From chaos to clarity: How Gradient Insights saves your budget (and sanity)

In the world of data engineering, managing Databricks jobs can feel like herding cats while juggling flaming torches. You’re responsible for hundreds or even thousands of jobs, each with its own quirks and performance characteristics. And let’s be honest, most of us don’t have the time, expertise, or frankly, the patience to sift through mountains of raw metrics to figure out what’s really going on.

That’s why we’re excited to introduce Gradient Insights – a feature designed to transform complex job metrics into actionable intelligence that even your VP can understand.

The data engineering reality check

Before diving into what Insights can do for you, let’s acknowledge some painful truths about managing Databricks jobs:

• Cluster management is fiendishly complex. Even experienced data engineers can struggle to interpret performance metrics and make optimal configuration decisions.
• Context gets lost. The engineer who wrote that critical ETL job three years ago? They’re now working at a startup in Portugal, and they took all their tribal knowledge with them.
• Scale creates blindness. When you’re responsible for hundreds of jobs, you’re lucky if you know what’s happening with a handful of them, and usually only when something breaks catastrophically.
• Raw metrics aren’t user-friendly. Gradient has always provided comprehensive metrics, but translating those numbers into actions requires expertise that many teams simply don’t have.
• Problems escalate silently. By the time you notice something’s wrong, it’s often already impacting your business, your budget, or both.

Introducing Gradient Insights: your job intelligence partner

Gradient Insights analyzes your job metrics and surfaces what matters, giving you clear visibility into potential issues before they become full-blown problems. Some insights also share opportunities for further cost savings.

Here’s what Insights detects:

High failure rate

What this means: Over 25% of job runs have failed.

Impact: Normally you may be notified or alerted when a job fails. However, this insight goes beyond that and looks at how this job has performed historically so you can be proactive instead of reactive. Failed runs hit you twice; they waste time and money. Your team spends valuable hours troubleshooting while you’re still paying for the compute resources that produced zero value.

Recommended action: Investigate the job and fix underlying issues to improve the success rate. Gradient highlights these jobs so you can prioritize them for immediate attention.

High variability

Gradient Insights identifies three types of variability that can signal deeper issues:

1. Variable costs

What this means: Job costs are spread out by more than 25% from their average.

Impact: Unpredictable costs wreak havoc on budgeting and forecasting. Your finance team will thank you for addressing these.

Recommended action: Verify if this variability is expected or if it indicates an underlying issue with your job configuration or data processing.

2. Variable data sizes

What this means: The data size processed fluctuates by more than 25% from the average.

Impact: Unexpected changes to data size can indicate upstream problems. One Gradient customer discovered their job had jumped from processing 500GB to over 1TB, which led them to uncover a critical data pipeline error.

Recommended action: Investigate the cause of data size variability and determine if it aligns with business expectations.

3. Variable runtimes

What this means: Job completion times are inconsistent and are spread out by more than 25% from the average.

Impact: SLA risk increases with runtime variability. When critical downstream processes depend on timely data delivery, variable runtimes can cascade into bigger problems.

Recommended action: Examine the job’s configuration and execution patterns to stabilize performance.

Dormant jobs

What this means: No job runs in over two weeks.

Impact: While not always urgent, dormant jobs can indicate unintentional disabling or represent organizational clutter. Even worse, upstream processes might still be running, producing data that nobody uses.

Recommended action: Confirm whether the dormancy is intentional. If so, consider removing the job and auditing associated upstream and downstream tasks.

Unused jobs

What this means: Almost no change to cost and runtime for this job.

Impact: Jobs with suspiciously consistent metrics are prime candidates for review as they often represent automated processes that everyone assumed were necessary but no one actively monitors. Nearly all jobs naturally exhibit some variability; spot pricing fluctuations, data size changes, and code updates typically cause metrics to fluctuate between runs. When a job shows remarkably consistent metrics over time, it often indicates a forgotten process that’s quietly consuming resources without delivering business value. These jobs can silently drain your budget month after month.

Recommended action: Verify whether this job is still delivering actual value to your organization. If not, consider stopping the job entirely or migrating it to a more cost-effective solution.

Project details – understand “why”

We’ve embedded insights into every project to give you a side-by-side view of the Spark metrics and the corresponding insights extracted from the data. This is extremely helpful when diagnosing issues, optimizing performance, and mastering your Databricks environment.

• Faster root cause analysis: Quickly identify and resolve issues without shifting thought endless lists of logs. Identify what caused an anomaly and its source in under a minute.
• Effortless anomaly understanding: Gain the context required to understand why anomalies occurred by connecting Spark metrics, like shuffle and disk spill, to cost and performance information.
• Track historical cluster changes: Gradient automatically logs every cluster change, along with who made it (Gradient/user). Use these logs to quickly see if a change in the cluster is behind the anomaly you are observing.
• Empower Spark comprehension: Improve your grasp of Spark operations, by reviewing low level metrics in tandem with their high level impact on cost and performance.

But wait, there’s more! The insights above are just the tip of the iceberg. This initial delivers immediate, tangible value to our customers. Think of it as the appetizer before the main course.

Coming soon

We’re working on new insights that will take your Databricks job management to the next level:

• Cost and performance anomaly alerts: Say goodbye to those sneaky budget-busters and performance hiccups. We’ll give you a heads-up before they can ruin your day.
• Data pipeline growth insights: Watch your data pipelines evolve. We’ll help you understand how they’re growing and what that means for your infrastructure.
• GPU optimization suggestions: Ever wondered if throwing some GPU power at your jobs is the right move? Gradient’s integration with NVIDIA RAPIDS lets you know when to do that, how much it will save you, and how it will impact performance.

These upcoming features aren’t just bells and whistles – they’re the secret sauce that will help you squeeze every last drop of efficiency out of your Databricks environment. Stay tuned, because the best is yet to come!

Conclusion

In today’s data-driven environment, the difference between success and failure often comes down to how quickly you can convert raw data into actionable intelligence. Gradient Insights bridges that gap for your Databricks jobs, transforming complex metrics into clear guidance.

By highlighting what matters most – failures, variability, dormancy, and waste – Insights helps you:

• Proactively address issues before they impact your business
• Optimize your Databricks spend by identifying inefficiencies
• Focus your team’s energy on high-impact improvements
• Maintain reliability of your critical data pipelines

The days of being blindsided by job failures or unexpected costs are over. With Gradient, you’re not just monitoring your jobs, you’re mastering them.

Interested in learning more? Book a time to connect with the team here!