The concept of unified IT observability has gained newfound importance in today’s world of remote work, hybrid infrastructures, and technological convergence. In this video, Christina Kosmowski, President at LogicMonitor, shares five tips on how to power your business forward and achieve unified IT observability during uncertain times.
There is an idea of the relationship between observability and monitoring, that they complement each other in an inseparable way. While true that you can only monitor a system that is observable, the line dividing observability and monitoring grows narrower with every deployment you make; making these two practices less of a pairing and more a single entity.
Software companies are in a constant pursuit to optimize their delivery flow and increase release velocity. But as they get better at CI/CD in the spirit of “move fast and break things,” they are also being forced to have a very sobering conversation about “how do we fix all those things we’ve been breaking so fast?” As a result, today’s cloud-native world is fraught with production errors, and in dire need of observability.
Kafka is a distributed, highly available event streaming platform which can be run on bare metal, virtualized, containerized, or as a managed service. At its heart, Kafka is a publish/subscribe (or pub/sub) system, which provides a "broker" to dole out events. Publishers post events to topics, and consumers subscribe to topics. When a new event is sent to a topic, consumers that subscribe to the topic will receive a new event notification.
IT Operations teams are often the bedrock of the digital business, ensuring that processes and services continue humming smoothly as developers continue to evolve and increase customer value. But increasingly complex systems can flood them with alerts that get in the way of operators from doing their best work and paving the way for new, innovative services.
The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to observability data. For another, most customers have to lean on a hodgepodge of tools that might blend open source and proprietary, require extensive onboarding as team members have to learn which tools are used for what, and have a steep learning curve in general.
After we’d fixed Aparna’s network issue, James came to see me at my desk. Masks on, socially distanced and all that, but it was nice to have some face-to-face time. James is cool – that dry British humor and not your classic IT Ops dude. He’s been here forever and mentored me when the CIO, Charlie, hired me as the first SRE here a year or so ago. I lucked out really.
Monitoring has always been a crucial operation in a software development cycle. This is mainly because of the complexity of industry-level IT and consumer-facing product development. Additionally, there is an ever-growing demand for rapid upgrades in products. To meet these requirements, streamlined performance and stability have become more important than ever; and without effective monitoring practices, they appear difficult to achieve.
Metrics measuring user engagement on your website are crucial for observability in marketing. Metrics will help marketing departments understand which of your web pages do not provide value for your business. Once known, developers can look at the web page’s technical metrics and determine if updates are required. Typically user engagement statistics, like the average time required to load your page, are stored separately from technical site logs.
Recently, we added a new derived column function to Honeycomb, INGEST_TIMESTAMP(), which can help customers debug event latency and/or inaccurate timestamps. A meaningful minority of the events sent to Honeycomb are already old when they arrive, and a very special few claim to have been sent from the future. Has this happened to you? Let’s do an experiment.
