Operations | Monitoring | ITSM | DevOps | Cloud

If those von Trapp Family singers from The Sound of Music collectively woke up in a really, really bad mood and decided to write a song about their least favorite things, then it’s a safe bet that not being able to connect to a website would make the list (alongside airline passengers who tilt their seat back, and clam shell plastic packaging).

Grafana 8.5 is here! Download Grafana 8.5 We’ve worked on a variety of improvements that focus on Grafana’s usability, data visualization, and security. For a full list of new features and capabilities, check out our What’s New in Grafana 8.5 documentation. You can get started with Grafana in minutes with Grafana Cloud. We have free and paid Grafana Cloud plans to suit every use case — sign up for free now.

London, 21 April 2022. Canonical Ubuntu 22.04 LTS is now generally available, featuring significant leaps forward in cloud confidential computing, real-time kernel for industrial applications, and enterprise Active Directory, PCI-DSS, HIPAA, FIPS and FedRAMP compliance – raising the bar for open source from cloud to edge, IoT and workstations.

Miss O11y is delighted to welcome our newest band member: Martin Thwaites! Martin has been a member of the Honeycomb user community practically since its inception. He is a UK-based consultant who specializes in helping teams scale up and tackle challenging business problems, and a long-time contributor to the Azure and.NET communities. We think he looks ✨amazing✨ in a tiara.

When clients make HTTP POST requests to ping URLs, Healthchecks captures and stores request body data. You can use this feature to log a command’s output and have it available for inspection later: Same thing, using runitor instead of curl: You can view the request body data in the web UI: Healthchecks also captures and stores email messages, when pinging by email.

Another post inspired by our weekly internal enablement office hours [should we open this up to the public?] and a few conversations at DevOps Days Atlanta, talking about the experience with Kubernetes can reverberate some sighs. Though in our weekly enablement office hours, the blunt question was asked “well why is Kubernetes so difficult?”. Industry thought leaders would state that Kubernetes is a platform to build other platforms.

So you’ve just been tasked with creating a Terraform Provider (or maybe upgrading an existing one). As you do your research to prepare for the project, you slowly begin to realize, “well this looks like I’ll just be developing a Terraform specific wrapper for a client of my API.” It’s not particularly difficult, but it seems tedious. Is there a better way to build this? Maybe something that can be modular and automated? A way that’s actually stimulating to implement?

The latest version of the Splunk Operator builds upon the release we made last year with a whole host of new features and fixes. We like Kubernetes for Splunk since it allows us to automate away a lot of the Splunk Administrative toil needed to set up and run distributed environments. It also brings a resiliency and ease of scale to our heavy-lifting components like Search Heads and Indexer Clusters.

We’ve all suffered that common irritation: “A service person will be at your house sometime between 9 am and 4 pm.” In our personal lives, that can mean frustration and inconvenience. For businesses, that broad window of uncertainty can add up to real money in lost productivity. Both scenarios can chip away at customer confidence and satisfaction. In increasingly competitive marketplaces, those agitations can even be enough to push a customer to look elsewhere.

Approximately two years ago, the pandemic forced us to start working from the safety of our homes. Organizations purchased, distributed, and deployed services and products to support and maintain business as usual. While doing that, the standard due diligence process was shortened or, in some cases, completely ignored. The common issues were: Excess purchases: Organizations were unprepared to change to an entirely work-from-home model, which was unexpected.