SLATE blog

The SLATE binaries and API server requires a fairly complex environment in order to build successfully. In order to provide a standardized build environment that could be reproduced and used in various contexts, the SLATE project generated a containerized environment for development and deploying binaries to production. We’ll describe the environment and how we use it in this blog post.

The SLATE API & Client version 1.0.40 includes various fixes and enhancements.

Note: This blog post was first published on Oct 20,2020 and last updated on Apr 04, 2023.

Our previous post JupyterLab and HTCondor with SLATE described deployment of an HTCondor pool onto a SLATE-registered Kubernetes cluster with job submission provided by a JupyterLab application. But what if you want just a JupyterLab capable of submitting jobs to the Open Science Grid?

Note: This blog post was first published on Jun 11,2020 and last updated on Apr 04, 2023.

JupyterLab is a great tool for data analysis, visualization, machine learning and much more. It allows users to run code interactively via its web notebook interface and thus iterate changes quickly. Often users need to scale up their work and thus require submission to a backend cluster from the notebook. We show how this can be done with HTCondor using SLATE.

Varnish is a web application accelerator also known as a caching HTTP reverse proxy. It’s an alternative to squid, the web caching service that the ATLAS community is familiar with. Slate recently released two Varnish charts, v4a and v4cvmfs. The former creates a Varnish instance that is configured to proxy ATLAS Frontier requests while the latter creates a Varnish instance that is configured to proxy CVMFS requests (CMS, ATLAS, and any CVMFS repository available on Stratum One servers).