Jira is an industry favorite when it comes to managing software projects, yet its native dashboards can sometimes leave teams wanting more insight. The default views give a general update, but often lack the connection to the day-to-day activity happening in other parts of your workflow. As organizations use a wide mix of modern tools – from code repositories and cloud services to spreadsheets and reporting apps, it’s easy for critical details to get scattered or overlooked.

Note: A version of this post originally appeared on the OpenTelemetry blog. Victoria Nduka is user experience designer and open source contributor making her way into the cloud native space. She writes about design, accessibility, and open source with the same curiosity she brings to her work. On May 29, I wrapped up my mentorship with Prometheus through the Linux Foundation mentorship program.

Imagine you’re a frontend engineer monitoring the user experience for an e-commerce app. You notice your checkout flow has a 15% abandonment rate. Your API responses are inconsistent. Your users are frustrated, and you’re drowning in data and complex queries trying to figure out why. Sound familiar? You can use real user monitoring (RUM) to determine what has happened, looking at page load times, error counts, user sessions, etc.

In the early stages of building a system, a few well-placed dashboards and monitors can provide sufficient visibility into service health and performance. However, as infrastructure scales and teams grow, so does the complexity of the monitoring landscape. In organizations where individual teams manage their own services but rely on a central platform or observability team for tooling and guidance, this complexity can quickly multiply.

Wilfried Roset is an engineering manager who leads an SRE team and he is a Grafana Champion. Wilfried currently works at OVHcloud where he focuses on prioritizing sustainability, resilience, and industrialization to guarantee customers satisfaction. Whether it’s for efficient resource allocation, flexibility, high availability, or scalability, it makes a lot of sense to run Grafana Mimir on Kubernetes—but it’s not the only way to deploy Mimir.

As part of our big tent philosophy at Grafana Labs, we think you should be able to dig into your data and find meaningful insights — wherever that data happens to live. For many of our users, that data lives in Salesforce, the cloud-based customer relationship management (CRM) platform. In this post, we’ll take a closer look at how you can use the Salesforce Enterprise data source for Grafana to quickly and easily visualize your Salesforce data using Grafana dashboards.