Operations | Monitoring | ITSM | DevOps | Cloud

It's Friday afternoon, and you have mail. Apparently, a user received a 500 error when attempting to sign in. She contacted Customer Service. They didn't know what to do, so they forwarded the email to your engineering team. A close look at the email thread reveals that Customer Service received it... on Tuesday. And they sat on it until today. ‍ Hopefully, it was just this one user. You open your browser, navigate to the web application, and attempt to sign in. You also get a 500 error.

Today it’s not unusual to see organizations having implemented mocking in their daily workflow, as mock APIs allow developers to speed up their development and not rely on external services. For those reasons and others, many engineers are looking to learn more about the mocked APIs and how they can best be implemented into their organization.

A SIEM (Security Information Event Management) platform, along with several other tools that make you crave Alphabet Soup (XDR, UBA, NDR, etc), is a critical component of any organization’s security infrastructure. Between a constantly growing volume of logs, increasing attacks and breaches, and challenges finding qualified staff, many organizations may consider a SIEM migration. There could be several reasons for this.

There have been amazing articles on the subjects of migrating from a monolith to a microservice architecture e.g. this is probably one of the better examples. The benefits and drawbacks of the architectures should be pretty clear. I want to talk about something else though: the strategy. We build monoliths since they are easier to get started with. Microservices usually rise out of necessity when our system is already in production.

When building systems that need to scale above a certain number of users, we usually can’t stay on one machine. This is where cloud providers like AWS usually come into play. They allow us to rent VMs or containers for small intervals. This way, we can start a few different machines when more traffic hits, and when it goes down later, we can simply turn off our extra capacity and save money. The question is, how does all this traffic get to our new machines? AWS Elastic Load Balancing!