Introduction In the world of Data, iron clad security is table stakes when considering 3rd party vendors to work with. Here at Sync, we take our customer’s security seriously and want to assure that their sensitive information is handled with utmost care. This is why we are thrilled to announce that Sync has successfully achieved
Jeffrey Chou
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Databricks recently released System Tables, to help users understand and monitor their usage. They also had the older and more skunk works project called Overwatch, which also provides usage and infrastructure information. So what’s the difference between the two? When should I use either one? Let’s dive in! Introduction Databricks as a whole is a
Jeffrey ChouBlog
Databricks is a popular unified analytics platform and a go-to solution for many organizations looking to harness the power of big data. Its collaborative workspaces have become the industry standard for data engineering and data science teams and an ideal environment for building, training and deploying machine learning and AI models at scale. However—as with
Jeffrey ChouBlog
Since we launched Gradient to help control and optimize Databricks Jobs, one piece of feedback from users was crystal clear to us: “It’s hard to set up” And we totally agreed. By nature, Gradient is a pretty deep infrastructure product that needs not only your Spark eventlogs but also cluster information from your cloud provider.
Pete TamisinBlog
Realities of company and cloud complexities require new levels of control and autonomy to meet business goals at scale
Jeffrey ChouBlog
Configuring Databricks clusters can seem more like art than science. We’ve reported in the past about ways to optimize worker and driver nodes, and how the proper selection of instances impacts a job’s cost and performance. We’ve also discussed how autoscaling performs, and how it’s not always the most efficient choice for static jobs. In
Jeffrey ChouBlog
