Monitoring platform for keeping systems up and running at all times.
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Detect and resolve any incident in record time.
Conform to industry best practices.
Both Amazon ECS and AWS Lambda were launched at the same time. They are both services and they are both offered by Amazon. A more generic term for them would be “cloud services”. So what is the difference between the two? Both services serve the same purpose: to offer an environment in which you can run applications – a computing one to be exact. An environment in which you can access services and some microservices that help you develop and deploy applications faster than you would do on your company’s servers.
Let’s first start with Amazon ECS. This service provides one with the possibility to run Docker containers on an AWS server. The upside is that these Docker containers can run an app regardless of the programming language it was written in. Amazon EC2 instances can be manually configured by the user according to one’s needs. These Amazon EC2 instances run in a cluster of servers and they can be configured with the help of AWS tools. Each of these instances can be configured to run at a specific time, be of a certain size, and handle a certain amount of resources. The code you develop and run however depends on said Docker containers.
In contrast, Amazon AWS Lambda uses lambda functions which are bits of code written specifically for Lambda. The server management part is handled by AWS in an automatic manner and the way in which the servers in the cloud execute the code is not at the user’s disposal. Lambda functions are limited in what they can do and they must be kept simplistic. AWS Lambda activity tracking can be done with a set of tools that you can choose from. In short, the cluster servers in the case of Amazon ECS are set up by the user while when it comes to AWS Lambda the underlying structure is handled by the system. AWS Lambda also supports few programming languages in contrast with Amazon ECS that can run any code in its containers. If you are familiar with a Linux environment and the programming languages it can run then AWS Lambda might be the thing for you. You can check online forums or mailing lists for an AWS Lambda c# example to see how the same code can be run both on Linux and in an AWS Lambda environment. The plus side with AWS Lambda is that scaling is automatic and one does not need to bother configuring the environment as is the case with Amazon ECS. If you’re a Python or JAVA developer this might be what you need to rapidly deploy applications.
Spoiler! There’s no winner!
Well, it’s not really a contest. There are lots of reasons why you’d pick Lambda over ECS and vice versa, it’s up to you to understand the two environments and make the correct decision when the time comes.
If your programming language of choice is not on the Amazon AWS Lambda list then you might want to go with Docker containers and use Amazon ECS. It would be great to see the transparency and ease of use present in Amazon AWS Lambda combined with the ability to run applications in a container environment. That would be a match made in Heaven for a developer that wants speed and plenty of options. Lambda functions are simple and easy to write but Docker containers can be scaled to run almost any amount of code. One can develop such code on a home computer then upload and manage the compilation process by using a preconfigured container.
To be noted that Amazon Lambda pricing might reach certain levels depending on the execution time of the code. One might regard Docker containers in an Amazon EC environment as a better option but the truth is Amazon AWS is gaining ground due to ease of use and the fact that most people use Python, Java, and other programming or scripting languages that the Amazon marketing department deemed as being necessary for their clients. AWS Lambda limits seem to be ignored by the vast majority of customers so Amazon must be doing something right with this kind of service. It may be that lack of transparency doesn’t bother many people when the upside is a quickly configured and efficient programming environment.
AWS serverless architecture has been around for some years and small and middle-sized companies find it easier to use an Amazon server cluster than to burden their own corporate server with processing times that are tens if not hundreds of times slower than what a few dollars can buy. Function as a service troubleshooting is also a factor must take into consideration since it is easier to use a fast cloud service than relying on a server administrator of your own for troubleshooting. And let’s not forget that log-based serverless monitoring is an easy way to keep watch on your processes or be alerted via e-mail when something has changed or has taken place. These are just some of the benefits of serverless architecture and people have been jumping on them for some time now.
Today we are announcing a new, updated pricing model and the end of free tier for Dashbird.
In this article, we’re covering 4 tips for AWS Lambda optimization for production. Covering error handling, memory provisioning, monitoring, performance, and more.
In this article we’ll go through the ins and outs of AWS Lambda pricing model, how it works, what additional charges you might be looking at and what’s in the fine print.
Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.
Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.
Thanks to Dashbird the time to discover the occurrence of an issue reduced from 2-4 hours to a matter of seconds or minutes. It also means that hundreds of dollars are saved every month.
Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.
I mean, it is just extremely time-saving. It’s so efficient! I don’t think it’s an exaggeration or dramatic to say that Dashbird has been a lifesaver for us.
Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird’s support has been good, and they take product suggestions with grace.
Great UI. Easy to navigate through CloudWatch logs. Simple setup.
Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.