Server-less computing is a distinct shift in application development. It enables developers to focus on writing codes without the hassles of infrastructure that is zero server management, no up-front provisioning, auto-scaling, and paying for services used. Companies that adopt these new approaches enjoy a lower cost of development and operations, release software faster, innovate quickly, and harness the cloud’s latest capabilities to gain an advantage over their rival firms. These cloud services have been applied with in-depth knowledge of the underlying software and huge investments in simplification, reliability, and security.
Functions are the compute engine in a server-less architecture providing a fully managed execution of common software language runtime environments. Code is uploaded as a zip file, in a managed container that activates, reads an event, processes the request, and becomes dormant for each application request. Software functions can be refactored using server-less technologies like AWS Lambda. AWS lets you run code for practically any application or back-end service, all with zero administration. Clients can find ways to improve their operations by changing the way they provision, publish, and code to production through continuous integration of (CI/CD) practices.
Cloud Functions is Google Cloud’s event-driven server-less compute platform. It lets you build in-depth server-less apps easily without having to provision servers. It automatically scales based on the load and simplifies complex application development across all languages, built-in security, distributed tracing, and key networking ability for hybrid and multi-cloud scenarios. For example, Blue Silver has leveraged Azure Functions and Logic Apps to build on many server-less applications. Kubernetes enables you to run workloads anywhere, fully managed on Google Cloud, on-premises, or on a third-party cloud provision like Anthos.
Serverless architectures mean applications that are dependent on third-party services (Backend as a service or “BaaS”) or on custom code, which runs in ephemeral containers (Function as a Service or “FaaS”), the suitable known vendor host of which currently is AWS Lambda. This term is used because the business or customer that owns the system does not have to purchase, rent, or provision servers for the back-end code to run on. Which in plain terms is that an application can be written that uses no assigned servers at all, being completely server-less. FaaS manages and allows the developers to carry out codes in response to events without maintaining any infrastructure.
Cloud database services, object storage services, and application data cache are some of the storage options available for server-less environments. Cloud database services provide a high level of scalability and ensure that data is protected via distributed fault tolerance. With MySQL and PostgreSQL compatible options, Amazon Aurora serverless is built on distributed, fault-tolerant, self-healing six-way replication storage to protect against any data theft. Microsoft also has Azure Storage as well as Azure Cosmos DB.
Object storage services such as Amazon S3 and Azure Blob are ideal for web-scale applications since these are cheaper, standardized, and highly scalable when used in server-less storage.
For application memory cache tools like Redis, an in-memory key-value store does away with traditional storage in favor of an in-memory approach that addresses high-performance application needs with increased availability.
Factors to be taken into consideration when going serverless:
When organizations turn to the adoption of server-less solutions to update their operating model requires them to manage these deployments in all areas of :
Debugging in server-less applications needs to be removed and replaced with events and triggers in event-driven architectures. This abstraction removes access to that layer and negates many tools used today. Mode2 recommends that set-ups consider how they could access data currently residing in VPC-based deployments, and how to optimize service calls for serverless workloads.
Networking in a server-less model removes any access for users beyond which is provided in environment variables. Functions run in multi-tenanted containers, which incurs a huge expenditure to bind to a private network interface. Event-driven architectures have a big impact on networking, and Cloud managers consider how to access data and ways to optimize architectures for server-less workloads.
Testing code also requires a change in approach because the function code may be simple, but the interactions between many functions in a highly distributed system is complex. The right approach is for functions to be written as a few hundred lines of code for a common purpose, so testing the code is simpler across many service interactions.
Team Roles: With less infrastructure to handle, the budgets shift to more developments and shared Site Reliability Engineer responsibilities. This SRE role expands towards long-term improvements in code, bug fixes during shifts, and in reducing the operational support for a well-instrumented automated workload.
Observation: Functions run in highly restricted environments with some performance tools removed, so companies must consider monitoring solutions to provide operational inputs and solve issues quickly, if any.
Security: Existing security tools like NIDs and WAFs rely on checking out networks and packets which are absent in server-less technology as these functions are in most cases chained together via other server-less services and the apt practice would be to apply least privilege access policies to each function and these have to be managed and updated as new service calls are added to code.
Event loops: Server-less adopters must frequently test for event loops, activate billing alarms, and establish a circuit breaker to buy time to debug and release code fixes.
When is server-less not the answer?
These server-less applications are poor fits for sharing information across functions that require solutions like Redis, as there is no shared cache in Lambda as it limits users to 1,000 concurrent executions by default.
Cloud customers are welcoming server-less because of its countless benefits saying this is very crucial for their jobs. While institutions are developing newer workloads to build knowledge and experience with server-less, they should also review existing applications to remove technical debt and streamline functions with lean software.