Operations | Monitoring | ITSM | DevOps | Cloud

When you’re investing in automation solutions, ultimately, tangible results need to follow quickly. Getting a return on investment (ROI) out of an automation project after two years is something that would have been OK in the not-so-distant past but is no longer acceptable nowadays. With the current speed of change, where new technologies come and go and existing ones evolve at lightning speed, IT teams require much faster time to value on automation investments.

There are a few key differences between distributed tracing and OpenTelemetry. One is that OpenTelemetry offers a more unified approach to instrumentation, while distributed tracing takes a more granular approach. This means that OpenTelemetry can be less time-consuming to set up, but it doesn’t necessarily offer as much visibility into your system as distributed tracing does.

Most classical, batch-oriented machine learning systems follow the paradigm of “fit and apply”. In an earlier blog post, I discussed a few patterns on how to better organize data pipelines and machine learning workflows in Splunk. In this blog, we’ll review how you can organize your machine learning model in a new way: online learning.

Companies are investing heavily in the cloud for the operational and financial benefits. But without a robust cloud cost management strategy in place, the complexity of cloud services and billing can to overspending and unnecessary cloud waste. Being able to accurately predict future cloud spend is one way to more optimize cloud spend and inform budgets.

In the early years of the internet, it was common to simply use a spreadsheet to manually assign and track IP addresses. We’d be given a generous pool of IP addresses that were not so widely distributed, and most network devices were desktops and not mobile. But this soon got out of hand as networks grew and mobile devices became the norm.

In today’s world, a significant fraction of a software business’s reputation depends on its web application and its speed. It all comes down to how fast your server responds to client requests (assuming your application is reliable and reasonably user-friendly). Therefore, you could argue that the server endpoint is the centerpoint of all the server-side action — the operations here primarily determine the performance of your application.

One of the key advantages of cloud services versus on premise deployments is the wide range of purchasing options and pricing models. While it’s an attractive advantage, it can be complicated for organizations to determine the best blend of service pricing models. The ability to define the organization’s blend of purchasing strategies and display the target versus actual performance is critical for optimizing cloud cost management efforts.

Microsoft Teams is the world-leading collaboration and productivity tool for today’s hybrid workforce, but your users’ experience with it is only as good as the network and IT environment it operates in. There is a critical visibility gap when it comes to delivering a stellar Microsoft Teams user experience to your users. Organizations lack an end-to-end picture of what problems are happening, what is causing the problems and who is affected.

Website uptime monitoring is crucial for any business that depends on its website. But for companies whose whole service is online, it is essential. If your site isn't reliably serving users when they need it, your competitors are just a Google search away. So you can't just check your site is running now and then - you need a tool to check it as frequently as possible.

We are thrilled to announce that Grafana Incident is now generally available to all Grafana Cloud users, including our generous free tier. (You can sign up for a free Grafana Cloud account now.)