Under the Hood of Serverless Applications

What Are Serverless Applications? 

Serverless applications are cloud-based solutions where infrastructure management tasks are abstracted away from the application developer. This model allows developers to focus on code and business logic without worrying about server provisioning, scaling, and maintenance. Despite its name, serverless still involves servers; it’s just that the responsibility of managing them is shifted to cloud providers.

Instead of managing server instances, the code runs in stateless compute containers that are triggered by events or HTTP requests. These applications are scalable by default, as cloud providers dynamically allocate resources as needed, ensuring optimal usage based on demand.

The serverless model offers a pay-as-you-go pricing. Developers are charged based on compute time and resources consumed during execution, which can lead to significant cost savings for sporadic workloads. This pricing model encourages efficient coding practices since applications are designed to execute only when necessary. 

This is part of a series of articles about serverless monitoring

Core Components of Serverless Applications 

Functions

Functions encapsulate discrete pieces of functionality, each performing a specific task or operation. Within cloud environments, these functions can be deployed quickly and scale automatically. They are event-driven, executing in response to triggers like file uploads or database changes. 

Functions are built to be isolated and independent, which helps in modular application design and simplifies maintenance by allowing updates to processes without disrupting others. The design of serverless functions promotes microservices architecture. Each function handles a distinct service, enabling easier debugging and scaling. Functions interact with other services through well-defined APIs or message brokers.

Event Sources and Triggers

Event sources are origins of changes that activate serverless functions. Common event types include HTTP requests, database updates, or file storage alterations. These sources provide context that the functions respond to, making event-triggered executions highly targeted.

Triggers are the functional mappings that link events to serverless functions. They define what actions should be taken when an event occurs. Using triggers, developers can tune what actions are necessary for specific events, which improves resource efficiency. This configuration-driven process allows for tailoring of functions to specific real-world scenarios. 

Execution Environment

The execution environment in serverless computing refers to the runtime conditions where functions execute. This environment is configured by cloud providers to run code in response to specific triggers. It includes the computational resources and libraries for the code to function. Environments are typically isolated and can accommodate varied programming languages.

Serverless execution environments can scale elastically with demand. They automatically allocate resources, allowing functions to handle sudden spikes in load without manual intervention. This scalability ensures consistent performance without wasted resources.

Popular Serverless Platforms 

AWS Lambda

AWS Lambda is a serverless computing platform provided by Amazon Web Services. It allows developers to run code without provisioning or managing servers, offering automatic scaling and high availability. Lambda supports multiple languages, enabling developers to work with familiar tools and frameworks.

Lambda’s billing model is based on the compute time consumed by functions, providing cost efficiency for tasks that run intermittently. With features like the AWS Lambda Power Tuner, developers can fine-tune resource allocation for optimal performance.

Source: Amazon

Learn more in our detailed guide to lambda logs 

Azure Functions

Azure Functions, by Microsoft, is another popular serverless computing option. It simplifies event-driven development, supporting a range of use cases from data processing to back-end services. Azure Functions can be triggered by various events, such as HTTP requests or messages from Azure service bus.

Azure Functions also supports multiple programming languages, allowing developers to use preferred coding environments. It integrates with the Azure ecosystem, providing possibilities for building complex cloud applications. Its serverless pricing model is beneficial for managing budgets, with costs based on usage.

Source: Microsoft

Google Cloud Functions

Google Cloud Functions is Google’s serverless compute option, intended for lightweight computing operations. This platform is useful for creating responsive applications that handle changes in real time. It supports multiple languages and provides an interface for developing functions. 

Google Cloud Functions charges based on the compute time used. It’s designed to automatically scale functions in response to incoming events, managing resource allocation dynamically. The platform also offers support for DevOps processes, enabling continuous integration and delivery.

Source: Google

Tips from the experts

1. Use custom warm-up strategies:

   To avoid cold starts, create lightweight "ping" events that trigger functions during off-peak times, ensuring environments are pre-warmed. This can be done through scheduled events in platforms like AWS Lambda or Azure Functions.

2. Optimize function granularity:

   Fine-tune the granularity of your serverless functions. Overly granular functions can introduce too many dependencies and coordination overhead. Group related tasks where possible to minimize inter-function latency.

3. Batch process to optimize costs:

   Where possible, batch your processes to reduce invocation frequency. For example, batch database writes or API calls to minimize the number of function invocations and reduce pay-per-invocation costs.

4. Leverage async processing for better performance:

   Offload non-critical or long-running tasks to asynchronous workflows like AWS Step Functions or Azure Durable Functions. This reduces user-facing latency and helps keep functions stateless and focused on core logic.

5. Design for function idempotency:

   Ensure your serverless functions are idempotent, meaning they can be safely retried without unintended side effects. This helps manage scenarios like duplicate event triggers or retry logic after failure.

Aviad Mor

CTO

Aviad Mor is the Co-Founder & CTO at Lumigo. Lumigo’s SaaS platform helps companies monitor and troubleshoot cloud-native applications while providing actionable insights that prevent business disruptions.Aviad has over a decade of experience in technology leadership, heading the development of core products in Check Point from inception to wide adoption.

Benefits of Serverless Applications 

Organizations often choose to use serverless applications due to the following benefits:

• No server management: There is no need to handle infrastructure, which reduces operational complexity and allows developers to focus on writing code rather than managing servers. Cloud providers handle provisioning, scaling, and maintenance, freeing development teams from these tasks.
• Flexible scaling: As user demand fluctuates, resources are dynamically allocated to match current needs, ensuring applications run efficiently. Unlike traditional architectures requiring pre-planned scaling strategies, serverless models handle scaling automatically.
• High availability: Cloud providers ensure redundancy and failover mechanisms for serverless applications. They automatically replicate functions across multiple data centers, protecting against downtime or service interruptions. This feature provides resilience, crucial for mission-critical applications that demand continuous availability.
• No idle capacity: In serverless models, resources are not allocated when functions are inactive, preventing idle capacity. This means no unnecessary costs for unused server time, leading to efficient billing strategies. The serverless framework automatically offloads infrastructure when not in use, ensuring compute resources remain available only when executed.

Challenges of Serverless Applications 

It should also be noted that relying on serverless applications can introduce several challenges:

• Loss of control: In serverless computing, developers relinquish control over the underlying infrastructure. This can pose challenges when specific environment configurations or optimizations are required. Modification of runtime settings is limited, as cloud providers dictate much of the execution environment’s characteristics. 
• Security: Serverless environments have a shared infrastructure model. Though cloud providers offer security measures, developers must still address data protection, access controls, and secure coding practices. The ephemeral nature of serverless functions requires careful design to safeguard against vulnerabilities and unauthorized access.
• Performance impacts: Latencies, known as “cold starts,” can occur when functions are invoked infrequently, impacting performance. During a cold start, the function environment must be initialized before execution, introducing delays. This can affect user experience, especially in real-time applications.

Best Practices for Serverless Applications 

Here are some of the ways that organizations can ensure the most effective use of serverless applications.

Managing State with External Services

Serverless architectures are inherently stateless, requiring external services to manage application state. Using managed services helps persist and retrieve state across function invocations. This approach enhances scalability by decoupling state management from compute resources.

Leveraging external state management reduces complexities associated with managing stateful servers. Services like databases or message queues provide the necessary persistence layer, enabling applications to maintain consistent state across transactions.

Handling Function Timeouts and Retries

Each function should have its timeout configured to ensure it terminates gracefully upon exceeding expected execution duration. Understanding the typical runtime helps avoid unexpected terminations.

Configuring retry mechanisms helps manage transient failures, ensuring that functions have another chance to execute. Balancing retry settings prevents resource wastage while promoting reliable task completion. Solutions like exponential backoffs provide structured retries with reduced overhead.

Reducing Cold Start Impacts

Addressing the impact of cold starts helps improve serverless application performance. One approach involves minimizing the package size of function deployments, which speeds up initialization times. Ensuring functions execute at regular intervals can also pre-warm environments, reducing latency for infrequently called functions.

Optimizations like using lighter runtime environments or prioritizing language runtime performance aid in mitigating cold start delays. Developers can leverage provider-specific features to manage cold starts.

Implementing Security Measures

Security considerations in serverless applications include implementing access controls and protecting data throughout its lifecycle. Encrypting sensitive information and enforcing strict permissions limits exposure and ensures compliance with privacy standards. Using secure APIs and adhering to cloud provider security best practices aid in protecting applications.

Regular security audits and monitoring help detect vulnerabilities early. Implementing security patches promptly ensures applications remain protected against emerging threats. By considering security as a continuous process, developers can maintain secure serverless environments.

Serverless Monitoring with Lumigo

Lumigo is an observability platform purpose-built for troubleshooting microservices in production. Developers building serverless apps with AWS Lambda and other serverless services use Lumigo to monitor, trace, and troubleshoot their serverless applications. Deployed with no changes and automated in one-click, Lumigo stitches together every interaction between micro and managed services into end-to-end stack traces, giving complete visibility into serverless environments. Using Lumigo to monitor and troubleshoot their applications, developers get:

• End-to-end virtual stack traces across every micro and managed service that makes up a serverless application, in context
• API visibility that makes all the data passed between services available and accessible, making it possible to perform root cause analysis without digging through logs 
• Distributed tracing that is deployed with no code and automated in one click 
• Unified platform to explore and query across microservices, see a real-time view of applications, and optimize performance 

Learn more about Lumigo