Welcome to our 2021 wrap-up, where I will take you through some major milestones at gridscale. I’ll also quickly give some insights into how each item could further develop.
Starting right with one that aligns with our Hybrid Core strategy. Last year we expanded our Hybrid Core footprint to three new public locations:
- hosttech – Austria, Vienna (at/wie1)
- hosttech – Switzerland, Gias (ch/app1)
- gridscale – Netherlands, Amsterdam (nl/ams1)
With the new locations of Gais and Amsterdam, we now have a total of three locations for our Object Storage.
As a partner you have to opt-in to use these sites, so if you haven’t done so already just navigate to the location explorer, click on the location details and enable it for your accounts.
Each location is run by a hybrid core partner, so the location’s features, partner agreements etc are all shown in the location explorer so you can make an informed decision as to which locations you would like to use.
The new Help Centre is the one-stop shop for all your queries linked to the platform. The Centre includes support, status page, documentation, tutorials, FAQs and other helpful information.There is also a search function by topic or product. Another option is to request support from within the Help Center.
The Help Center will also be expanded in the future. Partners will be able to configure support addresses to be displayed to their accounts. Later, partners will also be able to add their own links to documentation, FAQ or tutorials.
Many features that require emails were previously disabled by default for new partners, until they configured their own SMTP server. The reason for this was that whitelabel partners would obviously not want their customers to receive emails from gridscale.
Last year we released custom SMTP. The configuration of an SMTP server enables Magic Links for passwordless login for partners and their accounts. Thanks to the whitelabeled emails, we can now also activate self-signup for your partner space upon request. Thus, accounts can be created by oneself, with its own validation process to prevent fraud.
We greatly enhanced the power of our private networks (including virtual switches) by allowing you to configure DHCP settings per network. This feature automates the allocation of IP addresses within a network, allowing you to manage large private networks with ease.
Further improvements coming to networking this year will be native compatibility between our PaaS, Private networks and GSK (managed kubernetes).
We added the ability for customers to bring their own SSL certificates. This covers many use cases including wildcard certificates as well as multiple domain support. This way, if you use our load balancer with multiple domains, the costs will be significantly reduced.
Two new managed services found their way onto our portfolio: gridFs which is a highly scalable and highly performant file server running NFS 4, and our managed MS SQL Server with complete Object Storage backup functionality.
With the aforementioned private network native compatibility, gridFs will be fully compatible as RWM volumes for GSK clusters.
GSK (gridscale Kubernetes)
Along with keeping our GSK up-to-date we’ve also made sure to keep up full product support. For example, all new Load Balancer features like custom SSL certificates were timely integrated into the product. We also introduced vertical scaling and we’re looking forward to releasing the full native integration between our Platform Services and GSK.
Along with the aforementioned expansion of locations, we also overhauled the Object Storage interface. We support many standard S3 features (like static site hosting) but this wasn’t apparent via the Cloud Panel. We have now updated this and added important functions to the Cloud Panel. We will also introduce user-based access control for buckets this year.
We’ve partnered up with GTS – Data Processing to be able to offer gridscale customers GPU compute over the network. The offering features NVIDIA Tensor GPUs to compute demanding tasks. Ideal for deep learning and machine learning workloads using tools such as TensorFlow, Pytorch, RAPIDS or Conda.
If interested, feel free to contact us. We provide you with our GPU Compute on request.
Last year we released our product documentation. Here you will find a comprehensive overview of the most important functions and possibilities of our products, regularly updated and always up to date. These are often day 2 operations, like maintenance and housekeeping – see for example tips on upgrading your kubernetes cluster.