Asking simple questions about your queries and loads shouldn’t be difficult. Which users write the most expensive queries? What’s the average query latency? How much time do queries wait in the queue? Which transformations are too slow or failing? Making sense of thousands of varying data points takes a lot of time and resources. That’s why intermix.io allows you to group queries and transfers by common traits. To measure performance and find insights you can act on.
The metrics you want
We’re not another view of the same old static metrics. A proactive discovery of query groups and latency trends help you understand where your data is stuck. We put your queries into context across users, the apps that connect to your cluster, and what resources they use. So you know what knobs to turn in Redshift to get the query performance your users are expecting.
Tune your workload management without the guessing
Trying to find the right concurrency and memory settings for your queues can be challenging. Data loads, batch jobs and ad-hoc queries all compete for the same resources. You start adding nodes but performance still doesn’t improve. Our Throughput Analysis shows you in one intuitive timeline view where your WLM queues need adjustment, or where you’re wasting resources.
Track your schemas and tables in Redshift
Our Storage Analytics give you the power to predict your future storage needs. They also help you understand where you can save on storage and reduce your node count. Track your schemas, tables and the workflows that make them grow. With our custom vacuum scripts, you can keep your cluster lean and save time.
More visibility into your Data Lake
Your entire (data) team
Our app tracing auto-discovers SQL annotations by popular dashboards such as Looker, Chartio and Periscope Data. You get insights about how apps and users interact with your data. Down to the single view in a dashboard. So data engineers, data scientists and data analysts are all on the same page. Quite literally.
Add visibility to your workflows
User our tag generator or Python plugin to tag SQL in your code. The best part about that? Now you can monitor query performance across your entire data lake, from your ETL pipelines and DAGs all the way to your dashboard queries. You’ll never have to worry about understanding where queries and data are coming from.
PRINCIPAL SW ENGINEER, UDEMY
“Our Redshift cluster has never been better! We’ve improved performance by 4x and reduced ETL time greatly. Intermix gave us the insights to fix our issues with slow query performance and fine tune our cluster.”
Ready to take back control of your cluster and your time?