Issues to Avoid When Implementing Serverless Architecture
Serverless architecture offers unmatched scalability, cost savings, and reduced infrastructure maintenance. Yet, it comes with serverless implementation issues like vendor lock-in, cold starts, and a lack of control when debugging. Acknowledging and addressing all the pros and cons of serverless computing will help you adjust to the technology and implement it smoothly.
We at Serverless have 10+ years of experience in cloud development. Our certified developers have deployed from scratch and consulted on over 200 serverless architecture projects. In this article, we'll share primary serverless computing implementation pitfalls and the strategies to avoid them based on our deep expertise in the field.
After reading this, you will better understand the serverless implementation challenges and best practices for minimizing the downsides.
Common Serverless Architecture Implementation Issues
Before implementing serverless architecture, you should know the challenges that can undermine its potential. So, let’s get into serverless implementation issues and the strategies to minimize their impact.
On-demand scalability is one of the primary benefits of serverless architecture. Yet, this ability can become a double-edged sword for those implementing serverless computing. Although scalability on demand works well for managing increased activity, it can become an issue for downstream systems. Serverless architecture requires shifting perspective from one application handling massive data quantities to numerous microservices swiftly running smaller tasks.
You can tackle the flooding downstream systems by throttling the microservice or using queues to throttle parallel processing. As this task involves many parallel functions running simultaneously, it requires building a "stage" for appropriate event ordering. Sending your messages through an ordering stage can decrease your transmission speed. You can solve it by switching back to serial processing from parallel processing.
Ensuring enhanced security is one of the critical challenges of a serverless implementation. Applications that interact with customers must always have a tight security posture. The least privilege principle should likewise apply to these services, granting access only as much as needed and nothing more.
Suppliers and providers typically integrate access control and other techniques. Some solutions, including Azure API Manager, AWS Appsync, and AWS API Gateway, offer public-facing endpoints that are quickly and widely secureable. These services also come with default throttle and authorization rates, improving security and preventing DDoS and API hacking attacks.
Vendor dependency is one of the key issues of serverless implementation. Vendor lock-in is associated with various challenges. They include third-party API use, lack of customizable operational tools, implementation drawbacks, architectural complexity, and migration to other providers.
- Third-party APIs introduce issues around limited control and observability, multitenancy problems, security concerns, and vendor lock-in for the services. Compliance can require upgrades, leading to functionality losses, unexpected limits, constraints, or costs.
- Distributed debugging tools can encourage developers' dependence on the cloud provider. Piping logs to other third-party offerings can lessen the ties to the cloud provider but increase the reliance on these services.
- Implementation drawbacks vary depending on the cloud provider. Some providers do not support the deployment of a logical application with many serverless services, while AWS and Azure frameworks do. It creates a chain reaction of other problems, such as versioning and rollback concerns.
- Architecture complexity is defined by the time and effort needed to size the functions appropriately. An application or service may need to call many functions without proper function design.
- Migration to another provider will be impossible without reimplementing the logic in a supported language if its functions are written in a language not supported by other candidate providers.
To avoid these serverless implementation challenges, consider all the pros and cons and choose the cloud provider you are ready to depend on. The open-source Serverless framework that provides an abstraction layer can offset some discrepancies. Allow some flexibility within the code, and don’t lock yourself into one serverless compute service only. You need to have a backup plan you can use when your solution is more advanced than the platform to switch seamlessly to a bare server.
Monitoring and Debugging Difficulties
Lack of control and insights when monitoring and debugging is one of the concerns of developers working with serverless platforms. Partially, these serverless architecture issues stem from its nature. Even so, deploying in a setting that restricts visibility and control, particularly regarding troubleshooting issues, can compromise production and uptime.
In server architecture, developers can use SSH to connect to a host and access the programming environment directly or use introspecting the code to troubleshoot. These options are typically unavailable in serverless setups as the execution environment is opaque to the user, and only some interfaces, such as function logs, are exposed for debugging. It makes diagnosing issues challenging, particularly when numerous functions are called in a pipeline or local replication is unavailable.
Some serverless features can be emulated or performed locally, allowing developers to troubleshoot issues they cannot resolve on the provider's production system on their machines. Anyway, you need to use the supplier’s tools to debug on the platform itself. It typically entails keeping many logs inside your functions, triggering functions automatically with varying input using API testing tools.
Cold Start Issues
The function resources are spun down when not in use, giving the platform more capacity. The drawback is that there is a delay the next time it needs to run when the resources spin down. Running the function requires reallocating the resources, which takes time to load back into memory. As a result, the performance slows down. This is the cold start issue.
One of the solutions to minimize cold starts is employing atomic functions—tiny, discrete, compartmentalized code segments. Atomic functions simplify complicated logic, allowing for speedier loading and operation. Additionally, you can pre-warm functions by making regular calls to them or reserve virtual machine instances in the background to host the serverless function. It will increase the expenses but improve execution and speed.
Due to the indefinite scalability of microservices, it is simple to overlook duplicates created by your system or the cloud provider's underlying architecture. Clients may suffer grave consequences as a result of this. Therefore, duplicate detection is always required when using serverless microservices.
Fortunately, there are a lot of well-proven techniques for preventing duplicates. Keeping a temporary ledger is one way to do this. You can log everything that has run through the system and check past events in the ledger. Some suppliers offer de-duplication solutions straight out of the box. Duplicates may originate from different systems or within the supplier, so you need to have a plan to prevent all possible cases.
Kyrylo KozakCEO, Co-founder
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Best Practices for Serverless Architecture Implementation
Now that you know the common issues to keep in mind, let’s delve deeper and discuss the best practices for hassle-free serverless architecture implementation. The Serverless Team has prepared serverless implementation tips for each category based on our 10+ years of experience in cloud development.
In serverless computing, the cloud vendor provides backend services on an as-used basis. While serverless vendors still use servers, clients don’t have to worry about the infrastructure. Here are the best practices from our team to avoid the pitfalls of serverless computing:
- Resource Optimization: Balancing CPU and memory resources is vital to ensure cost and performance efficiency. Understand the resource requirements of your functions and adjust them accordingly to avoid over-provisioning. Leverage auto-scaling features to adjust resources based on varying workloads dynamically, ensuring optimal performance during peak times and cost savings during low-traffic periods.
- Initialization Latency: Minimizing the cold start time of functions is essential for time-sensitive applications. Utilize techniques such as keeping functions warm through scheduled executions or implementing strategies like provisioned concurrency to reduce initialization latency.
- Dependency Management: Keep dependencies minimal to reduce package sizes and simplify deployment. This improves performance and streamlines the operational aspects of managing dependencies in a serverless environment.
At Serverless, we use AWS Lambda and Amazon ECS (with Fargate) to adhere to the best practices in computing.
Networking and Content Delivery
In serverless architecture, networking ensures content delivery, providing user apps and data with improved security and minimal latency. Here is how to ensure the smooth work of these services:
- Security and access: Adopt robust security procedures, such as encryption, safe network setups, and frequent security evaluations. Employ identity and access management (IAM) to regulate and oversee resource access while upholding the least-privileged principle.
- API management: Optimize API performance by implementing caching mechanisms, efficient request handling, and rate limiting. It helps prevent abuse of APIs and minimizes costs associated with excessive usage.
- Monitoring and logging: Use comprehensive monitoring tools to track network activity and performance metrics. Implement centralized logging to facilitate troubleshooting and debugging. Set up alerts for critical events to proactively address issues and ensure the smooth operation of your serverless applications.
We recommend S3, CloudFront, and API Gateway services for seamless networking and content delivery.
Serverless storage systems allow development teams to avoid the hassles of setting up and maintaining cloud infrastructure. Let’s see how to ensure error-free data governance in serverless architecture.
- Lifecycle management: Automate data lifecycle management to efficiently handle retention, archiving, and deletion policies. This helps in optimizing storage costs and ensures compliance with data retention policies.
- Performance optimization: Use techniques like partitioning and caching to improve the efficiency of data access and storage. Recognize your data's access trends and adjust storage arrangements appropriately.
We leverage S3 service for data storage in a serverless architecture.
Serverless databases further improve the server-free development experience. They provide a fully managed and scalable database-as-a-service (DBaaS) paradigm that eliminates the need to control the underlying infrastructure. Here is how to use serverless databases efficiently:
- Capacity management: In auto-scaling environments, dynamically adjust database capacity to balance cost and performance. Utilize serverless database offerings or implement auto-scaling features to handle varying workloads efficiently.
- Data modeling: Design effective data schemas and indexing strategies to optimize database performance and query efficiency. Consider the specific requirements of your application and adjust data models accordingly.
- Backup and recovery: Implement regular backup procedures and conduct periodic tests to ensure data integrity and availability. Establish a robust disaster recovery plan to minimize downtime in case of unexpected failures.
The Serverless Team has experience working with DynamoDB, RDS with Aurora Serverless, or any other 3rd party serverless databases like PlanetScale or Supabase.
In this section, we want to highlight several crucial general factors to consider when implementing serverless architecture.
- Cost management: Continuously monitor and optimize expenditures by leveraging cost management tools provided by cloud service providers. Implement budget alerts and explore reserved instances or pricing plans to manage costs effectively.
- State management: Design applications to effectively manage the state, considering the stateless nature of serverless architectures. Utilize external storage solutions or serverless databases for persisting state when necessary.
- Vendor Lock-In: Again, be mindful of potential vendor lock-ins and design your architecture with portability in mind. Consider using open standards and abstraction layers to facilitate the migration of applications to different cloud providers if needed.
If you need help or clarification on the outlined best practices, the Serverless Team is happy to help and use our prior experience to assist with any implementation challenge.
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Our Team as Your Serverless Development Partner
Serverless is a software development company specializing in serverless applications using AWS and the Serverless Framework. Our cloud developers hold ISO 27001 and ISO 9001 certifications and are highly rated on Clutch and Upwork. Over the last 10+ years, we have deployed and consulted more than 200 serverless architecture projects.
We can develop high-performing serverless apps, enabling quicker time to market, lower operating costs, and seamless scalability for our clients. By delegating serverless architecture implementation to the Serverless Team, you leverage our deep expertise in cloud development to ensure a streamlined and seamless development process. Besides development, we provide migration and consulting services, as well as post-deployment maintenance & support.
Implement Serverless Architecture Hassle-Free with Serverless Team
Implementing serverless architecture requires deep expertise in cloud development. Knowing potential serverless implementation issues and the best mitigation strategies for each is vital for thriving in this environment. Working with a trusted and skilled serverless development partner will help you overcome all the obstacles of the serverless implementation process.
Over the last decade, we at Serverless have built a solid portfolio in serverless architecture implementation. Our developers possess all the knowledge and experience to help you deploy serverless architecture from scratch or consult you on any issue you face during the implementation process.
Consult with us on how to avoid the challenges of serverless architecture implementation.
How can I ensure the security of my serverless functions and data in a cloud environment?
Implementing robust authentication, authorization, and encryption procedures will help you to ensure the security of your serverless functions. We also recommend conducting security audits regularly to find and fix vulnerabilities.
How can I design my serverless architecture to be resilient to failures and ensure high availability?
You need to design serverless architecture with resilience in mind To provide high availability and fault tolerance in the event of failures. You can achieve it by implementing automatic scaling, dispersing functions over several availability zones, and using redundant storage techniques.
Is it possible to implement serverless architecture in a multi-cloud or hybrid-cloud environment?
Yes, serverless architecture can be implemented in a multi-cloud or hybrid-cloud environment through the use of containerization technologies, vendor-agnostic component design, and services that facilitate interoperability across various cloud providers. Don’t hesitate to contact the Serverless Team to discuss your implementation needs.
What are the key components of serverless architecture?
The serverless architecture comprises four major components: FaaS (Function As A Service), BaaS (Backend As A Service), API Gateway, and database.
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