I use nestjs with typeorm and postgresql, I get data from the database in 150-200ms, but if you wait 20 seconds and send a request to the backend again and get the data, then I get the data in 1000ms or 1500ms, although in theory and in general it should usually be 150- 200ms? Tried to use sequelize result was same. As if, if you wait, the server starts to fall asleep and wakes up for a long time when the request goes to it again.
This is code how I do request to database:
async getProducts() {
const products = await this.productRepository.find();
return products;
}
Please any ideas, answers, options
It is very unlikely that Nestjs is adding a significant delay here. The code you posted looks okay-ish.
Try removing the "surroundings" (as in moving parts) to get to the bottom of this. E.g. execute this method in the main.ts
Hint: if your service would be called MyService you could access it there like this:
const service = app.get(MyService);
Another way would be to remove everything that is involved in the response of the request:
Your code from controller -> service -> repository
Code that could intercept: Middlewares, Pipes, Guards, Interceptors
By switching Sequelize to TypeORM you kinda removed the DB communication layer as a suspect, if your investigation does not yield anything helpful you should consider looking into the underlying DB and the specified connection options (if any, e.g. pool size). Most likely the causing code should be in the application tho. For Sequelize and TypeScript, you can also enable logging to get better insights. Good luck on your research!
I've been messing around with serverless and postgresql. It seems that connection pooling is possible, but when I declared a connection pool to my postgresql instance outside:
var pool = new pg.Pool(config);
Not calling pool.end() at the end of request handlers seem to cause lambda-local to not terminate when I call it.
If I call pool.end() lambda-local does terminate, but I wonder if this means that the function will stop working?
If I don't call pool.end(), will the function run forever on AWS, costing me a lot of money?
This is because by default, the lambda callback waits for empty event loop before "freezing the process" doc
You can change this behavior by setting context.callbackWaitsForEmptyEventLoop to false. On subsequent calls, in case of "hot start", your lambda should be able to reuse the pool.
You can use middy middleware or serverless plugin to warmup your lambda and prevent cold start.
Also lambdas never run forever, the maximum execution duration per request is 300 seconds doc and of course, you can set your own (lower) timeout.
That being said, it's a risky path and should be used with caution.
I'd like to use Postgresql as a database on my AWS lambda functions but I'm worried about performance.
I'm worried that Lambdas are stateless and only exist in the time they're executing so I imagine every time the Lambda is triggered it'll try to initiate a brand new PG connection.
I'm not sure if this decreases performance or causes issues with stale connections somehow. Anyone know more about this?
I know DynamoDB is more in line with Lambda but I really need a relational database but at the same time Lambda's scalability.
You can make use of the container execution model of AWS lambda. When a lambda is invoked, AWS spins up a container to run the code inside the handler function. So if you define the PG connection outside the handler function it will be shared among the invocations of Lambda functions. You can find that in the above link.
Any declarations in your Lambda function code (outside the handler code, see Programming Model) remains initialized, providing additional optimization when the function is invoked again. For example, if your Lambda function establishes a database connection, instead of reestablishing the connection, the original connection is used in subsequent invocations. You can add logic in your code to check if a connection already exists before creating one.
const pg = require('pg');
const client = new pg.Client(<connection_string>);
exports.handler = (event, context, cb) => {
client.query('SELECT * FROM users WHERE ', (err, users) => {
// Do stuff with users
cb(null); // Finish the function cleanly
});
};
Refer this blog post.
But there is a caveat.
When you write your Lambda function code, do not assume that AWS Lambda always reuses the container because AWS Lambda may choose not to reuse the container. Depending on various other factors, AWS Lambda may simply create a new container instead of reusing an existing container.
Additionally you can create a scheduled job to warm up lambda function. (runs in every 5mins)
The only way I have found to "catch" EPIPE errors thrown asynchronously by a socket timing out or closing prematurely is to directly attach an event handler to the socket object itself, as demonstrated in the documentation here:
https://nodejs.org/api/errors.html
const net = require('net');
const connection = net.connect('localhost');
// Adding an 'error' event handler to a stream:
connection.on('error', (err) => {
// If the connection is reset by the server, or if it can't
// connect at all, or on any sort of error encountered by
// the connection, the error will be sent here.
console.error(err);
});
This works, but is in many cases unhelpful -- if you're accessing a database or another service that has a node driver, the request and socket objects are likely inaccessible from your app code.
The most obvious solution is "don't do things that generate these errors" but since any non-trivial application is dependent on other services, no amount of input-checking in advance can guarantee that the service on the other end won't hang up unexpectedly, throwing an EPIPE in your code and in all likelihood crashing Node.
So, the options for handling this situation seem to be:
Let the error crash your app and use nodemon or supervisor to automatically restart. This isn't clean, but it seems like the only way to really guarantee you'll get back up and running safely.
Write custom connection clients for dependent services. This let's you attach error handlers where known problems could occur. But it violates DRY and means that you're now on the hook for maintaining your own custom client code when otherwise reasonable open source solutions already exist. Basically, it adds a huge maintenance burden for a slightly cleaner solution to a fairly rare problem.
Am I missing something, or are those the best options available?
I'm looking to create a RESTful API using AWS Lambda/API Gateway connected to a MongoDB database. I've read that connections to MongoDB are relatively expensive so it's best practice to retain a connection for reuse once its been established rather than making new connections for every new query.
This is pretty straight forward for normal applications as you can establish a connection during start up and reuse it during the applications lifetime. But, since Lambda is designed to be stateless retaining this connection seems to be less straight forward.
Therefore, I'm wondering what would be the best way to approach this database connection issue? Am I forced to make new connections every time a Lambda function is invoked or is there a way to pool/cache these connections for more efficient queries?
Thanks.
AWS Lambda functions should be defined as stateless functions, so they can't hold state like a connection pool.
This issue was also raised in this AWS forum post. On Oct 5, 2015 AWS engineer Sean posted that you should not open and close connection on each request, by creating a pool on code initialization, outside of handler block. But two days later the same engineer posted that you should not do this.
The problem is that you don't have control over Lambda's runtime environment. We do know that these environments (or containers) are reused, as describes the blog post by Tim Wagner. But the lack of control can drive you to drain all your resources, like reaching a connection limit in your database. But it's up to you.
Instead of connecting to MongoDB from your lambda function you can use RESTHeart to access the database through HTTP. The connection pool to MongoDB is maintained by RESTHeart instead. Remember that in regards to performance you'll be opening a new HTTP connection to RESTHeart on each request, and not using a HTTP connection pool, like you could do in a tradicional application.
You should assume lambdas to be stateless but the reality is that most of the time the vm is simply frozen and does maintain some state. It would be inefficient for Amazon to spin up a new process for every request so they often re-use the same process and you can take advantage of this to avoid thrashing connections.
To avoid connecting for every request (in cases where the lambda process is re-used):
Write the handler assuming the process is re-used such that you connect to the database and have the lamba re-use the connection pool (the db promise returned from MongoClient.connect).
In order for the lambda not to hang waiting for you to close the db connection, db.close(), after servicing a request tell it not wait for an empty event loop.
Example:
var db = MongoClient.connect(MongoURI);
module.exports.targetingSpec = (event, context, callback) => {
context.callbackWaitsForEmptyEventLoop = false;
db.then((db) => {
// use db
});
};
From the documentation about context.callbackWaitsForEmptyEventLoop:
callbackWaitsForEmptyEventLoop
The default value is true. This property is useful only to modify the default behavior of the callback. By default, the callback will wait until the Node.js runtime event loop is empty before freezing the process and returning the results to the caller. You can set this property to false to request AWS Lambda to freeze the process soon after the callback is called, even if there are events in the event loop. AWS Lambda will freeze the process, any state data and the events in the Node.js event loop (any remaining events in the event loop processed when the Lambda function is called next and if AWS Lambda chooses to use the frozen process). For more information about callback, see Using the Callback Parameter.
Restheart is a REST-based server that runs alongside MongoDB. It maps most CRUD operations in Mongo to GET, POST, etc., requests with extensible support when you need to write a custom handler (e.g., specialized geoNear, geoSearch query)
I ran some tests executing Java Lambda functions connecting to MongoDB Atlas.
As already stated by other posters Amazon does reuse the Instances, however these may get recycled and the exact behaviour cannot be determined. So one could end up with stale connections. I'm collecting data every 5 minutes and pushing it to the Lambda function every 5 minutes.
The Lambda basically does:
Build up or reuse connection
Query one record
Write or update one record
close the connection or leave it open
The actual amount of data is quite low. Depending on time of the day it varies from 1 - 5 kB. I only used 128 MB.
The Lambdas ran in N.Virgina as this is the location where the free tier is tied to.
When opening and closing the connection each time most calls take between 4500 - 9000 ms. When reusing the connection most calls are between 300 - 900 ms. Checking the Atlas console the connection count stays stable. For this case reusing the connection is worth it. Building up a connection and even disconnecting from a replica-set is rather expensive using the Java driver.
For a large scale deployment one should run more comprehensive tests.
Yes, there is a way to cache/retain connection to MongoDB and its name is pool connection. and you can use it with lambda functions as well like this:
for more information you can follow these links:
Using Mongoose With AWS Lambda
Optimizing AWS Lambda(a bit out date)
const mongoose = require('mongoose');
let conn = null;
const uri = 'YOUR CONNECTION STRING HERE';
exports.handler = async function(event, context) {
// Make sure to add this so you can re-use `conn` between function calls.
context.callbackWaitsForEmptyEventLoop = false;
const models = [{name: 'User', schema: new mongoose.Schema({ name: String })}]
conn = await createConnection(conn, models)
//e.g.
const doc = await conn.model('User').findOne({})
console.log('doc: ', doc);
};
const createConnection = async (conn,models) => {
// Because `conn` is in the global scope, Lambda may retain it between
// function calls thanks to `callbackWaitsForEmptyEventLoop`.
// This means your Lambda function doesn't have to go through the
// potentially expensive process of connecting to MongoDB every time.
if (conn == null || (conn && [0, 3].some(conn.readyState))) {
conn = await mongoose.createConnection(uri, {
// Buffering means mongoose will queue up operations if it gets
// disconnected from MongoDB and send them when it reconnects.
// With serverless, better to fail fast if not connected.
bufferCommands: false, // Disable mongoose buffering
bufferMaxEntries: 0, // and MongoDB driver buffering
useNewUrlParser: true,
useUnifiedTopology: true,
useCreateIndex: true
})
for (const model of models) {
const { name, schema } = model
conn.model(name, schema)
}
}
return conn
}
Unfortunately you may have to create your own RESTful API to answer MongoDB requests until AWS comes up with one. So far they only have what you need for their own Dynamo DB.
The short answer is yes, you need to create a new connection AND close it before the lambda finishes.
The long answer is actually during my tests you can pass down your DB connections in your handler like so(mysql example as that's what I've got to hand), you can't rely on this having a connection so check my example below, it may be that once your Lambda's haven't been executed for ages it does lose the state from the handler(cold start), I need to do more tests to find out, but I have noticed if a Lambda is getting a lot of traffic using the below example it doesn't create a new connection.
// MySQL.database.js
import * as mysql from 'mysql'
export default mysql.createConnection({
host: 'mysql db instance address',
user: 'MYSQL_USER',
password: 'PASSWORD',
database: 'SOMEDB',
})
Then in your handler import it and pass it down to the lambda that's being executed.
// handler.js
import MySQL from './MySQL.database.js'
const funcHandler = (func) => {
return (event, context, callback) => {
func(event, context, callback, MySQL)
}
}
const handler = {
someHandler: funcHandler(someHandler),
}
export default handler
Now in your Lambda you do...
export default (event, context, callback, MySQL) => {
context.callbackWaitsForEmptyEventLoop = false
// Check if their is a MySQL connection if not, then open one.
// Do ya thing, query away etc etc
callback(null, responder.success())
}
The responder example can he found here. sorry it's ES5 because that's where the question was asked.
Hope this helps!
Official Best Practice for Connecting from AWS Lambda
You should define the client to the MongoDB server outside the AWS
Lambda handler function. Don't define a new MongoClient object each
time you invoke your function. Doing so causes the driver to create a
new database connection with each function call. This can be expensive
and can result in your application exceeding database connection
limits.
As an alternative, do the following:
Create the MongoClient object once.
Store the object so your function can reuse the MongoClient across function invocations.
Step 1
Isolate the call to the MongoClient.connect() function into its own module so that the connections can be reused across functions. Let's create a file mongo-client.js for that:
mongo-client.js:
const { MongoClient } = require('mongodb');
// Export a module-scoped MongoClient promise. By doing this in a separate
// module, the client can be shared across functions.
const client = new MongoClient(process.env.MONGODB_URI);
module.exports = client.connect();
Step 2
Import the new module and use it in function handlers to connect to database.
some-file.js:
const clientPromise = require('./mongodb-client');
// Handler
module.exports.handler = async function(event, context) {
// Get the MongoClient by calling await on the connection promise. Because
// this is a promise, it will only resolve once.
const client = await clientPromise;
// Use the connection to return the name of the connected database for example.
return client.db().databaseName;
}
Resources
For more info, check this Docs.
We tested an AWS Lambda that connected every minute to our self managed MongoDB.
The connections were unstable and the Lambda failed
We resolved the issue by wrapping the MongoDB with Nginx reverse proxy stream module:
How to setup MongoDB behind Nginx Reverse Proxy
stream {
server {
listen <your incoming Mongo TCP port>;
proxy_connect_timeout 1s;
proxy_timeout 3s;
proxy_pass stream_mongo_backend;
}
upstream stream_mongo_backend {
server <localhost:your local Mongo TCP port>;
}
}
In addition to saving the connection for reuse, increase the memory allocation for the lambda function. AWS allocates CPU proportionally to the memory allocation and when changing from 128MB to 1.5Gb the connection time dropped from 4s to 0.5s when connecting to mongodb atlas.
Read more here: https://aws.amazon.com/lambda/faqs/
I was facing the same issue few times ago but I have resolved with by putting my mongo on same account of EC2.
I have created a mongo DB on the same AWS EC2 account where my lambda function reside.
Now I can access my mongo from the lambda function with the private IP.