High Availability for applications.
This article is a comparision between cluster mode and serverless computing. Both are techniques to scale software deployments to meet the challenges of the increasing traffic from clients. Back of the envelope calculations for capacity and an inclination to treat software deployments as traditional have been common practice. It is time to wake up to lower costs with small changes in modes of deployment and application modularity
High availability clusters spin up additional nodes to handle the load. They scale out with fixed long running costs for nodes and continue till they are resized. The intervention to increase or decrease the number of nodes is independent of the demand and capacity fluctuations. All aspects of the node from compute to operating system and application stack involve maintenance chores for the application. The code for the application also takes on such routines as health checks, alerts and notifications.
Compare this with serverless computing where the resources required to execute the code is not only independent of the application but also dynamically provisioned and torn down so we pay as we go. Applications are already familiar with Platform as a service model and have shifted to deep divisions in application modularity with separate hardware and software for each module that is managed independent of the applications. This shift towards serverless computing also called Function as a service is only minimally more than the PaaS model because application have to organize their logic into smaller functions that can be executed without concern for resources. The applications also get to focus more on their actual business value rather than the mundane operation concerns.
The cluster model is hugely popular since it has shown a proven track record and tested software in cluster management. Cluster management also provides customized capabilities by way of dedicated nodes. The serverless computing is only provided by big cloud providers who can take away all the costs from our application by providing economies of scale. The serverless architecture may be standalone or distributed. In both cases, it remains an event-action platform to execute code in response to events. We can execute code written as functions in many different languages and a function is executed in its own container. Because these functions are asynchronous to the frontend and backend, they need not perform continuous polling which helps them to be more scaleable and resilient. OpenWhisk introduces event programming model where the charges are only for what is used.
The choice between the cluster and serverless computing also depends on the ability for the organizations to adapt. Clusters are easy to be provisioned on premise and on orchestration frameworks whereas the use of public cloud technologies has still not penetrated sufficiently within the organizations where they become mainstream mode of deployment. Some organizations also have genuine need for special purpose hardware racks and cannot truly be software defined.
This article is a comparision between cluster mode and serverless computing. Both are techniques to scale software deployments to meet the challenges of the increasing traffic from clients. Back of the envelope calculations for capacity and an inclination to treat software deployments as traditional have been common practice. It is time to wake up to lower costs with small changes in modes of deployment and application modularity
High availability clusters spin up additional nodes to handle the load. They scale out with fixed long running costs for nodes and continue till they are resized. The intervention to increase or decrease the number of nodes is independent of the demand and capacity fluctuations. All aspects of the node from compute to operating system and application stack involve maintenance chores for the application. The code for the application also takes on such routines as health checks, alerts and notifications.
Compare this with serverless computing where the resources required to execute the code is not only independent of the application but also dynamically provisioned and torn down so we pay as we go. Applications are already familiar with Platform as a service model and have shifted to deep divisions in application modularity with separate hardware and software for each module that is managed independent of the applications. This shift towards serverless computing also called Function as a service is only minimally more than the PaaS model because application have to organize their logic into smaller functions that can be executed without concern for resources. The applications also get to focus more on their actual business value rather than the mundane operation concerns.
The cluster model is hugely popular since it has shown a proven track record and tested software in cluster management. Cluster management also provides customized capabilities by way of dedicated nodes. The serverless computing is only provided by big cloud providers who can take away all the costs from our application by providing economies of scale. The serverless architecture may be standalone or distributed. In both cases, it remains an event-action platform to execute code in response to events. We can execute code written as functions in many different languages and a function is executed in its own container. Because these functions are asynchronous to the frontend and backend, they need not perform continuous polling which helps them to be more scaleable and resilient. OpenWhisk introduces event programming model where the charges are only for what is used.
The choice between the cluster and serverless computing also depends on the ability for the organizations to adapt. Clusters are easy to be provisioned on premise and on orchestration frameworks whereas the use of public cloud technologies has still not penetrated sufficiently within the organizations where they become mainstream mode of deployment. Some organizations also have genuine need for special purpose hardware racks and cannot truly be software defined.
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