Streaming telemetry holds the promise of radically improving the reliability and performance of today’s complex network infrastructures, but it does come with caveats. In the first of a new series, Kentik CEO Avi Freedman covers streaming telemetry’s history and original development.

IT, DevOps, and security teams are figuring out the best ways to manage their complex, ever-growing, ever-changing environments. And one contributing factor to all the complexity is the rise of using multiple cloud services. One cloud service to manage is difficult enough, but adding more to the mix — each with its own interface and set of tools — makes everyone’s job significantly more difficult.

The benefits of going cloud-native are far reaching: faster scaling, increased flexibility, and reduced infrastructure costs. According to Gartner®, “by 2027, more than 90% of global organizations will be running containerized applications in production, which is a significant increase from fewer than 40% in 2021.” Yet, while the adoption of containers and Kubernetes is growing, it comes with increased operational complexity, especially around monitoring and visibility.

If you work as a CTO, then you already know that having robust monitoring and analytical tools for your technology stack is a prerequisite to getting your job done right. Many companies that started off using Datadog discovered that it can become prohibitively expensive and complex when they needed to scale. As such, there are a lot of people out there currently seeking out alternatives.

Overview of what is high cardinality in the context of monitoring using Prometheus and Grafana.

Monitoring disk space is a basic but core component of proactive IT support, critical to reducing ticket volume and maintaining system health and stability. Running low on or running out of disk space can obviously be responsible for a host of issues and user complaints — from application failures to complete system crashes — so creating alerts for when drives fall below a specified threshold is a great way to head those off.

Gaming apps are complex systems. They combine multi-function systems, like the game engine, to other resources such as server containers, proxies and CDNs in order to give users a real-time interactive experience. At the same time, managing cross-functional behavior also means that games could generate massive amounts of data, commonly known as logs. You’ll want to turn that data into useful information to help improve game performance.