Evaluate your SIEM
Get the guideComplete visibility for DevSecOps
Reduce downtime and move from reactive to proactive monitoring.
Platform-as-a-service (PaaS) is a cloud service delivery model where a third-party cloud service provider delivers some hardware and software tools, often those needed for application hosting or development, to customers over the internet. The key benefit of the PaaS model is that users can access hardware and software to develop and run applications without having to purchase, install and maintain the infrastructure.
Organizations adopting a SaaS solution outsource their entire technology stack and the associated maintenance costs to a third-party provider. PaaS, in contrast, does not typically replace an organization's entire IT infrastructure. Instead, it helps organizations access key services with minimal start-up costs and reduced time to deployment.
Common PaaS functionality
PaaS products are generally geared towards software development, providing users with resources such as computing power and data storage capacity on demand, along with functions like version management, text editing, testing services and more. A PaaS product can also facilitate collaboration between geographically distant team members, allowing them to access the same development environment from separate locations.
PaaS pricing models
PaaS providers typically price their services using a pay-per-use model. But usage can be calculated in different ways, depending on the vendor. One vendor might charge a fixed rate per user based on a limited number of custom integration objects. Another vendor might charge based on the number and speed of servers and the overall bandwidth used. The usage of computing instances, the volume of data storage required on the platform and the amount of outbound traffic are all typical factors when determining the price of a PaaS subscription.
PaaS, SaaS and IaaS represent the three most common models for service delivery in cloud computing and the three most readily available alternatives to full on-premise IT infrastructure deployment. The difference between each cloud computing model is based on the portions of the technology stack outsourced to a third-party vendor and which functions are managed in-house.
Common SaaS products include Google Apps, Dropbox, Salesforce, GoToMeeting and Concur. These software products can be accessed through the internet based on a monthly subscription fee. When organizations contract for SaaS services, the software vendor manages every part of the technology stack required to host and deliver the application. This includes the application itself, data, runtime, middleware, the operating system, virtualization, servers, storage and networking functions.
Windows Azure, Google App Engine and Heroku are among the leading PaaS solutions. Companies licensing or subscribing to PaaS products outsource all of the hardware components and some of the software components of the technology stack. While the application and data storage/management functions are maintained in-house, all other functions are provided by a third-party vendor. PaaS products and solutions are most popular among application developers, as they can focus on the development of the application while the rest of the stack is managed.
The final category of cloud computing services is infrastructure-as-a-service (IaaS). In this model, the customer is leasing only the hardware and maintaining the entire software stack in-house, including the operating systems, middleware, runtime, data and applications.
Containers-as-a-service (CaaS) is a special type of IaaS where the customer leases a system for creating and managing containers and container clusters instead of leasing physical hardware.
PaaS for application development
PaaS products offer the computing infrastructure, storage capacity and features that software development teams need to reduce product development costs and coding overhead. Many PaaS products include built-in software components that can be integrated into new applications, such as a search function, security features, predefined workflows and directory services. PaaS services are often designed to meet the web application development life cycle’s needs, including building, testing, application deployment, management and updates.
PaaS geographically distributed teams
PaaS is a cloud-based service, meaning customers access the service via the internet. This means that even geographically distributed software teams can enjoy equal access to the development environment regardless of their locations. Team members can easily access the system while traveling and streamline collaboration between employees that may not have the luxury or convenience of working in the same office.
PaaS private cloud strategy
A private cloud environment consists of IT infrastructure that is used exclusively by one business. The infrastructure could be developed and implemented in-house, or it could be operated by a third party. But in either case, all of the services deployed on a private network can be customized and secured to meet specified requirements.
Enterprise IT organizations are incorporating private PaaS into their overall cloud strategies to enable cloud deployment for new and existing applications, develop microservices and move towards a hybrid cloud architecture. IT organizations that implement private PaaS solutions typically maintain those systems through their IT operations team. Meanwhile, a separate DevOps team leverages the system to enable smoother and faster application development and testing.
Sumo Logic provides cloud integration and infrastructure performance monitoring at scale. Unify your logs, metrics, and events from AWS, Azure, and GCP with public, hybrid, and multi-cloud monitoring from Sumo Logic. Eliminate blind spots with full support for apps, services, modern architectures and integration with your favorite cloud monitoring tools. Sumo Logic enables IT organizations to be proactive in identifying critical cloud application problems by easily correlating performance issues with errors and failures. Get to the root cause quickly with pattern detection using machine learning.
Reduce downtime and move from reactive to proactive monitoring.