Operations | Monitoring | ITSM | DevOps | Cloud

One of the inherent challenges you'll face when working with Kubernetes is that a typical cluster includes many resources that produce telemetry data. Because producing and moving telemetry data consumes resources, you can end up in situations where different workloads are competing for the resources necessary to manage telemetry data.

Whether you’re a business owner, a tech enthusiast, or simply a user who relies on cloud services for daily tasks, the cloud outage tracker can be a useful tool. It informs you of downtime, degraded performance, and maintenance of services that modern businesses rely on. Here’s the list of cloud outage tracker tools that can help you prepare for and mitigate the effects of inevitable disruptions in the cloud.

Query performance is critical in any database. Data partitioning is a mechanism that helps prune unnecessary data, allowing queries to run faster. However, there are always trade-offs between large and small numbers of partitions. For instance, fine-grained partitioning on high cardinality columns can reduce performance. This post describes different partitioning schemes supported by InfluxDB 3.0 and explains their trade-offs.

Nginx, a widely used web server and reverse proxy, maintains two crucial logs that provide valuable insights into its performance and user interactions: the access log and the error log. These logs play a pivotal role in monitoring and troubleshooting web server activities. The access log records every request made to the server, capturing details such as the requested URL, client's IP address, response status code, and user agent.

Good alerting hygiene consists of a few components: chasing down alert conditions, reflecting on incidents, and thinking of what makes a signal good or bad. The hope is that we can get our alerts to the stage where they will page us when they should, and they won’t when they shouldn’t. However, the reality of alerting in a socio-technical system must cater not only to the mess around the signal, but also to the longer term interpretation of alerts by people and automation acting on them.

I’m pretty sure that you’ve had a situation where you deployed a major UX change on your web app and missed the most obvious issues, like a misaligned button or distorted images. Unintended changes on your site can cause not only a sharp decline in user satisfaction but also a large fall in sales and customer retention. By identifying and resolving these discrepancies before the update went live, you could have prevented these outcomes.

We’ve all been guilty of it. Creating rules and filters to hide those alerts that, for the most part, are just noise. Only then to have notifications about a legitimate issue also get swept up by those same filters. There’s only so many times we can break concentration and disrupt productivity before getting fed up with false positives and ignoring everything completely.

Maintaining compliance requires aligning people, processes, policy, and technology.