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Now that you’ve chosen to go the serverless route, which major vendor should you go for – Firebase vs AWS? That’s one of the big questions that a lot of developers ask themselves when they make the switch.
Should I choose Amazon Web Services (AWS), which is a mature service that will serve you well, or should you go with Google’s younger Firebase?
Before we dive into the comparison, let’s remind ourselves what serverless really means.
A traditional server usually features a single server, that needs to be maintained in-house and has a variety of responsibilities within its codebase. When a request goes in, the server executes some processes and a response is given.
This one server can be responsible for several different functions. This could include authentication, writing files, watching users, etc. You can see why this might be a hectic model for running a server.
Serverless architecture is essentially a microservice architecture, meaning you build your infrastructure from different components in the cloud and send them to managed servers – in this case, either to AWS or Google Firebase, who will run your code for you whenever it’s triggered by an event. This makes it easy for your application to scale when needed and you only pay for the runtime. Whenever an event occurs, a code or function is executed. The server runs when something happens. The code only wakes up when it receives a request. It’s not persistent and running all day, all week.
Read more about how to solve cold starts.
It only uses resources when it needs to. The benefit of this is that each function has its own responsibility, and none of it overlaps, making things cleaner and less finicky.
Serverless Best Practices handbook
Amazon Web Services (AWS) as a whole is stacked. They have so many different services that it really is an all-in-one solution.
AWS Lambda‘s performance is strong. All of their Cloud solutions are beginner-friendly and they make it easy to set up. The service is reliable and customer support is there (It’s Amazon, so of course their customer support is superb).
AWS is a pay-per-use service, meaning your cost is dependent on the type of traffic you receive. In general, their entire ecosystem is made to be all-inclusive. If you don’t want to bounce around with services, AWS is a great choice.
AWS could also be a tricky choice to recommend. There’s a slight learning curve, especially considering they have such a large suite of products on hand. Luckily there’s plenty of resources, videos, and blogs to learn. To get started, make sure to check out this article on 5 Serverless AWS Core Services for Your Starter Toolkit.
Their infrastructure is also geared a little more towards larger teams but that does definitely not mean that smaller teams with no dedicated DevOps person in hand can’t make it work. However, if handled incorrectly, AWS could end up costing you more money than you originally anticipated, regardless of the size of your team.
Read more about how to reduce cost on AWS Lambda
Firebase, although younger, is a little more advanced in its technology. From image, text, and voice APIs, they have a lot more unique services to add.
Google’s Firebase includes services that make it easy to scale. It also features traffic management services within their suite.
They also boast low IT costs. If you’re a small team setting up, Firebase might serve you better than a heavy AWS setup. It also has less of a learning curve than AWS.
On the flip side, Firebase makes it difficult to query larger datasets. Their database also doesn’t provide relational data, which could spell trouble for some newer companies.
The question of choosing AWS vs Firebase is a loaded one. It really comes down to preference, needs, and your situation:
If your situation calls for a more mature service that has an entire suite of services at your beck and call, AWS should be in your sights.
If you’re a newer team that’s prepping to set things up quickly, Firebase could serve you well.
Regardless, you’ll need to monitor your serverless setup. That’s where Dashbird comes in. Built by serverless developers with specifically serverless technologies and AWS Lambda in mind. So if you’re going to choose AWS, Dashbird is here to make sure you’re running smoothly: save you hours..even days – on average, Dashbird users have seen their discovery time of an error reduce by 80% – on debugging, give you customized and actionable insights based on the AWS Well-Architected Framework to further improve your infrastructure, and provide a quick and easy to understand real-time overview of the health and performance of your serverless infrastructure.
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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.