Operations | Monitoring | ITSM | DevOps | Cloud

We have a term we like to use when we meet CFOs who have just gotten their biggest AWS bill ever: bill shock. Bill shock is when finance suddenly rings the alarm that the bill is “too high” and gets everyone scrambling to explain what they’re spending money on. It often happens when the bill reaches a new milestone (the first million, ten million, or hundred million) or growth trajectory (it doubled in a quarter!?). The problem with bill shock is that it can be highly disruptive.

This post is the third in a series of deeper dive articles discussing DORA metrics. In previous articles, we looked at: The third metric we’ll examine, Change Failure Rate, is a lagging indicator that helps teams and organizations understand the quality of software that has been shipped, providing guidance on what the team can do to improve in the future.

The MQTT Consumer Plugin is one of our most widely used input plugins for Telegraf. If you need a little bit of background, then I highly recommend checking out the following: I plan to release an MQTT best practices blog soon, but we thought this plugin partnership was too good not to talk about now.

A large U.S.-based insurance provider was experiencing rising database software licensing costs. In order to reduce the software licensing costs, the organization needed to complete a comprehensive infrastructure analysis of over 200 physical servers. 75 percent of these physical servers supported one software application, their database solution. Additionally, the software routinely only utilized between two and four cores, despite having 24 cores on each server.

PostgreSQL is an open-source relational database management system that’s been utilized in continuous development and production for 30 years now. Nearly all the big tech companies use PostgreSQL, as it is one of the most reliable, battle-tested relational database systems today. PostgreSQL is a critical point in your infrastructure, as it stores all of your data. This makes visibility mandatory, which in turn means you have to understand how logging works in PostgreSQL.

Aiven for Apache Kafka® Learning Apache Kafka doesn’t have to be difficult. Read on to get a friendly explanation of the Apache Kafka fundamentals.

The following guest post addresses how to improve your services’s performance with Sentry and other application profilers for Python. Check out this post to learn more about application profiling and Sentry’s upcoming mobile application profiling offering. We’re making intentional investments in performance monitoring to make sure we give you all the context to help you solve what’s urgent faster.=

Building Packs is good. Sharing Packs is better! The Cribl Pack Dispensary is the go-to place to find, install and share Cribl Packs. What are Packs? A Cribl Pack is a collection of pre-built routes, pipelines, data samples, and knowledge objects. Packs enable sharing of best-practice configurations that route, shape, reduce and enrich the log source, Palo Alto Networks logs for example. And it’s the quickest, easiest way to get started with Stream and Edge supports Packs too.

Nate Lee here, and I’m one of the founders of Speedscale. The founding team’s worked at several observability and testing companies like New Relic, Observe Inc, and iTKO over the last decade. Speedscale traffic replay was borne out of a frustration from reacting to problems (even if they were minor) that could have been prevented with better testing.

Regex—short for regular expressions—is a way to describe a search pattern. They can be used to find a text pattern or string (character sequence) within a larger body of text, such as a sentence or paragraph, but even entire documents and databases. They can be used to quickly find specific text in a text document like a configuration file for a network device. Need to know what IP addresses a device has? What VLANs are on a switch? What devices are using a deprecated DNS server?