Grafana is everywhere. Almost every DevOps team out there is currently in the process of creating a proof of concept enabling them to implement Grafana into their stack—if they have not already implemented it, that is. Teams are eager to employ Grafana’s highly effective visualizations and dashboards that monitor and track services’ functionality and performance.

Network monitoring is complex, which is why we’re developing a monitoring tool that will drastically increase DevOps productivity. This release is all about improving Netdata’s day-in, day-out performance. We’re working hard to make deploy enhancements that help engineers make faster, smarter decisions about their systems.

Joe Elliott, a backend engineer at Grafana Labs, took the stage in front of a packed house at KubeCon + CloudNativeCon in San Diego to demonstrate a few of the tricks he uses to debug applications live in Kubernetes. The goal is to increase your knowledge of applications in the production environment. Elliott’s techniques are framework agnostic and Linux-specific, and they are most useful in situations where you have a known type of problem and application.

In our previous blog post, we discussed the three core capabilities that constituted AIOps solutions: data ingestion and handling, machine learning analytics, and remediation. With an exponential increase in the amount of data generated by all these devices and siloed tool sets, the job of IT Ops can only get more challenging.

Netdata is made up from agile teams who are deeply committed to improving the usability of our product. We want to respond to our users and introduce in-demand features. Working directly with our community is the best way to make Netdata better. But we face the same the dilemma as all agile teams: How do we do this safely?

Developing for Google Cloud Run in a hybrid system managed by Anthos isn’t a solo race, it’s a relay between cloud and on-prem. To win, you’ll need an advanced Docker registry that can swiftly pass your containers for Cloud Run functions from one environment to the next. In our example hybrid architecture, you’ll see how JFrog Container Registry can be that reliable relay partner.

This guide will give you key strategies for deploying the same application on multiple AWS accounts. If you have multiple AWS accounts running, multi-account deployments make often make sense. If your developers have created an application within their dev environment (which has its own AWS Account), they’ll naturally want to move it over to production (with a separate AWS Account).

Azure Event Grid facilitates building event-driven serverless apps that can effectively solve a real-time business problems with a focus on the core logic rather than the infrastructure. Event Grid is designed for high availability, consistent performance, and dynamic scale. Event Grid can simplify event-based apps, as this serves as a single service to manage routing of all events from any source to any destination. Before we proceed further, it is important to understand what an ‘event’ is.

The power of community, and doing things together as that community, was the overarching theme in much of KubeCon/CloudnativeCon presentations. We were incredibly lucky to be able to attend, experience and learn from so many Cloud Native experts and developers over the past week.

With the growing complexity and velocity of security threats in dynamic, cloud-native environments, it’s more important than ever for security teams to have the same visibility into their infrastructure, network, and applications that developers and operations do. Conversely, as developers and operations become responsible for securing their services, they need their monitoring platform to help surface possible threats.