Operations | Monitoring | ITSM | DevOps | Cloud

At BugSplat, we've been supporting applications and video games with crash and error reporting for a long time. Over the years, we've collaborated with a wide range of teams, handling applications of all sizes. From our experience and numerous conversations with users, we've noticed an interesting trend: the distribution of crashes isn't uniform. If your application experiences 100 crashes in a given version, those crashes aren't caused by 100 different defects.

If you remember the last update, I originally planned to ship quite a few features in June. Life and family had to take priority for me, so they didn't get done. Thankfully, I'm building OnlineOrNot for the extremely long term, so there's no rush to ship as fast as possible. A fair few things did get shipped though.

As we continue adding to our growing catalog of more than 100 plugins for Grafana, we have been focused on developing data sources for Grafana that are more purpose-built for the respective technologies. One example has been the recent update to our core Prometheus data source. We have deprecated AWS authentication from the original Prometheus data source, and we created a new dedicated Amazon Managed Service for Prometheus plugin that will specifically cater to the AWS use case.

Exploratory data analysis is a key component of the machine learning pipeline that helps in understanding various aspects of a dataset. For example, you can learn about statistical properties, types of data, the presence of null values, the correlation among different variables, etc. But to get these details, you need to use different types of Python methods and write multiple lines of code.

From the NIST Cybersecurity Framework to GDPR and more, public sector agencies must comply with a myriad of IT regulatory requirements. These regulations ensure proper financial management and stewardship, security, governance, operational efficiency and effectiveness, incident management – and ultimately, assure public trust and accountability.

InfluxDB is all about your data: we bridge the gap between an empty database bucket and business value and provide experts to help you derive value from your data. InfluxDB expert support teams come with contracted InfluxDB 3.0 serverless products (Serverless, Cloud Dedicated) and our Clustered on-prem product. Though no customer is left to figure everything out on their own, your product selection will determine the level of custom support you receive.

When your IT systems are nearing capacity, you need to make decisions to expand provision, and many of those decisions will revolve around the choices you make to scale up vs scale out. For many the decision is intrinsically linked to their choice of platform and whether they are looking at cloud based, hybrid infrastructure or on-premises led strategies.

As a developer working with Linux systems, containers, or Kubernetes, it's crucial to understand process termination signals, particularly SIGKILL and SIGTERM. This comprehensive guide will explore these signals, their differences, and their implications in various environments. We'll delve into best practices, common scenarios, and advanced considerations to help you manage process termination effectively in your applications.