Operations | Monitoring | ITSM | DevOps | Cloud

OpenTelemetry offers powerful data collection, but maximizing its efficiency requires careful configuration. This article explores advanced techniques for sampling filtering, and data enrichment.

Asset attribution is an operational necessity for robust digital protection, but hasn't always been easy to achieve. Especially when software state and ownership is unknown, or inconsistent. This blog delves into the historical complexities and challenges of asset attribution for security and engineering teams and explores how Internal Developer Portals like Cortex can help.

Here are some of the most popular DevOps questions and their answers.

SOC 2 compliance is crucial for any company handling sensitive customer data, but the process can be a headache. From managing your infrastructure to rigorous audits and ongoing monitoring, staying compliant demands a lot of time and effort. Thankfully, SOC 2 automation tools can make this process much smoother and faster. In this article, I’ll walk you through five top SOC 2 automation tools that can help you get and stay compliant with less stress.

Managing costs while scaling operations is a challenging balancing act. One significant cost center is cloud infrastructure and its maintenance. This article aims to provide CTOs, VPs, and Head of Engineering with insights on optimizing these expenses. It highlights the benefits of leveraging DevOps Automation Platforms like Qovery to cut up to 5x their Cloud infrastructure costs.

In a world where businesses require uninterrupted network operations and people rely on applications for their day-to-day activities, understanding bandwidth utilization is critical. Rather than playing whack-a-mole with your bandwidth problems, you can monitor your network’s bandwidth usage and make informed decisions based on clear data. Bandwidth utilization metrics tell you how much data an interface, switch, or router can handle and how much data is currently passing through them.

LlamaIndex is a framework for building context-augmented large language model (LLM) applications. It enables you to augment the model with domain-specific data to customize it and improve its responses to your use case. You can use this framework to build a question-answering chat bot, a document understanding and extraction application, or an autonomous agent. The framework provides tools to ingest data, process it, and implement query workflows that combine data access with LLM prompts.

With the release of On-call, our system’s reliability had to be solid from the outset. Our customers have high expectations of a paging product—and internally, we would not be comfortable with releasing something that we weren’t sure would perform under pressure. While our earlier product, Response, was the core of a customer’s incident response process after an incident was detected, we’re now the first notification an engineer gets when something’s wrong.