Operations | Monitoring | ITSM | DevOps | Cloud

June 2018

SCIPY STACK VS. INFLUXDB AND GRAFANA

Scientific python programmers adore Pandas due to its many functionalities. In particular, for data manipulation and analysis it offers handy data structures and operations for numerical tables and time series. Combined with the rest of the SciPy stack and scikit-learn (e.g. for Machine Learning Analysis), multiple goals can be achieved. When it comes to on-line data analysis, interaction, or simple data navigation by multiple users, the SciPy stack can be stressed to its limits.

GRAFANA AND Flux

The new Flux (formerly IFQL) super-charges queries both for analytics and data science. David gave a quick overview of the language features as well as the moving parts for a working deployment. Grafana is an open source dashboard solution that shares Flux’s passion for analytics and data science. For that reason, they are very excited to showcase the new Flux support within Grafana, and a couple of common analytics use cases to get the most out of your data.

Paul Dix | INFLUXDATA PLATFORM FUTURE AND VISION

Paul will outline his vision around the platform and give the latest updates on Flux (a new Data Scripting language), the decoupling of query and storage, the impact of hybrid cloud environments on architecture, cardinality, and discuss the technical directions of the platform. This talk will walk through the vision and architecture with demonstrations of working prototypes of the projects.

Assessing Write Performance of InfluxDB Clusters using Amazon Web Services

In this technical paper, we'll explore the aspects of scaling clusters of the InfluxEnterprise product, primarily through the lens of write performance of InfluxDB Clusters. This data should prove valuable to developers and architects evaluating the suitability of InfluxEnterprise for their use case, in addition to helping establish some rough guidelines for what those users should expect in terms of write performance in a real-world environment.