Software Engineering Daily

Kafka is at the center of modern streaming systems. Kafka serves as a database, a pubsub system, a buffer, and a data recovery tool. It’s an extremely flexible tool, and that flexibility has led to its use as a platform for a wide variety of data intensive applications. Today’s guest is Gwen Shapira, a product manager at Confluent. Confluent is a company that was started by the creators of ApacheContinue reading...

Streaming architecture defines how large volumes of data make their way through an organization. Data is created at a user’s smartphone, or on a sensor inside of a conveyor belt at a factory. That data is sent to a set of backend services that aggregate the data, organizing it and making it available to business analysts, application developers, and machine learning algorithms. The velocity at which data is created hasContinue reading...

At a big enough scale, every software product produces lots of data. Whether you are building an advertising technology company, a social network, or a system for IoT devices, you have thousands of events coming in at a fast pace that you want to aggregate, study and act upon. For the last decade, engineers have been learning to store and process these vast quantities of data. The first common techniqueContinue reading...

Over 12 years of engineering, Box has developed a complex architecture of services. Whenever a user uploads a file to Box, that upload might cause 5 or 6 different services to react to the event. Each of these services is managed by a set of servers, and managing all of these different servers is a challenge. Sam Ghods is the cofounder and services architect of Box. In 2014, Sam wasContinue reading...

When Box started in 2006, the small engineering team had a lot to learn. Box was one of the earliest cloud storage companies, with a product that allowed companies to securely upload files to remote storage. This was two years before Amazon Web Services introduced on-demand infrastructure, so the Box team managed their own servers, which they learned how to do as they went along. In the early days, theContinue reading...

Applications need to be ready to scale in response to high-load events. With mobile applications, this can be even more important. People rely on mobile applications such as banking, ride sharing, and GPS. During Black Friday, a popular ecommerce application could be bombarded by user requests–you might not be able to complete a request to buy an item at the Black Friday discount. If you attend the Superbowl, and thenContinue reading...

Your friends from college are asking you how to buy Bitcoin. Your mom is emailing you articles about the benefits of decentralized peer-to-peer networks. Your shoe shiner is telling you to buy XRP. It is 2018, and cryptocurrencies have become a daily part of news headlines. The general public may not understand how this technology works, but everyone knows that changes are on the horizon. At some point in theContinue reading...

Over the last decade, computation and storage has moved from on-premise hardware into the cloud data center. Instead of having large servers “on premise,” companies started to outsource their server workloads to cloud service providers. At the same time, there has been a proliferation of devices at the “edge.” The most common edge device is your smartphone, but there are many other smart devices that are growing in number–drones, smartContinue reading...

How do you build resilient, failure tested systems? Redundancy, backups, and testing are all important. But there is also an increasing trend towards chaos engineering–the technique of inducing controlled failures in order to prove that a system is fault tolerant in the way that you expect. In last week’s episode with Kolton Andrus, we discussed one way to build chaos engineering as a routine part of testing a distributed system.Continue reading...

The number of ways that applications can fail are numerous. Disks fail all the time. Servers overheat. Network connections get flaky. You assume that you are prepared for such a scenario, because you have replicated your servers. You have the database backed up. Your core application is spread across multiple availability zones. But are you really sure that your system is resilient? The only way to prove that your systemContinue reading...