The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Since almost the beginning of programming, the idea of write-once and deploy everywhere, on all platforms, has been an unreachable ideal to minimize development costs for cross-platform applications, drive UI consistency and reduce security service area. In programming, the cross-platform languages Java and Python have topped developer utilization charts for decades.
You’ve pored over the MongoDB documentation, crafted highly polished and well-tuned queries, and confidently deployed your new code to production. Everything ran great at first, but once CPU or RAM usage hit a certain point, your queries suddenly slowed to a crawl. What happened, and how can you prepare for situations like this in the future? This is an unfortunate but common scenario with databases like MongoDB.
Machine Learning (and deep learning) applications are quickly gaining in popularity, but keeping the process agile by continuously improving it is getting more and more complex. There are many reasons for this, but primarily, behaviors are complex and difficult to anticipate, making them resistant to proper testing, harder to explain, and thus not easy to improve.
Alien wavelengths are commonplace today. Here a transponder pair from one optical system vendor connects to, and transmits over, the optical line system (OLS) – constituting fixed/reconfigurable multiplexer and amplification elements primarily – from another vendor. (While it can be technically feasible to pair transponders from different vendors, typically this is not done for commercial and operational reasons.)
I’m a bit of a data nerd. And like many fortunate people, I’m still working from and generally staying home and have a lot spare time on my hands. So what does that combination result in? Graphs!
If you were thinking that nothing will change in your VMware data centre in the following years, think again. Data centre storage is experiencing a paradigm shift. Software-defined storage solutions, such as Ceph, bring flexibility and reduce operational costs. As a result, Ceph storage on VMware has the potential to revolutionise VMware clusters where SAN (Storage Area Network) was the incumbent for many years.
Amazon Elastic Block Store (EBS) provides block storage for applications that are running in the cloud. However, not every company is getting the most out of the EBS volumes they are using. Some companies can pay too much for EBS volumes without utilizing the allocated storage and IOPS. Other organizations may pay high prices because they are using the wrong disk type for their needs. This article explains five techniques you can use to optimize the performance of your EBS workloads.
