Operations | Monitoring | ITSM | DevOps | Cloud

As assets are the main object of the IT Asset Management practice, in order to take full advantage of it, it's essential to go deeper and implement a complete IT Asset Lifecycle Management. This is a complex process that goes from the request of the asset to its disposal, so it's important to design and apply a plan to ensure that every single step and requirement is addressed.

To get visibility into highly distributed applications, organizations often use various tracing tools that are best suited to each individual service owner’s specifications. However, when a request travels between services that have been instrumented with different tools, the trace data may be formatted differently, resulting in broken traces.

Parsing logs with regex is a valuable technique for extracting essential information from large volumes of log data. By employing this method, one can effectively identify patterns, errors, and other key insights, ultimately streamlining log analysis and enhancing system performance.

In part 1 of this post, we talked about how Cribl is empowering security functions by giving our customers freedom of choice and control over their data. This post focuses on their experiences and the benefits they are getting from our suite of products. In a past life, I was in charge of security and operational logging at Transunion — around 2015, things started going crazy.

How often have you heard the phrase “trust is earned” in life? While well-meaning, I think this can actually lead to some strange behaviour at work, especially when you’re on a fast growing team. Startups experience a lot of chaos and unknowns your teams need to navigate, so it’s vital to know you can trust the people around you. As you grow, how you set expectations around trust as people join your team can impact your ability to hire, onboard, ship and ultimately, survive.

Users are complaining about slow load times and you’ve thrown logs, traces, and metrics — heck, the entire kitchen sink of performance monitoring — at your application, but you still can’t figure out the source of the bottleneck. Maybe you missed adding instrumentation to something in the critical path, or you’re simply testing in an environment vastly different from the ones your users are experiencing in production.

Elasticsearch is used for a wide variety of data types — one of these is metrics. With the introduction of Metricbeat many years ago and later our APM Agents, the metric use case has become more popular. Over the years, Elasticsearch has made many improvements on how to handle things like metrics aggregations and sparse documents. At the same time, TSVB visualizations were introduced to make visualizing metrics easier.

BugSplat's new auto-grouping feature is a powerful way to automatically group crashes in a way that's meaningful to your team. Normally, crashes are grouped by the top of the call stack. But sometimes this grouping isn't ideal. For example, if the top of your call stack is KERNELBASE!RaiseException (a Windows OS function) you'd probably prefer the crashes were grouped by a different stack frame. That's what BugSplat's auto-grouping feature does!