With tracing, for example, we can more reliably determine the state of application performance and the service being delivered by measuring all the work being done across many dependencies it builds a more observable system. Many of these do a great job at externalizing key application events through logs, metrics and events. There are many practices that contribute towards observability, some of which can be found in products and tools. It’s critical therefore that modern instrumentation should be employed to better understand the properties of an application and its performance as complex distributed systems take shape across the delivery pipeline and into production. As organizations move towards containerized workloads and dynamic microservice architectures, old practices of bolting on monitoring after the fact no longer scale. Observability is important today when we consider both the characteristics of modern applications and the pace at which they’re being delivered. I’m no engineer, but that makes good sense. Therefore, if our good old IT systems and applications don’t adequately externalize their state, then even the best monitoring can fall short. So in contrast to monitoring which is something we actually do, observability (as a noun), is more a property of a system. The term actually comes from the world of engineering and control theory.īasically, and as the definition states, it’s a measure of how well internal states of a system can be inferred from knowledge of its external outputs. So what about this new term observability?Īs it turns out, observability isn’t new at all. Plus there’s synthetic transactions and application experience analytics to gain critical insights into the digital meanderings of our customers. During application development, folks use monitoring to correlate coding practices to performance outcomes, while architects can validate which cloud patterns and models deliver the most bang for the buck.Īnd to achieve all this goodness, monitoring tools use many nifty techniques like instrumentation and tracing to gather, digest, correlate and analyze rafts of metrics across modern application stacks under our watch. That’s the basic stuff, but monitoring has also evolved to support many more stakeholders. As troubleshooters, we use it to find the root cause of problems and gain insights into capacity requirements and performance trends over time. We monitor applications to detect problems and anomalies. From basic fitness tests and whether they’re up or down, to more proactive performance health checks. Monitoring is a verb something we perform against our applications and systems to determine their state. Monitoring Basicsįirst, let’s review what we all know and love (well most of us anyway) - monitoring. We’ve just got to find it in all the noise. So better buy some observability, right?īut before getting too excited, let’s carefully dissect the meaning of the term. So what is observability? Should we accept what many are stating - that it’s basically monitoring, only on steroids? Bigger, better, faster the new Chuck Norris of DevOps tools. The new buzzword kid on the blocks is observability and you can bet many companies will be using it willy-nilly to spruce up their products. It’s cool, hip and trending, so get on board and start the buzzword washing. Along comes some funky new term and suddenly everyone starts using it to describe their wares. It’s amusing to see how our industry flocks around the latest tech buzzword. Through his regular work with CA, Waterhouse covers key trends such as DevOps, mobility, cloud, and the Internet of Things. He is a business technologist with more than 20 years’ experience with development, strategy, marketing, and executive management. Peter Waterhouse is a senior strategist at CA Technologies.
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