Staff Software Engineer Danila Sudbin on the experience and benefits of building highload systems

The ability to handle high load on servers is an important indicator of equipment in terms of security, stability, and maintenance costs. In modern conditions, the use of systems that are capable of processing a large number of requests becomes a necessity. Staff Software Engineer Danila Sudbin has been building and implementing high-load systems for more than 5 years. He spoke about the basic principles of work, the importance of the developer's work, and the benefits of using such systems. This article will be useful for both business owners and employees from the HR field to understand what skills a specialist who works with such systems should have.

Learn more about the principles of operation of a highly loaded system

A highly loaded system is a system that can process a large number of requests simultaneously. For example, a social network that processes millions of requests for viewing and publishing content, or an online store that receives thousands of orders a day. It is important to understand that highly loaded systems require careful design and implementation so that they can work stably and without failures. When developing such systems, the following factors should be taken into account:


1. Load distribution: It is necessary to distribute the load evenly and thereby improve performance. The system should be divided into several components that can work in parallel.
2. Scaling: Depending on the needs, it is necessary that it can be easily increased or decreased.
3. Reliability: Any shutdown of the system leads to large financial losses - the system must be reliable so that it can work without failures even under high load.

About the importance of a developer who knows how to work with highly loaded systems

A specialist with experience working with highly loaded systems is a valuable employee for any employer. The knowledge and skills needed to develop and maintain such systems are acquired over the years. The cost of an error in the implementation of such systems is too high and therefore employees who can implement them qualitatively are highly valued.

Only such a specialist can help develop a system that can process millions of requests per second. This may be necessary for a bank that receives a large number of transactions per day or, for example, for a search browser that processes millions of requests for content. In addition, it can help scale the system so that it can handle more requests without compromising performance. This may be necessary for a business that is experiencing rapid growth, or for a system that needs to handle peak loads.

The benefits of using high-load systems

Highly loaded systems ensure the smooth operation of many services that we use every day (for example, services of FAANG companies - Facebook, Amazon, Apple, Netflix, Google), and full implementation provides you with the following opportunities:

Make payments without worrying about the potential loss of funds. For example, due to the low speed of checking the balance history, a fraudster can simultaneously withdraw funds from your card with you.

You can communicate with friends and family on social networks, with a stable connection.

You can consume streaming videos and listen to music without interruptions.

In general, the use of a highly loaded architecture is an inevitable part of the evolution of the product, which appears with a large number of users of the service.

Recommendations for security and fault tolerance

Ensuring the security and fault tolerance of highly loaded systems is a difficult task. However, using the right methods and tools can improve the reliability and efficiency of the system. Let's look at them with specific examples:

Safety

Authentication and Authorization: Using two-factor authentication (2FA) to increase the security of user accounts.

Encryption: Using data encryption to protect it from unauthorized access.

Implementation of an intrusion detection system (IDS) to detect and prevent attacks on the system.

Using a backup system to restore data in case of loss.

Fault tolerance

Using clustering to ensure fault tolerance in the event of a failure of one of the system instances.

Using replication to create copies of data or system components.

Using load balancing to improve system performance.

When choosing methods for ensuring security and fault tolerance in such systems, it is necessary to take into account the size of the budget, as this may take a lot of time and resources.

Here are some recommendations for ensuring the security and fault tolerance of highly loaded systems: use several methods to increase reliability, do not rely on one method of ensuring security or fault tolerance, and automate the processes of ensuring security and fault tolerance. This will help save time and resources, and create a monitoring system. This will help you quickly identify and fix problems.

Knowledge of which technologies and tools for a developer should be paid attention to when hiring (useful for HR and CEO)

I will highlight the most common technologies and tools that are used in the construction of high-load systems. Among them, there are:

Operating systems: those that are optimized to work in a distributed environment. Examples of such operating systems are Linux, Ubuntu, FreeBSD, and Solaris.

Servers: with the ability to process a large number of requests simultaneously. Examples of such servers are Intel Xeon and AMD EPYC servers.

Databases: When choosing databases, it is also important to remember about the need to process a large number of requests at the same time. Examples of such databases are MySQL, PostgreSQL, and Oracle.

Application servers: examples of such application servers are Nginx, Apache Tomcat, Jetty.

Monitoring: Prometheus, Grafana, and Nagios can be used.

What nuances of system design should the owner know for the surface control of his product

To understand the architecture, it is necessary to understand the CAP theorem and the fact that at high loads, only 2 of the 3 parameters can be selected.

(C) Consistency. All clients see the same data at the same time, regardless of which node they connect to. To do this, they need to be synchronized with other nodes even before the first response with this data returns.

(A) Availability. Any client requesting data receives a response, even if one or more nodes are down. In other words, all the working nodes of a distributed system return a response to any request without exception.

(P) Partition tolerance. There is no communication gap between the servers and, accordingly, there is no response delay.

Depending on the product, we choose two options out of three possible:

(AP) There is availability and partition tolerance, but the data is not consistent - Products: social networks, as it is important for the user to have content and its constant availability, not accurate data.

(CA) There is consistency and availability, but a single node failure causes a delay. That is, we will always get the correct data in the response - just the response time can be increased. A classic example of a CA system is a distributed LDAP directory service, as well as relational databases (PostgreSQL, MySQL, MariaDB, MS SQL Server, etc.)

(CP) The data will be consistent and safe even if the connection between the nodes is lost. Products: these are mainly fintech since the amount of funds on the user's balance is important

Industry trends

Trends in microservices and cloud technologies are popular. This is due to the growing popularity of Internet services that require high performance and scalability. Microservices are an architectural style in which a system consists of small, independent services interacting with each other via an API.

The use of containers and microservices allows you to split the system into smaller, independent parts, which makes it easier to scale and manage the system. Containers can be easily scaled by adding or removing them as needed. It is also easy to scale Microservices because each service can scale independently of other services.

Cloud technologies provide a scalable and affordable infrastructure, which makes them an ideal choice for high-load systems. Cloud providers offer a wide range of services that can be used to create and scale highly loaded systems.

For example, Amazon Web Services offers the Elastic Beanstalk service, which allows developers to quickly and easily deploy applications in the cloud. Google Cloud Platform offers the App Engine service, which provides fully managed platforms for web applications, mobile applications, and containers.

In general, the potential for the development of high-load systems in 2023 remains high. This is due to the continued growth in the popularity of Internet services and the development of new technologies that can be used to improve the efficiency of high-load systems.