Operations | Monitoring | ITSM | DevOps | Cloud

The past ten years marked a significant change in how software teams build and deploy applications. We moved away from bulky, slow, monolithic applications toward lightweight, scalable, distributed service-based applications. Meanwhile, tools like Docker, Kubernetes, and other container platforms helped accelerate this process. Despite this sudden growth, a fundamental question remains: what exactly is a service, and how does it fit into a microservice architecture?

When it comes to building reliable and scalable software, few organizations have as much authority and expertise as Google. Their Site Reliability Engineering Handbook, first published in 2016, details their practices to maintain reliability as Google scaled. But when you have over a million servers running thousands of services across more than twenty data centers, how do you monitor them in a consistent, logical, and relevant way?

With the right load balancing in place, the demand of increasing web traffic can become manageable, but how do you determine which load balancing algorithm is best suited for your applications? Does the ease of use of static load balancing better suit the services you provide, or would your system benefit from a more complex and dynamic set of algorithms to maximize efficiency? In this blog post, we discuss what to consider when deciding on the right load-balancing algorithm.