Operations | Monitoring | ITSM | DevOps | Cloud

Reducing development and testing time is one of the top priorities for software development teams. A reduced development time allows teams to move ahead with projects faster and focus more on testing and refining them, which is especially important for end-user-based projects. This is because UI-UX-heavy projects often need to be put through a rigorous review and refinement process before they can finally be launched for customer use.

Docker logs play a critical role in the management and maintenance of containerized applications. They provide valuable information about the performance and behavior of containers, allowing developers and administrators to troubleshoot issues, monitor resource usage, and optimize application performance. By capturing and analyzing log data, organizations can improve the reliability, security, and efficiency of their containerized environments.

Testing is a vital aspect of security. Unfortunately, there are vulnerabilities that bypass the testing stage and introduce flaws in the production environment. Kubernetes vulnerabilities make more impact when exploited on running applications and production environments. These vulnerabilities can allow hackers to exploit the host machine if the container has escalated privileges.

When it comes to your SQL Server, performance degradation is a costly, time-consuming issue. There may be any number of reasons why your SQL Server performance may be diminishing, but one of the biggest culprits tends to be memory usage.

Meet your compliance goals using Aiven for OpenSearch®, S3 storage and Aiven for Apache Kafka®.

If you’re an Icinga user, you already know the importance of having a streamlined and efficient configuration management process. With the release of Icinga Director Branches v1.3, this process just got even better! In this latest version, Icinga Director introduces several enhancements to its branching system, making it even easier to manage and deploy your Icinga 2 configurations.

Traffic telemetry is the data collected from network devices and used for analysis. With traffic telemetry, engineers can gain real-time visibility into traffic patterns, correlate events, and make predictions of future traffic patterns. As a critical input to a network observability platform, this data can help monitor and optimize network performance, troubleshoot issues, and detect security threats. However, traffic telemetry can be difficult to understand.

You don’t often see real change, but when you do see it you know it. Artificial Intelligence/Machine Learning toolsets like ChatGPT are finally starting to offer broad capabilities that will benefit a mass audience. These tools are moving out of the domain of data scientists and math nerds and into mass markets with a little bit for everyone. The potential reach is awesome and a little scary.

Picture this: A critical business service is offline. Instead of panicking, you’re calm yet concerned. You retrieve data about the service in question and instantly see exactly which infrastructure components the service depends on, as well as their statuses. You quickly engage IT operators to address the issue and notify the line-of-business lead with an estimated time for its resolution. This scenario doesn’t have to be an impossible dream.

IT industry veterans have seen significant changes in the way applications are not only developed but also used. This evolution has been driven by several factors, including the ever-growing need for mobility, vast ecosystems, and the increasing demand for faster and more efficient ways to get work done. Let's take a closer look at how apps have evolved over time.