Secure Serverless Computing By Overcoming These Challenges in 2023

January 3rd, 2023

Secure Serverless Computing By Overcoming These Challenges in 2023

Cloud computing development has led to several service model innovations such as serverless computing. With serverless computing, cloud providers perform server-related management tasks such as service deployment, resource allocation, scaling, and monitoring. Moreover, the impact of digitalization buoyed by serverless computing optimizes costs. The application pays only for its execution time; hence, consumers can avoid performing grueling management tasks and concentrate on the business code, leading to cost reduction. 

Moreover, since the emergence of serverless computing, both cloud providers and consumers have been able to reduce costs through operation, agile development, and charging mechanisms. The rapid development in recent years has led to a particular survey that claims the estimated growth of the global serverless market size increasing up to $21.1 billion by 2025. Nevertheless, there are some characteristics of serverless computing like fragmented application boundaries that raise fresh security and compliance concerns. However, since the time of the pandemic, serverless computing has provided several solutions to companies for deploying various projects and has remained a widely chosen technology to date.

For example, the agile and lightweight virtualization technology may create weak isolation and could manifest difficulties in security management. However, substantiated efforts are being made recently to cut down the impact of such challenges. Such types of concerns that arise over migrating may lead to hampering various architectural decisions due to the fear of getting it wrong and due to a lack of the right resources. 

The article sheds light on the common concerns around going serverless and provides some practical advice to reduce the impact. 

Challenges of Going Serverless with Solutions

Some of the most popular and leading commercial serverless platforms available include AWS Lambda, Google Cloud Functions, Azure, and IBM Cloud Functions. Also, there are popular open-source serverless frameworks like OpenFaaS, Knative, Apache, and many more. Among all these, AWS Lambda scores the highest. In 2004, serverless architecture came into the picture. However, it gained its popularity only in 2016 with the introduction of Amazon Web Services bringing in Lambda. Since then, serverless provides dynamic cloud-based service models and competes with traditional on-premise solutions. 

So here we provide some of the most dynamic challenges that you may confront with serverless computing. 

Cold Start

When you boot up any new container that runs Lambda, it is defined as a cold start. With .NET or Java, you get longer cold starts as compared to other languages. By using VPC (virtual private cloud), you are adding 10 more seconds to a cold start. With your network in AWS and a private service like SQL database, you can use VPC for database access. Also, you are attaching an ENI (Elastic Network Interface) with these 10 seconds. 

This happens whenever you assign a specified amount of memory to Lambda. The more memory, the better network you get and you need lesser sharing of ENI. For example, while assigning 3 GB of memory, ENI Lambda will not be shared and there will always be a 10-second cold start. With AWS, this gets resolved at some point.

Solutions:

  • Avoid using VPC if you are not using private services. Lambda alone is a secured tool as it is an official recommendation of AWS
  • Try to use Node.js, Go, and Python wherein you can avoid VPC and would never even find a cold start anywhere
  • The library of Lambda Warmer by Jeremy Daly is one of the best. Several Lambdas get triggered periodically and remain warm.

Observability 

For anyone new to serverless infrastructure, the common stumbling block is the lack of visibility. Serverless has an event-based architecture and no state. With access to the logs and application traces, you will be able to understand the gaps in the infrastructure. However, when errors crop up, it becomes difficult to resolve them as compared to their traditional counterparts. This is because serverless systems are widely distributed and every part of the system is producing logs. So you can imagine how difficult it becomes to make sense of all these. 

Solutions:

  • Try using a common correlation ID to identify the kind of logs belonging to some requests
  • Use the new Cloud Watch features that are named ‘Logs Insights’
  • Use service X-ray that allows you to look into the connected services and helps you trace the calls that flow through different parts of the system. With this, you will be able to see the execution time, architecture, error date, and much more.
  • Use reliable and known third-party services that become extremely useful in these times.

Connecting with SQL Database

The main issue with SQL databases is the compulsory usage of VPC in case you choose not to give the public access to the database. With one of the pitfalls mentioned above, VPC also proves to be expensive while opening the connection. In the traditional system, you have connection pools. A connection pool is a pool of open connections wherein you get it and can return it to the pool. 

Serverless has no place to hold this connection. Lambda comes and goes. Every time you need to open and close the connection or keep them open that can create a risk of running out of available connections. Both prove to be expensive.

Solution:

  • The best solution is to use Serverless MySQL Library by Jeremy Daly. At the end of every request, there is a check that happens to find out whether it needs to close the connection or not. It is a perfect solution. 

DDOS and such attacks

Serverless computing is automatically scalable. And hence, in case of a DDOS attack, your bill will tend to increase enormously. 

Solution:

You can limit the use of resources by setting up the following features.

  • Lambda Timeout
  • Lambda Concurrent Execution Limit
  • API Gateway throttling

Cloud Formation

While using AWS as your cloud service provider, you get this feature as a solution for infrastructure as code. Most of the tools use Cloudformation for serverless deployment. Each cloud formation stack has a limit of 200 resources. That may sound like a lot, however, you will need more resources for one Lambda. You will be able to reach the limit within 30 to 35 Lambdas, This isn’t much keeping in view the number of Lambdas you would favor.

Solution:

  • You can have one stack just for Lambdas that form a part of the same microservice
  • You can use nested CloudFormation stacks that may not be ideal but still they work
  • Instead of CloudFormation, you can also use Terraform which is much harder as compared to tools like Serverless Framework.

Higher Cost Due to Prolonged Computing

The more time the computing takes to run, the more you pay. You must ensure to have optimal cost efficiency for highly scaled applications that work with data-intensive workload processing requests. Because the costs could increase in a manner that you may not imagine and organizations may need to trade off the traffic they may have accommodated in a bid to lower the IT costs.

Solutions:

  • Do not use Lambda for long-running processes at all. Instead, use a virtual machine or a container.
  • Implement the process in a more distributed manner if possible. This leads to quick invocations and reduced costs. 
  • Try using the services of other major cloud providers such as Microsoft Azure or Google Cloud Platform which have a series of open-source platforms.

Vendor Lock-in

Often there arises a sense of insecurity of losing control over serverless due to the vendor controls on management and application specifics. Various cloud benefits such as hardware choices, runtimes, and resource parameters can turn out to be inflexible for a specific time. Also, soon after the deployment of infrastructure and initiating functionality, there are concerns about vendor lock-in with limitations whenever the users wish to migrate later down the line.

Being a developer, it becomes important to get adapted to the architecture to meet the business needs. Irrespective of the limited hardware choices, public cloud platforms have given greater infrastructure autonomy. 

Solutions:

  • Programming to an interface by creating an interface that translates general Lambda requests to the DDB query standards.
  • This will enable developers to easily write a new interface that can understand the requests and can translate them to the new database query language. 

Security Management Risk

This is an important means for administrators to protect the applications. There is a vast diversity of possible attacks in the serverless environment. Hence, comprehensive security management capability-driven protection with multiple levels of security is needed. However, serverless applications have fragmented application boundaries which creates difficulty in security management. Moreover, the functions must be able to carefully inspect the input and output at various entry points. Failure to comply may lead to injection attacks. Such tasks pose a great challenge when it comes to handling large-scale or complex applications.

Solutions:

  • Regarding security policies, all types of cloud providers can formulate their best practices for security management.
  • These policies can be designed with multiple layers and multiple resources having the potential to provide promising management capabilities.
  • For example, commercial platforms have well-defined identity authentication and fine-tuned authorization strategy with very mature identity access management systems.
  • Even AWS Lambda can provide role-based policies, access control lists, resource-based policies, and various other management methods for consumers to choose from.

Conclusion

Adopting serverless can come with various challenges. The most confronted challenges can be:

  • It has limited control over the underlying infrastructure and you may lose its control. This can hamper the fine-tuning performance ability and possibilities of scaling the app. The solution can be to use the tools like AWS Lambda Power Tuning for performance optimization.
  • Debugging and monitoring can become a challenge due to the ephemeral nature of the underlying infrastructure. Because serverless architectures are distributed. To address this issue, you can use tools like AWS X-Ray, Datadog, or Epsagon to monitor and debug your serverless application.

However, serverless computing is one of the most accessible and fast-moving technologies. Not surprisingly, serverless is the need of the hour to stand the test of time. Today, large organizations having budgets for vast resources and skillful teams still confront various security breaches and architectural failures. In such a scenario, a serverless world proves to be daunting and promising. 

With so many questions and concerns floating around this dynamic technology, the most prominent advice we can give is to start with a small configuration and deployment and use a dedicated observability serverless platform. With Cubet Technologies, you get enough visibility expansion, enhanced insights, and non-stop encouragement that can help you remain simple throughout the phase and avoid taking up any complex systems. Get in touch with us to solve your unique serverless computing challenge. We are here to help you establish a sustainable serverless computing environment.

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