Data Visualisation Training in Maia

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level Grafana users who wish to build interactive, drill-down dashboards with dynamic thresholds and contextual updates.

By the end of this training, participants will be able to:

• Create dashboards that respond to user interactions, such as clicking a graph bar
• Implement visual drill-downs that update in-place (without new tabs)
• Configure pie charts and detailed panels based on selection filters
• Use dynamic thresholds that react to user input and real-time data

This instructor-led, live training in Maia (online or onsite) targets intermediate system administrators and monitoring professionals aiming to effectively utilize Grafana for setting up monitoring solutions, managing dashboards, and creating alerts.

Upon completion, participants will be capable of:

• Distinguishing between monitoring and observability.
• Installing and configuring the Grafana server.
• Configuring and connecting diverse data sources, including Prometheus, InfluxDB, and ElasticSearch.
• Creating, managing, and customizing dashboards and charts.
• Utilizing variables and queries to build dynamic dashboards.
• Establishing notifications and alerts via Grafana.
• Installing and managing plugins to enhance Grafana’s capabilities.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level DevOps engineers and SREs who wish to manage and scale Prometheus and Grafana for large environments effectively.

By the end of this training, participants will be able to:

• Architect Prometheus and Grafana for large-scale and distributed environments.
• Optimise Prometheus performance for high-traffic systems.
• Configure Grafana for large datasets and complex visualisations.
• Implement advanced troubleshooting and scalability strategies.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level developers and DevOps engineers who wish to instrument their applications to export and monitor custom metrics efficiently using Prometheus and Grafana.

Upon completing this training, participants will be able to:

• Grasp the significance of custom metrics for application monitoring.
• Instrument applications to export custom metrics for Prometheus.
• Build and configure Grafana dashboards to visualise custom metrics.
• Implement best practices for embedding monitoring within the development lifecycle.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

By the end of this training, participants will be able to:

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create dynamic dashboards to visualise cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level DevOps and SRE professionals who wish to enhance their alerting and automation skills with Grafana and Prometheus.

By the end of this training, participants will be able to:

• Create and manage advanced alerting rules in Prometheus.
• Integrate Prometheus Alertmanager with external tools using webhooks.
• Automate responses to alerts for faster issue resolution.
• Use Grafana to visualize and manage alerts effectively.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level cloud and DevOps engineers who wish to enhance cloud observability with Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the benefits of integrating Grafana and Prometheus with cloud platforms.
• Set up Prometheus for monitoring cloud-based resources.
• Configure Grafana for visualizing cloud service metrics.
• Leverage cloud-native tools and integrations for monitoring scalability.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level DevOps and SRE professionals aiming to create impactful dashboards and optimize their monitoring practices using Grafana and Prometheus.

Upon completion of this training, participants will be capable of:

• Grasping best practices for designing effective dashboards.
• Creating and configuring advanced Grafana dashboard components.
• Utilizing Grafana templating to produce dynamic and reusable dashboards.
• Implementing alerting mechanisms to boost operational awareness.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level system administrators and DevOps engineers who wish to develop core monitoring skills using Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the purpose and importance of monitoring in IT environments.
• Install and configure Grafana and Prometheus for basic monitoring tasks.
• Create simple dashboards and alerts to visualize system performance.
• Apply best practices for monitoring system availability and performance.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab for data visualization.
• Create various types of plots using Matplotlib.
• Utilize Seaborn for advanced visualization techniques.
• Customize plots for better presentation and clarity.
• Interpret and present data effectively using visual tools.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level IT professionals and DevOps practitioners who wish to learn the basics of Grafana and Prometheus.

By the end of this training, participants will be able to:

• Understand the purpose and key features of Grafana and Prometheus.
• Install and configure Grafana and Prometheus on a Linux environment.
• Set up basic data sources and dashboards in Grafana.
• Monitor system metrics and visualize data using Prometheus.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level administrators and developers seeking to deepen their expertise in Elasticsearch administration. The curriculum covers advanced techniques for dashboard development in Kibana alongside system maintenance.

Upon completion of this training, participants will be able to:

• Establish and configure Elasticsearch and Kibana environments tailored for advanced administration and dashboard creation.
• Create and administer Elasticsearch indices, mappings, and data models.
• Develop sophisticated queries and filters to extract valuable insights from Elasticsearch data.
• Design and construct interactive dashboards in Kibana employing a variety of visualization types and techniques.
• Apply best practices for the administration, optimization, and troubleshooting of Elasticsearch and Kibana.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level data analysts who wish to learn and utilize the advanced features and components of Grafana for data visualization and analysis.

By the end of this training, participants will be able to:

• Gain an in-depth understanding of advanced Grafana concepts and components.
• Leverage template variables and dynamic dashboards for enhanced data visualization.
• Use Grafana Query Language for complex queries.
• Learn best practices for scaling Grafana, optimizing performance, and ensuring high availability.

This instructor-led, live training in Maia (available online or onsite) is designed for data analysts who wish to build analytical applications using Python with Plotly and Dash.

Upon completing this training, participants will be able to:

• Configure a real-time interactive dashboard for streaming live-updating data.
• Create interactive dashboards using Python for data science solutions.
• Secure interactive dashboards through advanced authentication methods.

This instructor-led, live training in Maia is designed for system administrators looking to establish an ELK stack (Elasticsearch, Logstash, Kibana). Please note that a minimum of 3 delegates is required for this course to proceed.

The session begins by exploring the architecture and functionality of the ELK stack, before transitioning into live laboratory implementation and practical application. Practical exercises form a core component of the training, allowing participants to apply their learning and receive feedback on their progress.

This instructor-led, live training in Maia (onsite or remote) is aimed at data analysts who wish to use Grafana for monitoring and visualizing data.

Upon completing this training, participants will be able to:

• Set up the necessary development environment to begin creating visualizations in Grafana.
• Configure Grafana for high availability.
• Customize panels and dashboards with data.
• Configure a reverse proxy to ensure fast loading speeds.

In this instructor-led, live training in Maia (onsite or remotely), participants will learn how to use Microsoft Power BI to analyse and visualise data using a series of sample data sets.

By the end of this training, participants will be able to:

• Create visually compelling dashboards that provide valuable insights into data.
• Obtain and integrate data from multiple data sources.
• Build and share visualisations with team members.
• Adjust data with Power BI Desktop.

This instructor-led live training in Maia (available online or onsite) is tailored for developers who intend to use BusinessEvents and ActiveMatrix Service Bus to develop, deploy, and manage event-driven applications.

Upon completion of this training, participants will be able to:

• Configure the necessary development environment to begin development.
• Construct distributed, stateful, rule-based event-processing systems.
• Manage business events data and execute appropriate business rules.
• Decrease event response times in large-scale, data-driven applications.
• Develop applications for fraud detection, track-and-trace, real-time customer offer generation, and more.