In today’s world, the performance of your IT systems has a direct impact on your brand reputation and overall business revenue. A “good enough” approach to software performance is no longer good enough. This has led to the growing importance of SREs and a shift to more sophisticated, advanced observability that requires moving beyond basic on/off monitoring to advanced monitoring techniques.
You started the year with one Kubernetes cluster and now you have 100. How do you deal with that? This is a reality for many SREs, and as organizations scale their monitoring to address the growing complexity of their IT environments, SREs will inevitably encounter challenges. The key is to know what challenges to expect, so you can be prepared rather than surprised.
You started the year with one Kubernetes cluster and now you have 100. How do you deal with that? This is a reality for many SREs, and as organizations scale their monitoring to address the growing complexity of their IT environments, SREs will inevitably encounter challenges. The key is to know what challenges to expect, so you can be prepared rather than surprised.
This is my fifth company as CEO and I’ve really come to enjoy working in B2B enterprise software – the proverbial “picks and shovels” end of our industry. In particular I enjoy innovating in spaces that may not be immediately obvious and typically overlooked in the mad gold rush of today’s frothy venture capital scene.
A lot of companies bequeath the projects that they build internally unto the world as open source. But they’re usually up for a pretty rude awakening when they ship their software and it has to be run for the first time by someone other than them.
Telemetry data – the metrics and measurement data emitted by all machines and devices from servers to robots – is exploding. Telemetry data generation is growing so fast, there are no reliable estimates of just what that growth rate looks like. Theo Schlossnagle, founder of Circonus and widely respected computer scientist, estimates that telemetry data is growing at the rate of 1×1012 every ten years. Suffice to say, that’s a lot.
The monitoring industry is changing rapidly. Gartner reports that by 2022, 50% of enterprise-generated data will be created and processed outside of a traditional data center or cloud, up from less than 10% in 2019 and that number could reach 75% by 2025.
Complex architectures, pressures to deploy faster, and demand for optimal performance have placed greater strain on monitoring teams and as a result, an increasing number are looking to implement more advanced monitoring techniques. Part of the initial challenge around this is understanding what advanced monitoring techniques actually are. In this article, I help clarify this by differentiating basic and advanced monitoring, with examples on how each would be applied to Postgres monitoring.
Whether you’re just beginning your monitoring journey or are a seasoned pro, being reminded of monitoring’s core principles is still helpful. From my own experience as a former SRE to what I’ve seen from our customers at Circonus, here are 10 essential monitoring tenets to live by.
In our era of rapid release cycles, engineers make frequent API updates in an effort to constantly improve user experiences. But while updates are designed with user benefits in mind, they can also have the opposite effect — potentially creating new performance issues. Ensuring that your APIs are meeting performance requirements and SLOs as you release new updates is dependent on correctly monitoring API latencies.
