At AppSignal, our pricing revolves around the number of requests we process for a customer and the number of buckets of logging data we store. After their free trial, customers are offered the most fitting plan for them based on their usage in the previous 30 days. About nine years ago, we noticed that many customers were slowly growing their number of requests, but we kept charging them for the plan they started on.
This week, NVIDIA unveiled what they are calling “the world’s most powerful GPU for supercharging AI and HPC workloads,” the H200 Tensor Core GPU. There is much hype around the H200 as it is the first GPU with HBM3e. The larger and faster memory will further enable generative AI, large language models, and advance scientific computing for HPC workloads. Read the NVIDIA press release.
The cognitive bias known as the streetlight effect describes our desire as humans to look for clues where it’s easiest to search, regardless of whether that’s where the answers are. For decades in the software industry, we’ve focused on testing our applications under the reassuring streetlight of GitOps. It made sense in theory: wait for changes to the codebase made by engineers, then trigger a re-test of your code. If your tests pass, you’re good to go.
You’ve done your research and decided to use the DevOps approach for your software development process and IT operations. However, before you start tossing around terms like “continuous integration” and “containerization,” there’s an important starting point on your DevOps journey — creating a DevOps implementation roadmap.
It’s not uncommon to find with remote monitoring and management solutions that the functionality they offer around Apple device management lies a very distant second to that offered for Windows devices. N-central has long been a leading RMM solution, and it too has had its deficiencies when it comes to Apple device management.
Many ITOps organizations we speak with want a state of self-healing systems capable of identifying and resolving issues without human intervention. Thanks to the progress in AI and ML, AIOps has made significant advancements in areas that automate many of the steps involved with identifying and triaging incidents. We ask ITOps leaders why they aren’t taking the next step with auto-remediating incident response workflows.