Operations | Monitoring | ITSM | DevOps | Cloud

AutoCon3 in Prague offered important takeaways on network automation’s evolution, from hands-on learning and design principles to the impact of AI and the power of community. Read Justin Ryburn’s recap to learn about key insights from the event, showing why network automation is now a core competency you’ll want to understand.

Let’s face it: the modern enterprise network is a leviathan. No longer just a collection of routers and switches, today’s networks span multiple clouds, hundreds of SaaS applications, and countless IoT devices—supporting a workforce that could be anywhere.

Discover how Accenture and Elastic are helping businesses seize the opportunities offered by generative AI When it comes to generative AI, enterprises need to think big. Shaving a few seconds off the time needed to draft an email is helpful, but the journey to real value begins when you apply AI at the enterprise level. A new partnership between Accenture and Elastic combines technical expertise and strategic excellence, enabling businesses to build the data foundations for a successful AI future.

Splunk is the backbone of security analytics for many of the world’s most advanced enterprises. Its ability to unify, correlate, and analyze massive volumes of telemetry data has made it the platform of choice for SOC teams worldwide. But as security data grows exponentially in volume and complexity, many organizations face a different challenge: getting the right data into Splunk, in the right shape, without straining infrastructure resources or missing critical signals.

This guide aims to help your team shift testing left, simulate real user behavior, and catch critical issues early as part of CI/CD, prevent regressions from reaching production by automating tests as part of your CI/CD and aborting deployments that contain issues. Synthetic monitoring is a great way to check important flows in production and make sure everything is working the way it’s supposed to.

In Part 1, we explored how aligning network visibility with IT service context empowers faster, smarter incident response. But what does this actually look like? Here in Part 2, we’ll go deeper into the challenges of traditional monitoring approaches, and how teams should look to move from fragmented alerts to unified insights – because when ITOps and NetOps can both see the “what” & “why” of the problem, actions become instinct.

Trends in tech come and go, but certain underlying primitives stick around forever. In software, two such primitives are virtual machines and containers. Virtualization paved the way for the cloud to become massive. Data centers would likely never have been commercially viable without it. While still relatively new, containerization has already made a serious mark on the software engineering world.

What if you were to tell Kubernetes Monitoring what you wanted, and the system configured collectors based on your choices? We wondered that as well—wondered enough to create Alloy Operator and its Helm chart for version 3.0 of the Kubernetes Monitoring Helm chart. We’re excited to share that the new Kubernetes Monitoring Helm chart is now available, and it introduces a dynamic way of setting up your telemetry data collection with Alloy Operator.

Sometimes your API call takes a few seconds longer than expected. Or users start reporting slow page loads. One of the most common reasons? Network latency.

If your users are spread across the globe but your servers are sitting in Virginia, you’ll probably hear complaints about slow load times, especially from places like Australia. CDNs fix this by caching static assets closer to where your users are. Azure CDN does exactly that, and it fits well if you're already using Azure services. You can hook it up to Blob Storage, App Services, or your origin. This guide covers how to set it up, what to expect, and how to know it’s working.