Five Serverless Aspects to Keep in Mind
Pay attention, this is important. Take a look at these facts about the serverless paradigm, why they matter to enterprises, and what it all means.
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Ever wonder how people develop apps so fast? Why the competition always beats you to market?
There’s an obvious answer that most people overlook: those companies don’t bother with servers.
No servers, you say? Correctomundo.
Third-party servers streamline the app development process. Your business won’t need to host, maintain, or scale app servers. Instead, companies like Amazon offer off-site servers.
These off-site servers save your business time and money. There is no upkeep cost, no maintenance time, and you can quickly bring your app to market. So why doesn’t everyone use a serverless application model?
That’s what we’re here to discuss. We’ve come up with five little-known factors that could affect your serverless application model.
Let’s get started.
Price is the main reason people choose a serverless application model. Off-site servers, on the whole, cost less than hosting your own servers. Any money saved is money you can reinvest into your application.
However, most new users don’t understand how serverless pricing works. Think of the serverless application model as a “pay-as-you-go” phone model. You’re only responsible for paying the “minutes” that you use.
Minutes refer to used memory, processed code requests, and the code execution. Each metric scales right along with your server load. Your business is only paying for its exact server load.
…And Unpredictable Pricing
Serverless application models mean lower prices. As mentioned above, you’re only paying for the server space that you’re using.
Everyone wants lower costs. Low costs decrease your overhead and increase your ROI.
But while serverless application models promise lower costs, they don’t always lend themselves to stable pricing. Unless you’re Facebook, Twitter, or some other extremely large, established app, your traffic numbers will change.
Chances are good you’ll see traffic spikes. Maybe your app starts off strong and levels off. Maybe your app starts off slow and quickly gets popular.
You won’t know until you bring the app to market. You can’t properly budget for a serverless model without knowing your traffic numbers.
Deployment Speed (Zero-To-Production Speed)
Have you ever wished you could have someone to help you with your chores? Someone you can delegate almost half your responsibilities to while being at ease that they are handled correctly? Really? You, too? Great, because that's exactly how the new serverless paradigm aims to change the way we build our applications and websites. Focus on the business logic and your user experience and let the service provider handle the ugly backend stuff.
This is basically the promise of serverless, having you not be stuck, knee-deep in infrastructure problems, upgrade, updates, security issues, etc. A survey said that, on average, you save up to 4 developers days per month by switching to serverless, which adds to about 21% more time you can put into your frontend, learning new things, walking the dog, or knitting.
There Are Limits
The serverless application model comes with very specific limits. The limits prevent companies from abusing their server load. For example, let’s look at Amazon’s limits:
The code execution timeout is 5 minutes
You must set a concurrent execution limit
Memory volume must vary between 128 MB and 15236 MB
Deployment packages are limited to 50 MB
Request bodies max out at 128 KB
App designers need to understand these limits before going serverless. Third-party companies won’t make exceptions. You can’t use a serverless application model if you can’t fit within the guidelines.
Think of your car in cold weather. Everything takes longer to start and “warm up.” But once your car’s been running, you don’t need the same warm-up time. Application cold starts work the same way.
Your FaaS platform has to initialize a function before each event. Normally, this happens instantly, but a serverless model causes latency.
Let’s use AWS Lambda as an example.
Cold starts involve creating a new container and initializing the function host process. However, warm starts reuse a previous event’s host container. The more events you process, the less cold starts you’ll have.
If you’re not processing many events, it’s important to take latency time into account. Which is why we recommend a free serverless monitoring tool to help with.
Debugging Your Serverless Application Model
Serverless applications take extra work to debug. That's a fact. You need to compensate for lack of server control and observability with tools that help you in that regard. Tools like Dashbird.
Dashbird gives you the observability without sacrificing performance or adding any extra costs to your AWS bill. Oh, did I mention it's free?
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