There’s little doubt that serverless computing has transformed the way to deploy and manage applications. At its core, the serverless architecture allows application developers to write their code without worrying about the supporting infrastructure. While the serverless framework can reduce development costs, serverless applications can increase costs due to frequent API calls. The API calls can cost up to $3.5 for every million executions.
Without a proper cost strategy, organizations can risk higher cloud spending on the serverless framework. How can they implement cost management in the serverless domain? Here are 8 effective cost management practices:
- Understand the serverless cloud pricing model
The first practice in serverless cost management is to understand the pricing model of your cloud service provider. Typically, serverless plans follow the “pay as you use” model, where customers only pay for consumed resources like processed requests, execution time, and memory.
However, cloud providers do have different pricing models, based on the number of users, requests, and tiers. Based on their application requirements, organizations must choose the best pricing model that can help them reduce costs in the long run.
- Use cost-efficient coding practices
Efficient coding practices are among the best practices to implement cost-effective serverless applications. Typically, serverless providers charge their customers based on the cloud resources consumed by the deployed applications. Through code optimization, developers can directly reduce consumed resources and costs.
Here are some cost-effective coding practices:
- Minimize the cold start time of application functions.
- Minimize the number and size of application dependencies and packages (used in the code).
- Implement an event-driven approach to activate application functions (based on real-time events and messages).
- Use caching techniques to avoid the processing of unnecessary requests.
- Use function designing
Cost escalation in serverless environments mainly occurs due to memory overprovisioning and higher CPU allocation. When executing any serverless application on the cloud, the service provider allocates memory and processing power based on the serverless function design. One effective practice is to design the application's function in the initial phase to consume fewer computing resources.
Here are some effective design practices:
- Minimize the number of external calls by reducing application dependencies.
- Review the time taken for initializing the application code.
- Review the application logging level to your operational requirements.
- Monitor the usage
By monitoring the usage of the serverless framework, organizations can reduce costs. This involves identifying any anomalies, spikes, or inefficiencies, which can impact costs and the quality of service.
Cloud monitoring tools like AWS CloudWatch and Google Cloud Operations can help organizations collect and visualize serverless metrics. These monitoring tools can identify usage patterns besides monitoring application performance.
Other tools like Lumigo can provide companies with valuable insights into their serverless environment and architecture.
- Manage the resources
With effective resource management, organizations can match their resource size to their resource requirements. Proper resource management can help companies avoid overprovisioning along with the associated costs.
As part of managing the resource, implement auto-scaling to scale your serverless infrastructure based on workload demands. By setting a cost-effective upper limit, auto-scaling is effective for long-term cost optimization.
- Implement caching
Caching is also an effective but underutilized way to cut costs in serverless environments. Without any caching, serverless applications generate more requests from functions and APIs. This leads to cloud servers processing more requests, thus increasing the costs.
Here is a list of tools that support caching:
- CloudFront enables caching, which is nearest to the users.
- API Gateway has a built-in caching mechanism for optimum efficiency.
- Cloud services like Amazon ElastiCache or Momento enable application-level caching.
- Track cost-related KPIs
To control their costs, organizations can set and track cost-related KPIs or metrics from any cloud management tool. Here are some of the relevant KPIs:
- Cost per execution metric calculates the average cost of executing a single function. This helps in identifying the most expensive serverless functions, which need to be optimized.
- Function duration is the amount of time taken to execute any function. The longer the duration, the higher the costs.
- Idle time is another KPI that tracks serverless functions that are running, but not delivering any output. By reducing the idle time, companies can reduce costs.
- Deploy cost management tools
With cloud cost management tools, organizations can effectively control their cloud spending. These tools provide real-time insights into cloud usage and expenses, thus enabling companies to make proper cost-cutting decisions. Some examples of cost management tools for the serverless framework include:
- AWS Cost Explorer
- Google Cloud Billing
- Azure Cost Management
Besides using cost management tools, organizations can apply cost-saving strategies by setting budget limits and configuring alerts for cloud spending tracking.
Serverless vs Dedicated instances
How does the serverless framework compare against dedicated instances? For heavy workloads, dedicated reserved instances on Amazon EC2 can provide discounts of up to to 75%, as compared to on-demand instances.
Overall, dedicated instances are designed to be cost-effective for running over longer time periods. However, they are slower to respond to a sudden spike in activity (for instance, higher workloads). On the other hand, serverless instances are less cost-effective for longer running time, but are better designed for sporadic variations in workloads.
Organizations that run a mix of “higher” predictable workload and “lower” variable workload can consider a hybrid cloud environment to leverage benefits from both technologies. To achieve this, they can architect the application to run the predictable workload (on the dedicated instances) and their variable workload (on serverless instances).
Conclusion
Serverless frameworks have emerged as the preferred choice for application developers, which can save both time and costs for organizations.
At Wissen, we have enabled our customers to leverage the capabilities of serverless architecture. With our approach, you can benefit from our customized serverless solutions and our cloud-related services.
If you are struggling with unpredictable bills with your cloud implementation, we can help you out. Contact us now.
