Hello Everyone! As Feu had mentioned in their post earlier this week, we are restructuring how we work and how we communicate. From maintaining the project, to developing, to doing our events and working with you – the community. We see that we have been underperforming in a few aspects of our work: mainly the open communication with our open source community, and we want to change that.
Damn it March. 2020 was doing so well. The biggest news last month was the dramatic escalation of COVID-19. We won’t go into any detail, I’m sure you’re seeing enough of that. But due to the outbreak, the state of robotics this March has been, heartwarming. We have seen a surge in online learning platforms, companies, startups and communities rising to the challenge.
The stable release of LXD, the machine container hypervisor, is now available. LXD 4.0 is the third LTS release for LXD and will be supported for 5 years, until June 2025. This version comes with a significant amount of new features including adding virtual machines (VMs) support, the introduction of projects and improved networking, storage and security capabilities.
In part 1 we talked about the industrial applications and benefits that 5G and fast compute at the edge will bring to AI products. In part 2 we went deeper into how you can benefit from this new opportunity. In part 3 we focused on the key technical barriers that 5G and Edge compute remove for AI applications. In this part we will summarise the IoT use cases that can benefit from smart cell towers and how they will help businesses focus their efforts on their key differentiating advantage.
The fierce competition existing in the market today is a result of the numerous choices available for customers. All they need is a click to switch brands. It’s that simple. Traditionally, product and price were the two elements that gave businesses a competitive edge. This is no longer the case. Increasingly, customers are valuing experience more than product and price. A recent study shows that customer experience is surpassing product and price in brand differentiation.
We’re excited to announce that Zendesk is now available as a pre-built content source, along with a host of others, as part of the Workplace Search application. With more than 130,000 customers in 30 countries, Zendesk has become one of the de facto customer service platforms in the world. Each day, millions of users interact with support agents via the cloud-based tool regardless of the support channel they choose.
With Elasticsearch machine learning one can build regression and classification models for data analysis and inference. Accurate prediction models are often too complex to understand simply by looking at their definition. Using feature importance, introduced in Elastic Stack 7.6, we can now interpret and validate such models.
Cloud applications don’t just run flawlessly by way of magic. Many things can go wrong, and rest assured some will go wrong at one point. For small teams, this can be cumbersome and take a toll at the development speed. A monitoring system will detect these issues on behalf of the development team, so that they can act accordingly. At Dashbird, we think there’s much more to it, though, than just detecting and alerting issues, especially for small teams of developers.
Alex Hidalgo is a Site Reliability Engineer at Squarespace, and he’s currently writing a book called Implementing Service Level Objectives for O’Reilly Media. The first three chapters of the book are available now through O’Reilly’s early access program. I had a chance to read those chapters and ask Alex some questions about service level objectives and reliability. Thanks, Alex, for sharing your knowledge.
