6.4 Serverless computing and Function as a Service (FaaS)
4 min read•august 14, 2024
Serverless computing revolutionizes cloud infrastructure by eliminating server management. Developers focus on code, while providers handle scaling and resources. This model aligns with DevOps principles, enabling rapid iteration and continuous delivery.
is a key component of serverless computing. It allows developers to run individual functions in response to events, offering granular and pay-per-invocation pricing. FaaS is ideal for data processing, APIs, and event-driven architectures.
Serverless Computing and DevOps
Benefits of Serverless Computing for DevOps
Top images from around the web for Benefits of Serverless Computing for DevOps
A beginner's guide to building DevOps pipelines with open source tools | Opensource.com View original
Is this image relevant?
GitLab - a Complete DevOps Platform | GitLab View original
Is this image relevant?
FaaS on Kubernetes - IMTI - Craig Johnston View original
Is this image relevant?
A beginner's guide to building DevOps pipelines with open source tools | Opensource.com View original
Is this image relevant?
GitLab - a Complete DevOps Platform | GitLab View original
Is this image relevant?
1 of 3
Top images from around the web for Benefits of Serverless Computing for DevOps
A beginner's guide to building DevOps pipelines with open source tools | Opensource.com View original
Is this image relevant?
GitLab - a Complete DevOps Platform | GitLab View original
Is this image relevant?
FaaS on Kubernetes - IMTI - Craig Johnston View original
Is this image relevant?
A beginner's guide to building DevOps pipelines with open source tools | Opensource.com View original
Is this image relevant?
GitLab - a Complete DevOps Platform | GitLab View original
Is this image relevant?
1 of 3
- Serverless computing is a cloud computing model where the cloud provider manages the infrastructure and automatically allocates resources based on the demand of the application
- Developers focus solely on writing and deploying code without worrying about the underlying infrastructure, such as server management, scaling, and capacity planning
- Offers benefits such as automatic scaling, pay-per-use pricing, reduced operational overhead, faster development and deployment cycles, and improved cost-efficiency
- Well-suited for event-driven and stateless applications, as well as tasks that require sporadic or unpredictable workloads (data processing, IoT data ingestion)
- Aligns with DevOps principles by enabling rapid iteration, continuous delivery, and a focus on application development rather than infrastructure management
Serverless Computing Architecture and Use Cases
- Serverless architectures are composed of loosely coupled functions that communicate through well-defined interfaces and events, allowing for independent scaling and deployment
- Functions should be designed to be small, focused, and stateless, with minimal dependencies and fast startup times to optimize resource utilization and reduce costs
- Leverage event-driven patterns, such as asynchronous processing, message queues (AWS SQS), and event sourcing, to decouple components and enable scalability
- Proper function granularity and separation of concerns are important to avoid function sprawl and maintain maintainability and testability
- Designed with fault tolerance and resilience in mind, using techniques like retries, dead-letter queues, and idempotent operations to handle failures gracefully
Function as a Service (FaaS)
FaaS Concept and Characteristics
- Function as a Service (FaaS) is a subset of serverless computing that allows developers to execute individual functions or pieces of code in response to specific events or triggers
- FaaS platforms provide a runtime environment where functions can be executed without the need to manage the underlying infrastructure or server instances
- Functions in FaaS are typically stateless, short-lived, and event-driven, meaning they are triggered by specific events such as HTTP requests, database changes, or message queue events
- Offers benefits like granular scalability, pay-per-invocation pricing, rapid development and deployment, and the ability to compose and orchestrate functions to build complex applications
FaaS Use Cases and Examples
- Suitable for use cases such as data processing, real-time stream processing, serverless APIs, webhook handlers, IoT data ingestion, and event-driven architectures
- Examples:
- Processing and resizing uploaded images in a web application
- Handling webhook events from external services (payment gateways, version control systems)
- Real-time data processing and aggregation from IoT devices
- Implementing serverless APIs and
Implementing Serverless Functions
Cloud Platform FaaS Offerings
- Major cloud platforms such as , , and provide FaaS offerings for implementing and deploying serverless functions
- To implement a serverless function, developers write the function code in a supported programming language (JavaScript, Python, Java) and specify the event triggers and configurations
- Cloud platforms provide SDKs, CLI tools, and web consoles for deploying and managing serverless functions, allowing developers to package and upload function code along with its dependencies
Function Triggers and Integrations
- Serverless functions can be triggered by various event sources, such as HTTP API requests, cloud storage events (S3 object uploads), database changes, message queues, or scheduled events
- Cloud platforms handle the automatic scaling, provisioning, and management of the underlying infrastructure required to execute the serverless functions based on the incoming event load
- Serverless functions can be integrated with other cloud services, such as API gateways, databases (DynamoDB), storage (S3), and messaging services (SNS, SQS), to build complete serverless applications
- Examples:
- Triggering a function to process data when a new file is uploaded to an S3 bucket
- Invoking a function through an API Gateway to handle HTTP requests and responses
Serverless Application Architecture
Designing Serverless Applications
- Designing serverless applications requires a different approach compared to traditional monolithic or microservices architectures, focusing on event-driven and stateless components
- Cost optimization strategies include rightsizing function memory and timeout settings, using cost-effective event sources, and implementing efficient data access patterns
- Monitoring, logging, and tracing are crucial for serverless applications to gain visibility into function executions, diagnose issues, and optimize performance and cost
Scalability and Cost-Efficiency Considerations
- Serverless applications automatically scale based on the incoming event load, allowing for efficient utilization of resources and cost savings
- Pay-per-use pricing model ensures that costs are incurred only when functions are executed, making it cost-effective for applications with variable or unpredictable workloads
- Proper function granularity and separation of concerns help in optimizing resource utilization and reducing costs
- Implementing efficient data access patterns, such as caching and minimizing data transfer, can further optimize costs in serverless applications
- Examples:
- Building a scalable web application using serverless functions for backend logic and API Gateway for handling HTTP requests
- Implementing a serverless data processing pipeline that scales automatically based on the volume of incoming data
Key Terms to Review (19)
AWS Lambda: AWS Lambda is a serverless computing service provided by Amazon Web Services that allows users to run code in response to events without provisioning or managing servers. It simplifies application development by automatically scaling resources and managing the execution environment, enabling developers to focus on writing code rather than infrastructure management.
AWS SAM: AWS SAM, or AWS Serverless Application Model, is an open-source framework that simplifies the development and deployment of serverless applications on AWS. It allows developers to define serverless resources like functions, APIs, and event sources in a simple YAML file, streamlining the process of creating, testing, and deploying applications using serverless architecture and Function as a Service (FaaS). AWS SAM integrates seamlessly with other AWS services, making it easier to build scalable and cost-effective applications without managing servers.
Azure Functions: Azure Functions is a serverless compute service provided by Microsoft Azure that allows developers to run event-driven code without the need to manage infrastructure. This enables the creation of small pieces of code, or 'functions', that can respond to various events such as HTTP requests, timers, or messages from other services, making it an essential tool for deploying and managing applications in the cloud.
Blue-green deployment: Blue-green deployment is a release management strategy that reduces downtime and risk by running two identical production environments, referred to as 'blue' and 'green'. One environment is live and serving all traffic while the other is idle, allowing for seamless switching between versions without impacting users.
Canary Release: A canary release is a software deployment strategy that allows for testing a new version of an application in a controlled manner, by releasing it to a small subset of users before rolling it out to the entire user base. This approach minimizes risk and enables teams to gather feedback and monitor performance on a smaller scale, ensuring that any potential issues can be identified and resolved early in the process.
Cold start: A cold start refers to the initial delay experienced when a serverless function or service is invoked for the first time after a period of inactivity. This phenomenon occurs because the cloud provider needs to allocate resources, set up the runtime environment, and load the function code, which can result in latency compared to subsequent invocations that use pre-warmed instances.
Cost Efficiency: Cost efficiency refers to the ability to deliver services and products while minimizing expenses and maximizing value. This concept is especially crucial in technology, where organizations seek to optimize resource use and improve operational effectiveness, making it essential in both cloud computing models and serverless architectures.
Data Protection: Data protection refers to the process of safeguarding important information from corruption, compromise, or loss. This concept is crucial in ensuring that data remains confidential, accurate, and available, particularly in environments where data is processed and stored, such as serverless computing and Function as a Service (FaaS) architectures, where traditional security measures may not apply directly due to the nature of cloud-based solutions.
Event-driven architecture: Event-driven architecture is a software design pattern where the flow of the program is determined by events, which can be defined as any significant change in state. This approach allows different components to communicate and react to these events asynchronously, promoting scalability and flexibility. It plays a crucial role in serverless computing and Function as a Service (FaaS) environments, where services are invoked based on events like user actions or system triggers.
Function as a Service (FaaS): Function as a Service (FaaS) is a cloud computing service model that allows developers to deploy individual functions or pieces of code in the cloud without managing the underlying infrastructure. This model enables automatic scaling and a pay-as-you-go pricing structure, meaning users only pay for the compute time their code actually uses. FaaS is a key aspect of serverless computing, where developers can focus on writing code instead of worrying about server management, making it an attractive option for building microservices and event-driven architectures.
Google Cloud Functions: Google Cloud Functions is a serverless execution environment that allows developers to run code in response to events without the need to manage the underlying infrastructure. It enables the deployment of single-purpose functions, which can be triggered by various events from other Google Cloud services, making it an essential tool in the serverless computing landscape.
Identity and access management: Identity and access management (IAM) refers to the framework of policies and technologies that ensure the right individuals have the appropriate access to technology resources at the right times for the right reasons. It plays a crucial role in enhancing security, managing user identities, and providing seamless access control within cloud platforms and serverless computing environments. IAM not only streamlines user access but also helps organizations comply with regulatory requirements by managing user permissions effectively.
Latency: Latency refers to the time delay experienced in a system when processing requests or data. It is a critical factor in system performance, particularly in serverless architectures and Function as a Service (FaaS) where quick execution is essential. High latency can lead to slower response times and reduced user satisfaction, making it crucial to monitor and optimize for low latency in applications and infrastructure.
Microservices: Microservices are a software architecture style that structures an application as a collection of small, independently deployable services, each running a unique process and communicating through well-defined APIs. This approach allows for improved scalability, flexibility, and maintainability of applications by enabling teams to develop, test, and deploy services independently.
Scalability: Scalability is the ability of a system to handle increased load or demand by adding resources without compromising performance. This concept is crucial in modern technology, as it allows businesses to grow and adapt to changing requirements effectively. Scalability can be achieved through vertical scaling (adding more power to existing machines) or horizontal scaling (adding more machines), and it plays a significant role in maintaining efficiency and reliability across various platforms and architectures.
Serverless architecture: Serverless architecture is a cloud computing model that enables developers to build and run applications without managing the underlying infrastructure. In this model, the cloud provider automatically handles the server provisioning, scaling, and maintenance, allowing developers to focus solely on writing code. This approach enhances efficiency and scalability, particularly when integrated with Function as a Service (FaaS), where applications are divided into discrete functions triggered by specific events.
Serverless Framework: The Serverless Framework is an open-source framework designed to build and deploy serverless applications across various cloud platforms. It abstracts the infrastructure management, enabling developers to focus on writing code while seamlessly integrating with Function as a Service (FaaS) offerings. This framework simplifies the deployment of microservices, streamlines API management, and promotes event-driven architectures by facilitating the creation and handling of serverless functions.
Throughput: Throughput refers to the amount of data processed or delivered by a system in a given time period, usually measured in units like requests per second or transactions per minute. In the context of software systems, especially those using serverless computing and Function as a Service (FaaS), throughput is crucial as it directly impacts performance and scalability. High throughput indicates that the system can handle many operations simultaneously, which is essential for meeting user demands and optimizing resource utilization.
Vendor lock-in: Vendor lock-in is a situation where a customer becomes dependent on a specific vendor for products and services, making it difficult to switch to another provider without incurring significant costs or operational disruptions. This can occur due to proprietary technologies, data formats, or contractual obligations that tie the customer to the vendor's ecosystem. Such dependency can limit flexibility and competitiveness in adopting new technologies or solutions.