This post mainly discusses about the two major computing resources used in Amazon Web Services (AWS) namely AWS Lambda and AWS EC2. The major areas of comparison would be infrastructure management, performance and pricing. From this post, visitors will be able to know more about the evolution of AWS computing resources, AWS EC2 and AWS Lambda.
As per the global research by a non-profit organization which is overlooks the cloud computing projects observed that out of 550 cloud platform users almost 31% of the audience were using the serverless architecture. When they had further researched the audience they learnt that 71% of them were using AWS Lambda. FaaS services like AWS Lambda are much more popular than the server based applications like EC2.
One of the major reasons why businesses are interested in moving to cloud is because of the freedom from maintenance and ability to focus on the core tasks. And building more agile and advance version of scalable applications using such FaaS solutions becomes much easier task than using server-based applications. As EC2 needs requires lot of management and resources for ensuring proper functioning of the applications. In addition the EC2 instances does not run on a full copy of operating system which is virtual copy of the hardware that is majorly utilizing the operating system to run. Whereas if we compare with the AWS Lambda then it perfectly works on sufficient resources and system requirements that run on specific programs. Moreover, AWS Lambda can help in developing any kind of software or application that you need for your business.
Also with AWS Lambda you have the flexibility to create portable code blocks which makes the process of development much easier and faster including coding, processing, testing and deployment. This is a perfect combination of resources, systems, environments, automation and delivering right solutions. With the help such platforms, the process of development and delivery moves to the next level from the current traditional methods.
However, there is much more to learn about EC2 as well, because if there was all this only, then this post will end here itself. So for detailed comparison of both the AWS services, below are some of the major points that we have considered for your reference. So let’s start with the basics of what are the services and what is comparison between these two services.
About AWS Lambda
AWS Lambda is basically an on-demand cloud computing service which works as ‘Function as a Service’ (FaaS) enabling businesses to create, architect and use the desired applications as per their business requirements.
The major difference between the AWS Lambda and AWS EC2 is the virtual server based application environment that the Lambda offers. At the same time, costing and pricing of AWS Lambda is a major factor of comparison between the two.
As per the traditional format the operations team had to allocate sufficient amount of resources and memory to the system so that the performance does not get hampered. Secondly it required lot of maintenance and frequent upgrade to ensure that the applications do not stop working.
But with the AWS Lambda, teams can enjoy the freedom from maintenance and upgradation. Secondly, the system and infrastructure on which the AWS Lambda service is implemented, it can seamlessly scale on its own and down depending on the data volume, requests and traffic dynamically at real-time. AWS Lambda also support multiple languages which is highly useful for applications for back end services.
The architecture in which the AWS Lambda has been designed is known as a serverless architecture. With such technology in place, your team can completely focus on the development than resource maintenance or upgrades.
About AWS Elastic Compute Cloud (EC2)
The Amazon Elastic Compute Cloud is a cloud based virtual infrastructure service that enables businesses to seamlessly avail on-demand resources to create world class servers for their applications. The hardware of EC2 is fragmented in various instances by which each instance can be scaled up for enhancing the computing memory and processing power.
With the help of server setup options in EC2, you have the flexibility to host your application on more than one platforms which maximum security to offer multi-tenant multi-model scenario. The traffic requests can be through HTTP or HTTPS API by which the developer can create a similar environment and application as on premise applications.
If you choose AWS EC2 you have the flexibility to choose virtual machines for the applications and offer a subscription based access model where the users charged on monthly rentals for accessing the applications.
Evolving from AWS EC2 to AWS Lambda
After the implementation of AWS EC2 started, Amazon wanted to remove the headache of maintenance and support of infrastructure at the clients end. So, in order automate the EC2 server with the fraction of auto-scaling, auto-scheduling, provisioning, monitoring, alerts, etc. it was powered with AWS CloudWatch.
Earlier version of EC2 came with much volatile environment compared to the version that is being used in the market. There were some early version issues which had to be resolved without which the EC2 would experience failed instances, fail scheduling, etc. Some of the famous brands which had deployed EC2 early version and experienced the failed instances are Reddit, Foursquare, Heroku, etc.
With such experiences, Amazon launched the AWS Elastic Beanstalk (EB) which had the excellent facilities to package and ability to create in different frameworks and multiple languages. The service was design the automate the process in such a way that the developers were required to only upload their code from the AWS console and rest all the process of managed by the platform.
In addition to the environment automation as per your code, the AWS EB also spins the EC2 instances so that the load can be balanced automatically. Further, developers have the flexibility to manually go to the instance where the program is stored and edit or tweak as per the requirements. EB will automatically update the changes and keep track of the same.
With the launch of Infrastructure as a Service (IaaS), there platform had advanced tremendously in terms of automation and no-maintenance. This had enabled several businesses to gain money and save a lot of time. However, still some of the customers felt that the upgraded version has some glitches and few promises were not fulfilled by Amazon. This gave rise to a newer version of service which led to the launch of AWS Lambda.
After the latest version of AWS Lambda was released which had all the major features including EB with an add-on feature of fully automatic scale up features. At the same time, Lambdas work through the API gateways like URL routers to your Lmabdas.
AWS Lambda Vs AWS EC2 – Detailed Competency Comparison
As per the standard documentation of AWS Lambda, the timeout of AWS Lambda is 300 seconds. Lambda automatically limits the tasks within the timeout as it has been designed to function for short term tasks. Long running functions or complex processes aren’t good fit for the AWS Lambda.
Similarly, it also get limit by the API Gateway for invoking the function within 30 seconds. Even if the timeout is configured and customized, it has to be monitored regularly and ensured that no bug occurs.
Not all the functions are timed out at 300 seconds, some timeouts also occur because the server is unable to communicate with the third party external server or the response is not received within the defined timeline.
Compared to Lambda, the AWS EC2 has pretty good and flexible options which is useful in running instances of different types and requirements of various configurations. This gives EC2 a great flexibility over Lambda.
As any other services, EC2 also comes with certain errors which needs to be managed using some techniques. Like EC2 frequently experiences security overlapping group rules issues and it’s a common error that most of the developers have to deal with to make the instance more secured.
Compared to Lambda, the EC2 has been designed to cater long functions and complex requirements so you can easily run the desired applications with maximum timeout on EC2.
Just like any other project, the AWS Lambda is also dependent on the external libraries and when you are working on large process or complex processing like image conversion, video conversion, etc. in large scale then it is important the application is support with the right set of libraries to perform.
But, there is a limit in AWS Lambda by which you will not be able to upload the package size more than 50 MB. So every time your function is executed and completed, you will have to download the dependencies in the tmp storage file.
In addition to the above, the storage limit is also 512 MB so if there are more number of dependencies then it has to be executed accordingly.
With EC2, storage and management of dependencies is not a major concern. The reason behind the same is, EC2 is not restricted with limited with limited temporary storage space. At the time, it is also important that the size of the software and corresponding instance space is appropriately defined in the system otherwise it will go burdened with the same.
As most of the parts of AWS Lambda is designed to automate, scalability is one of the important and major part AWS Lambda. The dynamic scaling characteristic of Lambda makes it one of the most best automated service model in AWS.
However, with the scalability and concurrency also comes the negative aspect of multiplying the errors. For example, if the AWS Lambda is executing 500 concurrent functions, and each function takes 3 minutes. And if a single error occurs then the entire 500 functions running consecutively will throw thousands of errors. This will lead to a spike in the errors and the response may take longer time.
AWS Lambda dependent on the EC2 for offering Elastic Network Interface for functions that are VPC based. And maximum number of 500 concurrent VPC based functions are allowed per minute.
With the help of the configurations in EC2, you have the complete flexibility and control within your limits. You can manually define the scalability features and at the same time, you can run an error-free process. In addition, there are auto-scaling groups in EC2.
By creating the auto scaling groups in EC2, you can simply create the minimum number of instances and maximum in each group so that you do not over burden the process. So AWS will ensure the that it does not go beyond the defined instances limit and automatically terminate any additional requests to other instances.
Getting a fully automated service is nothing less than a dream come true but not at the cost of lack of features to mitigate the errors. At the same time, configuring manually is difficult at the early stage if you are not use to the platform. But, once you have the control and know how to tune the applications, then automatically things become much simpler and faster.
There are many such features in AWS services which look highly optimized and useful for the business infrastructure but without the right set of knowledge and in-depth analysis it can lead to a difficult situation. In our next post, we will be discussing about similar AWS services with different perspective.
If you are planning to move your infrastructure to cloud or already have cloud infrastructure which requires AWS professionals’ support then you can contact us. We have dedicated team of AWS certified consultants and professionals to assist you with the right set of service implementation. We also have support packages that is highly beneficial for hourly tasks for your business. If you need more information regarding our cloud services then contact us at firstname.lastname@example.org