Observability Blogs

MTTR (mean time to recovery) is a key performance measurement for any application. Observability helps you reduce MTTR dramatically. Learn how and try it today.

Dive into our newly released State of Observability 2021 report to discover how leaders in observability continue to outpace their competitors and have more reliable applications, better performance metrics, and increased ability to innovate.

In this blog post, we discuss the recent Fastly outage, examine how traditional monitoring technologies would have responded to that outage, and show how adopting Digital Experience Monitoring inside your Observability practice is crucial to detecting and responding to these types of issues.

Learn how to collect and monitor Kafka performance metrics with Splunk Infrastructure Monitoring using OpenTelemetry — a vendor-neutral and open framework to export telemetry data.

In this three part blog series, we take a deep dive into Kafka architecture, the key performance characteristics that you should monitor and how to collect telemetry data to gain real-time observability into the health and performance of your Kafka cluster using Splunk.

We understand change is never easy, but trust us when we say, migrating from these legacy apps and adopting the new IT Essentials Work (ITE Work) app will be both worthwhile and beneficial.

Get your IT strategy on the right track by focusing on more integrated processes, breaking down team silos and aligning your team objectives to business goals. Check out some practical steps to consider, to maximize value for your organization and customers.

If your observability platform makes you sample, you may be drawing incorrect conclusions from it – resulting in large hidden costs and consequences. Learn more about how you can avoid missing out on critical insights at the most relevant time.

In this blog we will talk about some strategies for monitoring your models in ITSI for model drift. This is the idea that the predictive models will become less accurate over time as the rules that were generated originally no longer match the data they are applied to.