If i understood the whole concept correctly, the "serverless" architecture assumes that instead of using own servers or containers, one should use bunch of aws services. Usually such architecture includes Amazon API Gateway, bunch of Lambda functions and DynamoDB (or alternative) for storing data and state, as Lambda can't keep state. And such services as EC2 is not participating in all this, well, because this is a virtual server and it diminish all the benefits of serverless architecture.
All this looks really cool, but i feel like i'm missing something important, because right now this seems to be not applicable for such cases as real time applications.
Say, i have 2 users online. One of them performs an action in an app, which triggers changes in database, which in turn, should trigger changes in the second user app.
The conventional way to send some data or command from server to client is websocket connection. But with serverless architecture there seem to be no way to establish and maintain websocket connection. So... where did i misunderstood the concept? Or, if i understood everything correctly, then how do i implement the interactions between 2 users as described above?
where did i misunderstood the concept?
Your observation is correct. It doesn't work out of the box using API Gateway and Lambda.
Applicable solution as described here is to use AWS IoT - yes, another AWS Service.
Serverless isn't just a matter of Lambda, API Gateway and DynamoDB, it's much bigger than that. One of the big advantages to Serverless is the operational burden that it takes off your plate. No more patching, no more capacity planning, no more config management. Those may seem trivial but doing those things well and across a significant fleet of instances is complex, expensive and time consuming. Another benefit is the economics. Public cloud leverages utility billing, meaning you pay for what you run whether or not you actually use it. With AWS most of the billing per service is by hour but with Lambda it's per 100ms. The cheapest EC2 instance running for a full month is about $10/m (double that for redundancy). $20 in Lambda pricing gets you millions of invocations so for most cases serverless is significantly cheaper.
Serverless isn't for everything though, it has it's limitations, for example it's not meant for running binaries. You can't run nginx in Lambda (for example), it's only meant to be a runtime environment for the programming languages that it supports. It's also specifically meant for event based workloads, which is perfect for microservice based architectures. Small independent discrete pieces of compute doing work that when done they send an event to another(s) to do something else and if needed return a response.
To address your concerns about realtime processing, depending on what your code is doing your Lambda function could complete in less than 100ms all the way up to 5 minutes. There are strategies to optimize it's duration time but in general it's for short lived work which is conducive of realtime scenarios.
In your example about the 2 users interacting with the web app and the db, that could very easily be built using serverless technologies with one or 2 functions and a DynamoDB table. The total roundtrip time could be as low as milliseconds if not seconds, it really all depends on your code and what it's doing. These would all be HTTP calls so no websockets needed. Think of a number of APIs calling each other and your Lambda code is the orchestrator.
You might want to look at SNS (simple notification service). In your example, if app user 2 is a a subscriber to an SNS topic, then when app user 1 makes a change that triggers an SNS message, it will be pushed to the subscriber (app user 2). The message can be pushed over several supported protocols (Amazon, Apple, Google, MS, Baidu) in addition to SMTP or SMS. The SNS message can be triggered by a lambda function or directly from a DynamoDB stream after an update (a database trigger). It's up to the app developer to select a message protocol and format. The app only has to receive messages through its native channels. This may not exactly be millisecond-latency 'real-time', but it's fast enough for all but the most latency-sensitive applications.
I've been working on an AWS serverless application for several months now, and am amazed at the variety of services available. The rate of improvement and new features being added is enough to leave you out-of-breath.
Related
In Traditional Performance Automation Testing:
There is an application server where all the requests hits are received. So in this case; we have server configuration (CPU, RAM etc) with us to perform load testing (of lets say 5k concurrent users) using Jmeter or any load test tool and check server performance.
In case of AWS Serverless; there is no server - so to speak - all servers are managed by AWS. So code only resides in lambdas and it is decided by AWS on run time to perform load balancing in case there are high volumes on servers.
So now; we have a web app hosted on AWS using serverless framework and we want to measure performance of the same for 5K concurrent users. With no server backend information; only option here is to rely on the frontend or browser based response times - should this suffice?
Is there a better way to check performance of serverless applications?
I didn't work with AWS, but in my opinion performance testing in case serverless applications should perform pretty the same way as in traditional way with own physical servers.
Despite the name serverless, physical servers are still used (though are managed by aws).
So I will approach to this task with next steps:
send backend metrics (response time, count requests and so on) to some metrics system (graphite, prometheus, etc)
build dashboard in this metric system (ideally you should see requests count and response time per every instance and count of instances)
take a load testing tool (jmeter, gatling or whatever) and start your load test scenario
During the test and after the test you will see how many requests your app processing, it response times and how change count of instances depending of concurrent requests.
So in such case you will agnostic from aws management tools (but probably aws have some management dashboard and afterwards it will good to compare their results).
"Loadtesting" a serverless application is not the same as that of a traditional application. The reason for this is that when you write code that will run on a machine with a fixed amount CPU and RAM, many HTTP requests will be processed on that same machine at the same time. This means you can suffer from the noisy-neighbour effect where one request is consuming so much CPU and RAM that it is negatively affecting other requests. This could be for many reasons including sub-optimal code that is consuming a lot of resources. An attempted solution to this issue is to enable auto-scaling (automatically spin up additional servers if the load on the current ones reaches some threshold) and load balancing to spread requests across multiple servers.
This is why you need to load test a traditional application; you need to ensure that the code you wrote is performant enough to handle the influx of X number of visitors and that the underlying scaling systems can absorb the load as needed. It's also why, when you are expecting a sudden burst of traffic, you will pre-emptively spin up additional servers to help manage all that load ahead of time. The problem is you cannot always predict that; a famous person mentions your service on Facebook and suddenly your systems need to respond in seconds and usually can't.
In serverless applications, a lot of the issues around noisy neighbours in compute are removed for a number of reasons:
A lot of what you usually did in code is now done in a managed service; most web frameworks will route HTTP requests in code however API Gateway in AWS takes that over.
Lambda functions are isolated and each instance of a Lambda function has a certain quantity of memory and CPU allocated to it. It has little to no effect on other instances of Lambda functions executing at the same time (this also means if a developer makes a mistake and writes sub-optimal code, it won't bring down a server; serverless compute is far more forgiving to mistakes).
All of this is not to say its not impossible to do your homework to make sure your serverless application can handle the load. You just do it differently. Instead of trying to push fake users at your application to see if it can handle it, consult the documentation for the various services you use. AWS for example publishes the limits to these services and guarantees those numbers as a part of the service. For example, API Gateway has a limit of 10 000 requests per second. Do you expect traffic greater than 10 000 per second? If not, your good! If you do, contact AWS and they may be able to increase that limit for you. Similar limits apply to AWS Lambda, DynamoDB, S3 and all other services.
As you have mentioned, the serverless architecture (FAAS) don't have a physical or virtual server we cannot monitor the traditional metrics. Instead we can capture the below:
Auto Scalability:
Since the main advantage of this platform is Scalability, we need to check the auto scalability by increasing the load.
More requests, less response time:
When hitting huge amount of requests, traditional servers will increase the response time where as this approach will make it lesser. We need to monitor the response time.
Lambda insights in Cloudwatch:
There is an option to monitor the performance of multiple Lambda functions - Throttles, Invocations & Errors, Memory usage, CPU usage and network usage. We can configure the Lambdas we need and monitor in the 'Performance monitoring' column.
Container CPU and Memory usage:
In cloudwatch, we can create a dashboard with widgets to capture the CPU and memory usage of the containers, tasks count and LB response time (if any).
I've been learning more and more about AWS lately. I've been reading through the white papers and working my way through the various services. I've been working on PHP applications and front-end dev for a while now. Two things really stuck out to me. Those two things are server-less architecture using Lambdas with event-triggers and SQS (queues). The last three years I have been working with REST over HTTP with frameworks like Angular.
It occurred to me though that one could create an entire back-end/service layer through Lambda's and message queues alone. Perhaps I'm naive as I have never used that type of architecture for a real world project but it seems like a very simple means to build a service layer.
Has anyone built a web application back-end consisting of only Lambdas and message queues as opposed to "traditional" http request with REST. If so what types of drawbacks are there to this type of architecture besides relying so heavily on a vendor like AWS?
For example, wouldn't it be entirely possible to build a CMS using these technologies where the scripts create the AWS assets programmatically given a key with full admin rights to an account?
Yes, you can practically create the entire backend service using serverless architecture.
There are a lot of AWS services that usually play into the serverless gambit of things.
DynamoDB, SNS, SQS, S3 to name a few.
AWS Lambda is the backbone and sort of acts as a glue to bind these services.
Serverless doesn't mean you move away from "traditional" http request to message queues. If you need the web interface you would still need to use HTTP. You would primarily use message queues to decouple your services.
So, if you want the service to be accessible over HTTP just like your REST services and still be serverless then you can do that as well. And for that you will need to use AWS API Gateway in conjunction with AWS Lambda
One primary drawback/limitation is that debugging is not very straightforward. You cannot login to the system and cannot attach remote debuggers. And then obviously you get tied into the vendor.
Then there are limitations on the resources. E.g. Lambda can offer you a maximum memory footprint of 5GB, so if you need to do some compute intensive job that needs more memory and can't be broken down into sub tasks then serverless (AWS Lambda) is not an option for you.
I've recently signed up to AWS to test out their IoT platform and after setting up a few Things and going through the documentation I still seem to be missing a crucial bit of information - how to wrangle all the information from my Things?
For example if I were to build a web-based application to display the health/status of all the Things and possibly also interact with a specific Thing, what would be the way to go about it?
Do I register a "dummy" thing that also uses the device SDK to pub/sub to the topics?
Do I take whatever data the Things publish and route it to a shared DB for further processing?
Do I create Lambdas that the Things invoke?
Do I create a stand-alone application that uses the general AWS SDK to connect itself to the IoT platform?
To me the last idea sounds the most viable and "preferred" as I would need two-way interaction, not just passive listening to changes in Things, is that correct?
Generally speaking your setup might be:
IoT device publishes to AWS SQS
Some Service (application or lambda) reads from SQS and processes data (e.g. saves it to DynamoDB)
And then to display data
Stand alone application reads from DynamoDB and makes data available to users
There are lots of permutations of this. For example your IoT device can write directly to DynamoDB, then you can process the data from there. I would suggest a better pattern is to write to SQS, as you will have a clean separation between data publishing, processing and storage.
In the first instance I would probably write one application that reads from the SQS, processes the data, stores it in DynamoDB and then provides access to that data for users. A better solution longer term is to have separate systems to process/store the data, and to present that data to users.
Lambda is popular for processing of the device data, as its cost effective (runs only when needed) and scales well. Your data presentation application is probably a traditional webapp running on something like elastic beanstalk.
I'm working on a new game project at the moment that will consist of a React Native front-end and a Lambda-based back-end. The app requires some real time features such as active user records, geofencing, etc.
I was looking at Firebase's Realtime Database that looks like a really elegant solution for real-time data sync but I don't think AWS has anything quite like it.
The 3 options I could think of for "serverless" realtime using only AWS services are:
Option 1: AWS IoT Messaging over WebSockets
This one is quite obvious, a managed WebSockets connection through the IoT SDK. I was thinking of triggering Lambdas in response to inbound and outbound events and just use WebSockets as the realtime layer, building custom handling logic on the app client as you typically would.
The downside to this, at least compared to Firebase, is that I will have to handle the data in the events myself which will add another layer of management on top of WebSockets and will have to be standardized with the API data layer in the application's stores.
Pros:
Scalable bi-directional realtime connection
Cons:
Only works when the app is open
Message structure needs to be implemented
Multiple transport layers to be managed
Option 2: Push-triggered re-fetch
Another option is to use push notifications as real-time triggers but use a regular HTTP request to API Gateway to actually get the updated payload.
I like this approach because it sticks to only one transport layer and a single source of truth for application state. It will also trigger updates when the app is not open since these are Push Notifications.
The downside is that this is a lot of custom work with potentially difficult mappings between push notifications to the data that needs to be fetched.
Pros:
Push notifications work even when app is closed
Single source of truth, transport layer
Cons:
Most custom solution
Will involve many more HTTP requests overall
Option 3: Cognito Sync
This is newer to me and I'm not sure if it can actually be interfaced with from the server.
Cognito Sync offers user state sync. across devices complete with offline support and is part of the Cognito SDK which I'll be using anyway. It sounds like just what I'm looking for but couldn't find any conclusive evidence as to whether it is possible to modify, or "trigger", updates from AWS and not just from one of the devices.
Pros:
Provides an abstracted real-time data model
Connected to Cognito user records OOTB
Cons:
Not sure if can be modified or updated from Lambdas
I'm wondering if anyone has experience doing real-time on AWS as part of a Lambda-based architecture and if you have an opinion on what is the best way to proceed?
I asked a similar question to the AWS Support, and this was their response.
My question to them:
What's the group of AWS services (if it's possible) to give that same
in-browser real-time DBaaS feel like Firebase?
AWS Cognito seems to be great for user-accounts. Is there anything
similar for the WebSockets / real-time DB part?
Their response:
To your question, Firebase is closest to the AWS service AWS
MobileHub. You can check out more details below about mobilehub from
below link.
https://aws.amazon.com/mobile/details/
https://aws.amazon.com/mobile/getting-started/
"AWS Cognito seems to be great for user-accounts. Is there anything
similar for the WebSockets / real-time DB part?"
Amazon Dynamodb is a fast and flexible NoSQL database service for all
applications that need consistent, single-digit millisecond latency at
any scale. It is a fully managed cloud database and supports both
document and key-value store models. Its flexible data model, reliable
performance, and automatic scaling of throughput capacity, makes it a
great fit for mobile, web, gaming, ad tech, IoT, and many other
applications.
Amazon Dynamodb can be further optimized with Amazon DynamoDB
Accelerator (DAX) which is a fully managed, highly available,
in-memory cache that can reduce Amazon DynamoDB response times from
milliseconds to microseconds, even at millions of requests per second.
For more information, please see below documentation.
https://aws.amazon.com/dynamodb/getting-started/
https://aws.amazon.com/dynamodb/dax/
Should you have any further questions, please do not hesitate to let
me know.
Thanks.
Best regards,
Tayo O. Amazon Web Services
Check out the AWS Support Knowledge Center, a knowledge base of
articles and videos that answer customer questions about AWS services:
https://aws.amazon.com/premiumsupport/knowledge-center/?icmpid=support_email_category
Also while researching this answer I also found this, looks interesting:
https://aws.amazon.com/blogs/database/how-to-build-a-chat-application-with-amazon-elasticache-for-redis/
The comments to that article is interesting as well.
Jacob Wakeem:
What advantage this
approach have over using aws iot? It seems that iot has all these
functionality without writing a single line of code and with
server-less architecture.
Sam Dengler:
The managed PubSub feature in the AWS IoT
service is also a good approach to message-based applications, like
the one demonstrated in the article. With Elasticache (Redis),
customers who use Pub/Sub are typically also using Redis as a data
store for other use cases such as caching, leaderboards, etc. With
that said, you could also use ElastiCache (Redis) with the AWS IoT
service by triggering an AWS Lambda function via the AWS IoT rules
engine. Depending on how the message-based application is architected
and how the data is leveraged, one solution may be a better fit than
the other.
Check out AWS AppSync for some of these realtime and offline features using different data sources, including databases search and compute.
AWS Amplify is AWS's modern answer to Firebase.
Fastest way to build mobile and web applications
AWS Amplify is a development platform for building secure, scalable
mobile and web applications. It makes it easy for you to authenticate
users, securely store data and user metadata, authorize selective
access to data, integrate machine learning, analyze application
metrics, and execute server-side code. Amplify covers the complete
mobile application development workflow from version control, code
testing, to production deployment, and it easily scales with your
business from thousands of users to tens of millions. The Amplify
libraries and CLI, part of the Amplify Framework, are open source and
offer a pluggable interface that enables you to customize and create
your own plugins.
Sounds like AWS Serverless is most suited alternative.
Also wondering: AWS vs Firebase - Is It Even a Fair Fight?
AWS Amplify. You can find more information here: AWS Amplify
You could consider using supabase.
It is opensource and can be installed onto ec2 / docker containers.
https://supabase.com/docs/guides/hosting/docker
I've found the hosted solution / free really poewrful to get up and running quickly. (yet to deploy to aws)
I know this is an old question, but nowadays AWS offers AppSync... a service that destroys Firebase RDB in every aspect
I'm still trying to wrap my mind around the limitations of AWS Lambda, especially now that AWS API Gateway opens up a lot of options for serving REST requests with Lambda.
I'm considering building a web app in Angular with Lambda serving as the back-end.
For simple CRUD stuff it seems straightforward enough, but what about authentication? Would I be able to use something like Passport within Lambda to do user authentication?
Yes, you can do pretty much anything, just store your session on an AWS hosted database (RDS, Dynamo, etc). But be aware exactly you are buying with lambda. It has a lot of trade-offs.
Price: An EC2 server costs a fixed price per month, but lambda has a cost per call. Which is cheaper depends on your usage patterns. Lambda is cheaper when nobody is using your product, EC2 is most likely cheaper as usage increases.
Scale: EC2 can scale (in many ways), but it's more "manual" and "chunky" (you can only run 1 server or 2, not 1.5). Lambda has fine-grained scaling. You don't worry about it, but you also have less control over it.
Performance: Lambda is a certain speed, and you have very little control. It may have huge latencies in some cases, as they spin up new containers to handle traffic. EC2 gives you many more options for performance tuning. (Box size, on-box caches, using the latest node.js, removing un-needed services from the box, being able to run strace, etc) You can pay for excess capacity to ensure low latency.
Code: The way you code will be slightly different in Lambda vs EC2. Lambda forces you to obey some conventions that are mostly best practice. But EC2 allows you to violate them for performance, or just speed of development. Lambda is a "black box" where you have less control and visibility when you need to troubleshoot.
Setup: Lambda is easier to setup and requires less knowledge overall. EC2 requires you to be a sysadmin and understand acronyms like VPC, EBS, VPN, AMI, etc.
Posting this here, since this is the first thread I found when searching for running NodeJS Passport authentication on Lamdba.
Since you can run Express apps on Lamda, you really could run Passport on Lambda directly. However, Passport is really middleware specifically for Express, and if you're designing for Lamda in the first place you probably don't want the bloat of Express (Since the API Gateway basically does all that).
As #Jason has mentioned you can utilizing a custom authorizer. This seems pretty straight-forward, but who wants to build all the possible auth methods? That's one of the advantages of Passport, people have already done this for you.
If you're using the Servlerless Framework, someone has built out the "Serverless-authentication" project. This includes modules for many of the standard auth providers: Facebook, Google, Microsoft. There is also a boilerplate for building out more auth providers.
It took me a good bunch of research to run across all of this, so hopefully it will help someone else out.
but what about authentication?
The most modular approach is to use API Gateway's Custom Authorizers (new since Feb'16) to supply an AWS Lambda function that implement Authentication and Authorization.
I wrote a generic Custom Authorizer that works with Auth0 a the 3rd-party Single-Sign-On service.
See this question also: How to - AWS Rest API Authentication
Would I be able to use something like Passport within Lambda to do user authentication?
Not easily. Passport relies on callback URLs which you would have to create and configure.