Just spent another late night staring at our Splunk ES dashboards during a Sev2, and I have to ask. Those glass tables look fantastic in a demo—all shimmering tiles and animated flows—but when you're trying to trace a user's suspicious activity across five different data sources, do they actually help?
I'm comparing this to my Grafana/Prometheus setup for infrastructure, where a single stat panel can drill down into 10 layers of detail. With the ES glass tables, I often find myself:
* Clicking a beautiful tile just to get a basic list view I could have had from the start.
* Missing clear hierarchies or relationships because the visual metaphor doesn't scale.
* Wasting precious seconds on animation when I need the *data*, not the presentation.
For example, trying to correlate a failed login spike with unusual outbound traffic meant jumping between three different glass table "stories" instead of having a correlated timeline view. Ended up pulling the raw searches to get what I needed.
Is this a configuration issue on our end? Are people using these effectively for real-time incident response, or are they primarily for high-level executive summaries? I'd love to hear how other SREs or SOC folks have integrated them (or replaced them) in their actual workflow.
- away
You're not wrong. They're a visual abstraction that adds a layer between you and the data, and that's the opposite of what you want during a Sev2. It's like having a beautifully rendered map when you really need the raw GPS coordinates and terrain data.
The core issue is that these interfaces prioritize storytelling over investigation. They're great for presenting a finalized narrative to a non-technical audience, but they fall apart when you're the one building the narrative from disparate clues. I've seen teams spend more time fighting the dashboard to correlate events than actually analyzing them.
My rule is this: if your primary console during an incident isn't as fast and utilitarian as a CLI, it's slowing you down. Build your dashboards for the people who *use* them, not the people who *see* them once a quarter.
Build once, deploy everywhere
Your comparison to Grafana's drill-down capability is spot on. That's a data architecture difference, not just a UI one. Grafana panels typically query a unified data model or a single correlated dataset, while Splunk ES glass tables are often configured as independent visualizations of separate SPL queries. They're presenting isolated results, not modeling relationships.
The configuration question is key. I've seen teams use them effectively by treating the glass table strictly as an entry point to a correlated investigation. They build each tile not as a static visualization, but as a launchpad for a pre-built correlation search that joins those five data sources you mentioned. The animation flow is then programmed to pass context between those searches.
But that requires deep knowledge of the underlying SPL and data models, turning the dashboard builder into an integration developer. If it's not set up that way from the start, you're left with what you described: disconnected stories. Most out-of-the-box deployments aren't built to that spec, which is why they default to being pretty summaries rather than investigative tools.
This really resonates. We're looking at Splunk ES for our help desk and I worry about that exact config problem. You mention needing deep SPL knowledge to make them truly useful - does that mean these dashboards can't be effective without a dedicated Splunk power user on the team? For us, the people using it daily would be tier 1 analysts.
The configuration is always the problem, but that's exactly the point. You've hit on the classic mismatch between what the tool can be made to do and what the team has time to make it do.
You mention pulling the raw searches to get what you needed. That's the signal. If your glass tables are just decorated gateways to a list view, they've failed. The animations and flows are supposed to *be* the correlation, passing context from one tile to the next so that clicking on a failed login tile automatically filters the outbound traffic tile. But building that requires you to pre-model every investigative path, which is a massive SPL and data modeling lift.
Most teams end up with what you have: a set of pretty launchpads for independent searches, because maintaining a truly dynamic, correlated glass dashboard is a full-time job. It's not for Tier 1 analysts unless you have a dedicated Splunk dev building and updating those context-passing workflows for them. Otherwise, you're just putting a slow, shiny shell on top of the search bar.
That CLI comparison hits hard. It's the same reason I build my deployment dashboards as glorified buttons to trigger API calls - the status page is for stakeholders, but the *action* needs to be immediate and functional.
If your main console during a crisis doesn't feel like a tool you're wielding, it's a picture you're looking at.