A practitioner's guide to building scalable systems

Building Scalable Systems: Distributed Systems basics to System Design Interviews

We want to give you the tools to compare multiple approaches and pick the one that works for your scenario.

Grokking the Distributed and Scalable Systems

# What engineers need to know about Data Centers?
We all know what Data Centers are. They are massive buildings where large companies pack a lot of computers that are connected to each other and to the Internet. All of the cloud computing provides (AWS, Azure, GCloud) own massive data centers in many parts of the world. Many of these data centers are 

* Built on millions of square feet of land
* Hosts hundreds of thousands of computers
* Offers hundreds of Exabytes of storage provided by thousands of disks
* Has a massive network transmitting TBs of data every minute.

As Software Engineers, we don't need to understand the finer details of how power transmission, cooling and other aspects of the data center are taken care of. However, it is good to know a few things about data centers that will help you in designing better software.

## 1. Computing is capped by the Megawatts

Power infrastructure is the backbone of the Data Center. Typically, a small grid is established close to the Data Canter that provides electricity to the data center. The capacity of that grid caps the total amount of computing power that the Data Center can pack. 

Data Centers require a lot of power - not only to run the computers but also for cooling (or heating based on the location) as a lot of heat is generated in data centers.

### Watts per Square foot
A unit that Data Designers use is called Watts per Square Foot or WPSF.


What and Why

Node in a Distributed System

Performance and Numbers

Fault Tolerance and Availability

Understanding TIME in Distributed Systems

Data Centers for software engineers

Scaling Distributed Systems

Load Balancers

Structured Storage at Scale

Sharding in Storage Systems

SQL vs NO-SQL

Blob Storage at Scale

Caching in Distributed Systems

Queues and Asynchronous Processing

Data Analytics and Batch Processing

Logging and Monitoring

Searching at Scale

Conclusion

Data Center for Software Engineers

What engineers need to know about Data Centers?