Benefits of Serverless Computing for DevOps Engineers

Serverless computing is a way of building, deploying, and maintaining applications that are changing the way DevOps teams work.

Thanks to serverless computing, engineers no longer have to spend countless hours managing servers. Instead, they can focus on deploying and delivering new updates and features to users. Serverless computing also makes it easier and faster to release updates and patches.

In this article, we will look into what serverless computing is all about, the benefits it brings to DevOps engineers, and how pipeops can help you enhance your serverless production environment.

What is Serverless Computing?

Serverless computing is a cloud-based computing model where developers can deploy applications without managing servers. Instead, cloud providers allocate resources on demand based on the application’s needs. You can also use pipeops to deploy, maintain, and manage your apps easily providing you with serverless computing functionalities.

Serverless computing removes the need for businesses to run and manage on-site servers, freeing up resources for other business endeavors. 

The main benefits of serverless computing to DevOps engineers include:

• Lower costs
• Increased speed and efficiency
• Better resource allocation
• Improved security
• Easier to scale 

Popular Serverless Computing Services

Here are the three most popular serverless computing services:

AWS Lambda

AWS Lambda is an event-driven computing service that runs code and handles resource management. 

DevOps engineers can use AWS Lambda to run code automatically in response to different events, such as table updates, HTTP requests, and state transitions.

AWS Lambda handles all the back-end tasks like computing, databases, storage, processing, and many more, which allows the engineer to focus on his program and allows him to innovate. Common AWS tasks include:

• Compute using Lambda
• Data Stores using Amazon DynamoDB
• Storage using Amazon S3
• API Proxy using Amazon API Gateway
• Orchestration using Step Functions
• Application Integration using Amazon SNS
• Analytics using Amazon Kinesis
• Developer tooling using different tools and services.

Azure Functions

Azure Functions is a powerful cloud-based computing service that allows developers to build stateless serverless functions. Events, such as HTTP requests, blob storage changes, and timer schedules, trigger these functions. Azure Functions automatically manages the underlying compute resources so developers can focus on writing code.

Once a function is deployed, Azure Functions monitors it and provides insights into its health, performance, and usage. This information can be used to improve the reliability and efficiency of functions.

Azure Functions is a valuable tool for developers who want to build and deploy scalable, reliable, and cost-effective cloud applications.

It also manages the flow of data and executes commands as requested. Microsoft Azure is made of three components, namely, Azure functions, Logic Apps, and Event Grid. 

Google Cloud Functions

Google has been a pioneer in serverless computing since 2008 with its Google App Engine. Launched in March 2017, Google Cloud Functions is a newer event-driven serverless computing platform that supports various environments, including Cloud Run, Kubernetes, and other Knative-based environments. 

Cloud Functions can be used to integrate with third-party services, power application backends, process data in real-time, power virtual assistants, and train and deploy machine learning models.

Cloud Functions supports internal events from Google Cloud Storage (Object Change Notifications) and Google Cloud Pub/Sub.

Google Cloud Pub/Sub is a message bus that helps with scaling on demand by hiding the messaging queue from the user. All the user needs to do is write the code for the consumer and the data producer. Once the user writes executable code, Google App Engine fires up enough nodes to handle incoming traffic and scales up and down as needed.

How serverless Computing can take DevOps to the next level

Serverless computing can help improve DevOps operations in several ways. Let’s consider a few ways it does that below:

Infrastructure as code (IaC)

Infrastructure as Code (IaC) is essential for smooth operations in modern cloud environments. Containers and microservices have made it necessary to provision infrastructure separately for hundreds of small applications instead of a few large ones. IaC automates this provisioning, making it possible and scalable.

IaC is also crucial for DevOps environments, giving developers easy access to the IT infrastructure that DevOps requires. By treating infrastructure and operations similarly to application code and other code, businesses can ensure that DevOps’ best practices, such as continuous monitoring and version control, are applied to the code that manages their infrastructure.

Distributed DevOps

Serverless services can radically change how DevOps teams work, enabling them to collaborate seamlessly across different environments and locations with minimal disruption. These services allow for the efficient distribution of workloads at scale, ensuring that infrastructure is always available and responsive.

However, the greater distribution and temporary nature of serverless computing can also make infrastructure monitoring more challenging. To overcome this, DevOps teams must implement centralized monitoring with real-time alerts to proactively identify and address any potential issues.

Additionally, teams should periodically conduct audits of infrastructure availability and performance to ensure that resources function optimally. Developers can do this using various tools and techniques, such as synthetic monitoring, load testing, and capacity planning.

By taking these steps, DevOps teams can leverage the power of serverless computing to deliver innovative and scalable solutions while ensuring the reliability and performance of their infrastructure.

Flexible deployments

Serverless services offer the unique advantage of immutable infrastructure, which means that changes do not affect existing instances. Instead, new instances are spun up and activated, allowing old and new versions to run simultaneously.

Because this cannot be changed, it makes it possible for flexible deployment strategies like canary and blue-green deployments to work, which would be hard or impossible to do with older infrastructures. With serverless infrastructure, users can seamlessly switch from one version to another, minimizing the risk of service interruptions and simplifying rollbacks.

Here is an example of how you can use canary deployments with serverless infrastructure:

1. A new version of a serverless function is deployed to a small subset of users.
2. The performance and functionality of the new version are monitored closely.
3. If the new version performs well, it is rolled out to all users.
4. If the new version performs poorly, it is rolled back to the previous version without impacting most users.

Blue-green deployments are another popular strategy that can be easily implemented with serverless infrastructure.

1. Two identical production environments are created, one blue and one green.
2. The new version of the serverless function is deployed in a green environment.
3. Once the green environment is verified to be stable, traffic is switched from the blue environment to the green environment.
4. The blue environment is then decommissioned.

Serverless infrastructure’s immutability and flexibility enable DevOps teams to deploy and manage their applications more efficiently and reliably.

Others

In a serverless environment, developers start by collaborating on the architecture but then work independently on their service components. A serverless system promotes independence and autonomy among DevOps engineers. 

Best Practices When Considering Serverless Computing

Serverless computing offers significant benefits, but running serverless workloads in production requires careful planning and execution. DevOps teams must consider several best practices, such as:

Use API Gateways to Maintain Security

Security is a top priority for all applications, regardless of their architectural style. When using serverless computing, implementing an API gateway as the event source for your Lambda functions is essential. Securing your API Gateway endpoints is also critical, and the API Gateway provides several options to carry this out.

Here are some of the ways to secure your API Gateway endpoints:

• Authentication and authorization: API Gateway supports numerous authentication and authorization mechanisms, such as OAuth2, AWS Identity and Access Management (IAM), and API keys. You can use any of these mechanisms to authenticate and authorize users before they can access your API.
• Rate limiting: API Gateway can help you protect your API from denial-of-service attacks by limiting the number of requests a client can make within a certain period.
• Web Application Firewall (WAF): API Gateway supports AWS WAF, which can help you protect your API from common web attacks such as SQL injection and cross-site scripting (XSS).
• API monitoring: API Gateway provides monitoring tools that can help you track the performance and security of your API. Use these tools to identify and respond to any potential security threats.

Employ Automation

Automation is a vital part of DevOps, but it’s necessary to strike a balance. Too much automation can lead to unexpected problems, so it’s crucial to implement it in a way that doesn’t repeat existing flaws.

One of the best ways to start with automation is to focus on the development process. Once you streamline these processes, you can set up automated tools to improve efficiency and reduce manual errors.

Another crucial element of automation in DevOps is automated testing. Automated testing can be used to test all aspects of an application, from unit tests to end-to-end tests. This ensures that the application is high quality and meets all requirements.

In addition to CI/CD and automated testing, many other tasks can be automated in DevOps, such as deployments, QA, and security checks. By automating these tasks, DevOps teams can free up their time to focus on more strategic initiatives.

You shouldn’t automate every task. Certain tasks require human judgment and creativity and should be left to humans. However, by automating as much as possible, DevOps teams can improve their efficiency and productivity.

Perform Load Testing

Load testing your Lambda functions is essential for determining the optimal amount of memory and timeout value to allocate. Even complex serverless applications can have hidden dependencies that may perform poorly under heavy load. Load testing helps to identify potential issues that are crucial to maintaining a highly available application.

Secure Data

Securing and verifying data in transit is essential to preventing data breaches and protecting the confidentiality, integrity, and privacy of data transmitted between different parts of a serverless architecture. Here are some guidelines:

• Use HTTPS: This secure protocol encrypts data transmitted over the internet, preventing unauthorized access to sensitive data.
• Verify SSL certificates: This ensures that the certificate owner is legitimate and that the certificate is authentic, preventing man-in-the-middle attacks.
• Enable signed requests: This adds a digital signature to requests, which the recipient then verifies, preventing data tampering and ensuring integrity.

Conclusion On Serverless Computing

In conclusion, serverless computing offers many benefits to DevOps engineers. If you’re a developer with zero experience, Pipeops can help you easily build, deploy, and maintain any application written in your favorite frontend or backend frameworks on our servers.

It supports over 30 frameworks, including MySQL, MongoDB, and Redis. You can sign up via email, GitHub, or GitLab and start deploying apps.