Experience Superior Performance with Auto Scalable eNlight Managed Cloud
eNlight cloud gives you complete control and power to do more as you achieve superior performance on the World’s First Auto-Scalable cloud.
- Create on-demand Virtual Machines
- Reboot, Start and Shut down VMs, independently
- Deploy & assign resources dynamically
- Intelligent Auto Vertical and Horizontal Scaling
- Know Resource Usage before-hand, through eNlight's wise & Timely Predictions
- Pay Per Consume, eliminate the cost of unused resources
Register for eNlight cloud services by paying a one-time fee of Rs. 100 + GST which will be adjusted against your final cloud package amount once we begin your billing cycle.
eNlight Cloud Functions – Serverless : Use Cases
- Independent, concurrent, asynchronous, and easy to parallelize work units
- Infrequent demand, with random and huge scaling variation
- Stateless hence, temporary, without a primary need for immediate cold start duration
- Extremely dynamic due to varying business requirements which need accelerated development mechanism
Following are a few examples of application types that can run on eNlight Cloud Functions – Serverless platform.
Multimedia Processing
Example: Multimedia processing can be easily implemented on serverless platform. Certain examples include - processing an image on upload to build an index of elements that are present in the image after that image is uploaded on object storage repository, converting image / video / audio in different formats, Language translation after data is received.
Database Changes or Change Data Capture (CDC)
Example: Certain operations (mostly asynchronous) like logging activity, data post processing or data auditing can be performed in parallel to database changes along with the synchronous flow of execution.
IoT Sensor Input Messages
Example: IoT devices connected via network generate massive amount of data and network traffic. Functions can process this data generated by IoT devices which helps in balancing this workload and then later providing the processed data to applications and services downstream.
Stream Processing at Scale
Example: Stream processing involves performing operations like - read, transform, and then write - on messages sourced from infinite stream of messages like queue. Functions can be implemented which will be invoked by triggers to perform stream data processing.
Batch Jobs or Scheduled Tasks
Example: A batch of jobs or a task is an operation that needs to be executed periodically. Such functions can be scheduled timely and efficiently on a serverless platform.
Chatbots
Example: Chatbots can be implemented on serverless platform because of the fact that human-bot interaction does not require instantaneous response. Chatbots can efficiently scale on demand instead of maintaining an always-on daemon on some IaaS or PaaS platform.
HTTP REST APIs and web applications
Example: HTTP based web applications are a good fit to run on a serverless platform when workloads are non-transactional. As an example, an online exam application running in an event-driven environment uses serverless platform to generate results on demand.
