In a professional tone: Separate database server is not only required but recommended for many reasons. The biggest benefit of having a separate database server is that it provides you with a way to scale your application by adding more servers to handle the load.
The first step toward scaling an application is to separate the database from the web tier. This allows you to add additional web servers, which can handle more traffic and serve requests faster.
When it comes to scaling applications, the most common approach is to use multiple web servers. Each web server can be configured with its own set of static content, such as images and CSS files, and it can also have its own instance of MySQL or PostgreSQL installed on it.
Separate Server For Database
You can’t just scale the API and DB on the same server. They are completely separate systems and need to be scaled separately.
You can use a multi-server architecture, where you have multiple servers behind a load balancer, but then you have to worry about the load balancer itself being overloaded or having issues. And you need to add more servers if traffic increases significantly.
In a real world scenario, I would try to avoid updating 10000 servers at once by using an incremental update approach. This means that you update one server at a time, wait for it to become healthy, then update another one and so on until all servers are updated. You can configure your application so it only accepts connections from healthy servers (you might need some kind of failover mechanism in case some servers go down).
In the real world, we don’t have the luxury of having a separate server for our database. In this article, I will explain how to scale a web application with millions of users.
We will start by understanding the common multi-server architecture, which is used by most companies and then move on to understand how to scale multiple servers at once.
Multi-server architecture
In this type of architecture, all servers are connected to a single database server via a network and all requests are routed through this central server. The main advantage of such an architecture is that it helps in reducing load on individual servers as well as on the database server.
This type of architecture is commonly used by large corporations like Google or Facebook to power their websites and apps. In such companies, each developer has access to only one machine, which runs multiple virtual machines on top of it. These virtual machines are connected using virtual networks and they act as separate servers within the company’s infrastructure but they’re still running on just one machine!
For a web application with millions of users, there are many things to consider when scaling it. In this article, I will talk about the database aspect of scaling.
I’m going to explain how you can scale a web application with millions of users.
Let’s say you have a website which is receiving 10,000 requests per second. This website has an API and a database. You can’t split the database and the API because they are tightly coupled. So, the only way to scale this web application is to scale each server separately.
You will have to have a separate server for each database and another one for your API. In this case, your architecture will look like this:
Now let’s say you want to add more capacity to this system. You need more servers but you don’t want to add them on top of this architecture as it will make it difficult for future scaling needs. Instead, we can move our database server outside of our application servers by creating a separate network for our database servers:
The above architecture makes it easy for us to scale our application in the future.
When you have a large database with many users and many requests, it is important to separate the API from the database. Otherwise, you might end up with a lot of contention on your database servers.
Separate API Server
The API server should be its own machine or cluster of machines. The reason for this is because the API server will be receiving requests from all clients (web browsers, mobile apps, etc.). These requests can come in at any time and they will have varying amounts of data (some may have nothing while others may be huge). You don’t want to impact your database by having a lot of requests coming in at once and causing contention on your database servers. Also, if one of these requests fails for whatever reason (like a network issue), you don’t want that failure to propagate over to other users because now they are getting errors from their database query when they shouldn’t be getting anything yet!
In my opinion, the best way to update 10000 servers in a real world scenario without impacting the end customers is:
– API and database on same server (best practice)
– Multi server architecture
– Multi server architecture with load balancing and failover.
– How to scale a web application with millions of users? Make it scalable! The more you handle requests, the more money you earn. So don’t be afraid of scaling up your application or services as much as possible.
There are some things that you should consider when designing your architecture:
1 – Availability – one of the most important criteria when designing an application’s architecture is availability. You have to make sure that your application will work 24/7 without any downtime and in case of failures it can recover automatically without user intervention. For example, if one of your servers fails, another one should be able to take over all its workloads without any problems at all. This kind of high availability can be achieved through redundancy and load balancing technologies like Microsoft NLB or F5 BigIP LTM which are available as part of Windows Azure Virtual Machines (VMs).
In this blog post, we will explore an example of how to update 10000 servers at once without impacting the end customers.
This is a real world scenario and the goal is to update the api and database on same server.
In order to achieve this, we will be using multi server architecture. This means that we have multiple servers running the same codebase but each server is serving a different subset of traffic.
I would think of a multi-server architecture where the API and database are on the same server, and then have many more servers which handle web traffic.
This way you can scale up/down your web app without having to manually update each server.
You might also want to consider using a CDN (or multiple CDNs) for your static assets (images, JS files etc), so that if one server goes down, it doesn’t bring down the whole thing.
In the real world, you would use a multi-server architecture. Each server would have its own copy of the API and database, but they would all be running on the same hardware.
When you want to update the API, you can update each server individually and then run tests to make sure they still work. Then when everything is working, you can go live with all of them at once by updating them all simultaneously.
You might be thinking that now you have to manage 10x more servers — but in fact it’s no different than managing one big server before. In both cases, you need to make sure that each server is properly configured and secure; in both cases there needs to be some sort of monitoring so that when one goes down it’s easy to notice and fix; etc., etc., etc..
The big difference is that instead of doing all the work yourself (which means tons more hours spent configuring things), you can just buy 10x more servers from Amazon Web Services or Google Cloud or whatever (they’ll even do most of the configuration for you).
I would have to say that it depends on the application and what you are trying to accomplish. If you are just looking for a quick way to update all of your servers, then I don’t see why you would need to do it one by one.
A simple example:
You have 10000 servers and each server has 2 instances of Apache2 and MySQL running. You have an API running on port 8080 and a database running on port 3306. Your API is written in PHP and communicates with your database through mysqli. Your database has a table called “user” that contains user information. Currently there is 1 row in this table with a username of “user1”.
You want to update the row in this table so that it now has a username of “user2”.
Here’s how I would do it:
1) Stop/restart Apache2 on all 10000 servers
2) Run mysqldump on all 10 000 servers and store them locally (or remotely) so they can be accessed later
3) Modify the table locally (or remotely), adding another row with the desired username and modifying the username from user1 to user2
4) Copy over all 10 000 dump files locally (or remotely) so they can be.
Database Scaling
The most common way to scale a database is by using a separate server for it. This is done by either using master-master replication or master-slave replication. Both approaches have their own pros and cons but they are both better than using one server to host both the api and the database.
One advantage of using multi servers is distribution of load. If you have 100k requests per minute coming in, you can distribute them evenly among 10 servers and then have each server handle 10k requests per minute. Another advantage is that if one server goes down due to an outage, your system is still alive because other servers are still responding. Also, if one server has a problem like high memory usage or load spikes then other servers can take over its share of requests until the problem on that server gets resolved. Another benefit is that if you need more resources for an additional request coming in than what you have available on a single server then you can use multiple servers so each request gets its own resources.