When you are configuring your event log monitor settings, you need to decide which event log events you need to worry about. Event logs are generated for a wide array of processes, applications, and events. Logs will record both successes and failures. As such, you need to decide what data is most vital and needs your immediate attention.

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.

Logz.io is focused on creating the best observability service to manage the scale of monitoring, add value on top of AI/ML technologies, and enhance enterprise security. Metrics is one of the pillars of Logz.io, and our Prometheus-as-a-Service offering. It has been a crucial part of our platform goals, but if we turn the clocks back a year, our service only used the open-source Elasticsearch database (ES).

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.

My Grafana Labs colleague RichiH recently talked about why IoT and time series databases work so well together. It just so happens that we have a highly scalable time series database on hand. Let’s talk about that. My name is Goutham, and I am a maintainer for Cortex. I have been working on it for nearly three years out of the four-and-a-half years the project has existed. Cortex is built to serve as a scalable, long-term store for Prometheus.

Monitoring the current state and performance of applications is critical for IT Ops and DevOps teams alike. Understanding the health of an application is one of the most effective ways of anticipating potential bottlenecks or slowdowns, yet it’s one of the largest challenges faced by many organizations that build and deploy software. This is largely due to applications’ distributed and diversified nature.

In this first edition of our Customer Spotlight series, we are joined by James Kahn and Ben Gittins of Idea 11. Idea 11 is an award-winning, full-stack AWS IT company that specializes in digital transformations, cloud infrastructure, software development and managed services.

Over a year after COVID-19 was declared a global pandemic, the hope of speaking about it in the past tense is something we all still hold on to. Not only are we still being challenged by it in the present, but it has changed the way we think and do many things. However, just because something has become normalized over time (out of necessity) doesn’t mean that everyone has adjusted without incident.