Operations | Monitoring | ITSM | DevOps | Cloud

Trust shouldn't start at zero

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.

Boosting Resilience with Chaos Engineering: Litmus 3.0 & Beyond | Civo TV

Prithvi Raj explores the world of chaos engineering and discusses its security, comparisons between open-source projects, and the latest Litmus 3.0 release. Discover how chaos engineering is not just about inducing failures, but also an essential aspect of building resilient systems across all stages of development.

Profiling from Sentry: Identify and Eliminate Performance Bottlenecks with Code-level Insight

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.

How to use Elasticsearch and Time Series Data Streams for observability metrics

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.

Prioritizing Defects with the New Auto Grouping Feature

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!

New in Grafana 9.5: Debug Grafana instances faster with support bundles

With the arrival of Grafana 9.5, we’re excited to introduce Grafana support bundles — a tool to help debug your Grafana instance faster and more easily. Support bundles provide a simple way to gather and share information about your Grafana instance, and this feature is available across all tiers in Grafana Cloud as well as in Grafana OSS and Grafana Enterprise.

Understanding Azure Function App Metrics

This article will focus on the metrics side of Azure Functions and features offered by the Azure Portal and then talk about the value of Serverless360. Then about the product that provides beyond the primary feature set in the Azure Portal, which will help you improve the day-to-day operations of your Azure solution. There are many different ways you can manage and operate Azure Functions and features like Application Insights which can also help you with Azure Functions.