Although moving into the cloud can mean that your IT budget increases, cloud computing helps you customize how it runs. There are many advantages to using AWS - whether you're using it for just one application or using the cloud as a data center. The advantage of using AWS is that you save money on other aspects of your business, allowing you to spend more wisely on AWS services. For example, monitoring time zones to the only charge for the services used at peak times means that costs can be managed anytime.
This means there are great opportunities to save money if users pay only for what they need, making sure that costs are minimized while also providing abilities to scale back when things are quiet.
AWS Lambda Cost Optimization
With AWS Lambda, you only pay for the time your code is running. More time means more money. The best part about this billing model is that it removes virtually all of the guesswork that used to go into planning your infrastructure costs. Since server capacity is provisioned automatically when needed, there's no need for expensive hardware allocations to handle surges in demand!
How AWS Lambda Pricing Works
Before we get into the meat and potatoes of understanding how to lower costs, let's review how Amazon determines the price of AWS Lambda. Amazon's Lambda has several indicators to calculate how much it will cost to run them. The duration is measured according to the time your code began executing until it completes or otherwise ends. Price depends on how much memory your function requires.
The AWS Lambda service is part of Compute Savings Plans, which provide low prices for Amazon EC2, Amazon Fargate, and AWS Lambda if you commit to using them consistently for a period of one or three years. You can save up to 17% on Amazon Lambda when you use Compute
Request pricing
- Free Tier: 1 million monthly requests
- Then $0.20 for every million requests
Duration pricing
- 400,000 GB-seconds free per month
- $0.00001667 for each GB-second afterward
Function configuration memory size.
An invocation consumes 1.5 GB or less of memory, multiplied by the duration. In practice, GB-sec proves to be rather complicated, despite its simple appearance. If you want to see what your function might cost, you can try an Amazon Lambda cost calculator.
Ways to Optimize AWS Lambda Costs
Monitor All AWS Lambda Workloads
There are over 120,000 AWS Lambda functions in the wild. Let's say you own a business. If you want to see every single function, you'd need over 2000 computers in your network just to keep up with what's running. While that's a horrible amount of computer resources, many of us don't have that capability. You can create instances with many cores, memory, storage, and other resources to monitor what's going on.
Your Lambda function will still keep running, but as long as you can monitor the outcome, it's effortless to see what's going on in there. AWS Lambda dashboard from AWS allows you to view metrics from your Lambda functions. You can see live logs of how long functions run and which parts of your code are processing or not.
Reduce Lambda Usage
Lambda usage can be easily optimized and significantly cut down, by simply turning off and downing Lambda services whenever they are not in use.
You can configure AWS Lambda to function on a per-task basis. It might even inspire you to do the same for your other services. Don't use lambdas for simple transforms, or you will find yourself paying more than $0.20 per 1000 calls. If you are deploying a serverless API using AWS AppSync & API Gateway, this happens quite often.
Cache Lambda Responses
Instead of sending a static string to all API endpoints, developers can send response headers that include the exact value the user needs and even identify the intended application using a unique ID.
One of the keys to delivering a very efficient response is to cache those responses, so your endpoints don't need to send it all the time. A function that is not called doesn't add to your bill. Further, this allows developers to save time and energy and achieve implementations that enhance user experience.
Use Batch Lambda Calls
Sometimes, a server may be under heavy load, and the peak traffic will fluctuate due to intermittent events. Good use of queue could be utilized to make this an effective, fast solution to pause Lambda execution and "batch" code executions. Instead of calling functions on every event, you will be calling only a set number of times during a specific event period.
If the function call rate is constant, the other requests can wait until the function is called. For outstanding performance, Lambda has native support for AWS queuing services such as Kinesis and SQS. It's essential to test your function optimally and follow these best practices to ensure your data is batched properly.
Never Call Lambda Directly from Lambda
If you want to change the AWS Lambda endpoint on the server, you can't call it directly. This is another example of why Lambda isn't meant to be a transactional backend or database but rather a real-time event-sourced service. You may be using AWS Lambda today without knowing this, but it's easy to minimize your AWS Lambda costs with this knowledge in mind.
There are many options available when it comes to AWS queuing services. SQS, SNS, Kinesis, and Step Functions are just a few that set AWS apart for those tasks that require heavy-hitting responses. You can notify clients with WebSockets or email as your needs arise.
Cloudride specializes in providing professional consultancy & implementation planning services for all cloud environments and providers. Whether the target environment is AWS, Azure GCP, or others, Cloudride specialists are experienced experts with these systems and cater to any need. You no longer have to worry about reducing cloud costs or improving efficiency—just leave that to us. Give us a call today for your free consultation!