Operations | Monitoring | ITSM | DevOps | Cloud

You did it! Sure, it might be four weeks overdue and late on a Friday, but you’ve finally finished deploying a long-awaited update to the web app. However, your celebrations are cut short as your phone vibrates off the table. Picking it up, you’re confronted with a developer’s worst nightmare. You’re getting flooded with messages that the login is no longer working. Was it your deployment? This is bad. Nobody can use the site if they can’t log in.

Learn how to identify & resolve edge cases when testing complex systems and the best ways to prepare a test suite to validate performance.

Does anyone really enjoy being on-call? That looming dread over what could go wrong? The alarms in the middle of the night when everything does in fact go wrong? Of course not! But that doesn’t mean on-call shifts need to be a giant bundle of anxiety and exhaustion. This is something near and dear to our hearts at Grafana Labs, since the majority of our engineers participate in on-call shifts.

The Linux kernel has recently introduced the Rust programming language as an alternative to C for creating kernel modules. Rust is a strongly, statically typed programming language with a focus on memory safety features which produces extremely compact executable code. These properties, paired with its good tooling, make Rust a natural choice for creating many types of kernel modules, including device drivers, network protocols and filesystems.

We’ve all been there: at that frustrating moment when you have a problem or an urgent need and the customer support line is busy. Endless searching for answers turns up nothing that matches your predicament. That’s the friction ServiceNow teams are diving into headfirst to provide each of our customers satisfactory answers with promptness that matches the urgency they feel. Generative AI is helping the teams improve customer support at a rapid pace.

Data has become the lifeblood of businesses, empowering organizations to make more informed decisions, drive innovation, and gain a competitive edge. McKinsey touts the benefits of adopting data-supported capabilities, referring to the various ways data is utilized to enable and enhance the functioning of an organization.

Operational efficiency is as critical within the IT and engineering teams as any other part of the business. Automating repetitive tasks and reducing escalations within and to these teams is of immense value. While automation saves time and boosts productivity, the complexity of developing automation can be a limiting factor and bottleneck. Generative AI is a paradigm shift here, in that it brings consumer-style simplicity to assisting in the development of enterprise-grade automation.

Vertex AI is Google’s platform offering AI and machine learning computing as a service—enabling users to train and deploy machine learning (ML) models and AI applications in the cloud. In June 2023, Google added generative AI support to Vertex AI, so users can test, tune, and deploy Google’s large language models (LLMs) for use in their applications.

The Information Technology Infrastructure Library (ITIL) Service Asset and Configuration Management process, described in its Service Transition guide, requires IT organizations to establish and maintain a configuration management database (CMDB) to keep track of configuration items (CIs) and the relationships between them. An up-to-date and functioning CMDB is one of the most important indicators of ITIL implementation success.