personal information kept on vendor-assigned servers and code execution shared among tenants, leakage risks become real threats - particularly given how frequent broken authentication issues arise when certain functions expose public web APIs that allow public consumption as well as events from various sources with unapproved authentications are consumed by wide range of tenants.
- Testing and debugging is a real challenge: Developers find it challenging to conduct thorough tests when there is no control of backend services and the app has multiple functional units that need testing/debugging simultaneously.
- There is a concern with the pay-as-you-go model: While serverless computing provides cost-saving and benefit calculations that stack up well against conventional cloud infrastructure costs, sometimes paying by the month could exceed its effectiveness altogether.
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Vendor Lock-in: Relying solely on one vendor offers several advantages in terms of reliability.
However, switching vendors could prove costly as every provider may employ different processes and workflows that make switching much harder than it needs to be.
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EDA-Based Programming: Serverless cloud computing models rely heavily on event-driven architecture(EDA), in which applications are designed with multiple functions connected through architecture.
If, during serverless solution design, however, use cases become complex we must take an alternative approach as debugging EDA programming becomes harder consequently leading to architecture with harder logic flows and complexity in its final form.
- Complex: Serverless programming can be agile so long as programmers follow its model but if developers go against its dictates, complexity arises that may prevent serverless from becoming viable in certain use cases.
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Latency Challenges: One challenge associated with serverless computing is managing state using stateless functions.
Databases, messaging systems and shared file systems all serve as platforms where state can be stored according to current architecture best practices.
Serverless also has two categories of latency concerns - cold starts and high tail latencies.
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Lack of Standards: The adoption of serverless computing can be jeopardized by its lack of standards and concerns over vendor lock-in.
Here, serverless functions themselves do not represent a significant difficulty rather it lies with all of the platform services needed by them and abstracting those away is challenging.
- Conflict with DevOps: In Serverless computing paradigms, software developers don't necessarily need to understand all system requirements for the code they create - an essential aspect of DevOps that ensures both developers and operators share an understanding of one another's requirements.
Conclusion
Serverless computing may only have recently made headlines, yet its impact has already been felt throughout industries and businesses worldwide.
According to Gartner research, serverless computing will become mainstream within two years - over 20% of businesses plan to adopt serverless technology by 2025 according to another study.
Although serverless architecture provides several benefits, its implementation strategy will depend on each use case and present unique challenges.
Serverless computing adoption may be useful if resources are scarce but for complex apps proper system architecture must also take place to make serverless useful for its intended use case. As with other emerging technologies, blockchain will develop gradually over time to eventually provide businesses with the solutions they require.
