Amazon EC2 offers a flexible and convenient way to run virtual machines in the cloud. With dozens of EC2 instance types available, as well as multiple pricing options, it’s easy to use EC2 to configure the best cloud-based virtual machines for your needs and budget. One thing that EC2 doesn’t make very easy on its own, however, is monitoring.

Implementing and operationalizing the best practices and capabilities of DevOps into an organization is a key predictor for increased customer satisfaction, organizational productivity and profitability. Doing so successfully can be a challenging endeavour. Implementing DevOps can be particularly difficult because it oftentimes requires technology changes, process changes and a drastic change in mindset.

As the shift to cloud, modern app architectures and technology stacks continue to accelerate, the demand for real-time analytics to monitor, troubleshoot, secure and speed new innovations to these environments is also accelerating. So, we're not surprised to see demand for continuous intelligence—what we define as: real-time analytics from a cloud-native platform, supporting multiple use cases—is also accelerating.

Logs are valuable. Logs generated by a major backend resource that provides clients with access to crucial data are more than just valuable; knowing where they are and being able to manage and understand the information that they contain can mean the difference between smooth, secure operation and degraded performance or even catastrophic failure for your application. MySQL Server produces a handful of basic logs.

As service architectures have transitioned from the monolith to microservices, one of the tougher problems that organizations have had to solve is service discovery and load balancing. The advent of service mesh technologies seeks to solve these and other problems exacerbated by the number of hosts that has grown exponentially. In this article, we’re going to explore what a service mesh is.

In this post, we continue our discussion of use cases involving account take over and credential access in enterprise data sets. In the first part of this series, we introduced the definition of a VIP account as any account that has privileged or root level access to systems/services. These VIP accounts are important to monitor for changes in behavior, particularly because they have critical access to key parts of the enterprise.