Snowflake and Databricks are both robust data platforms. Both are built for speed, scale, and cloud-native applications. They also prioritize efficiency and adherence to strict data protection protocols. Yet each adopts a distinct approach and features suited to its architecture and various use cases. It is these differences that can make all the difference in the way your data is processed, analyzed, reported, and more.

The demand for LLM is rapidly increasing—it’s estimated that there will be 750 million apps using LLMs by 2025. As a result, the need for LLM observability and monitoring tools is also rising. In this blog, we’ll dive into what LLM monitoring and observability are, why they’re both crucial and how we can track various metrics to ensure our model isn’t just working but thriving.

Microsoft offers several cost-saving opportunities with Azure pricing. Azure Reserved Instances, Azure Savings Plan, Azure Hybrid Benefit… all can help you save a pretty penny if you know what you’re doing. If you’re looking to cut costs with your Azure VMs, Spot VMs can be the way to go – but the risks can be just as high as the rewards. How do you help your FinOps organization save big – and improve your chances of avoiding a complete resource shutdown?

Tired of managing your Kubernetes clusters all on your own? Don’t have the time to figure out how to deploy, run, and optimize usage? Azure has just the thing for you: Azure Kubernetes Services. This article will cover everything you need to know about Azure Kubernetes Services, how it works, what the Azure pricing will be, whether you should use it, and, if so, how to save on your cloud cost.

This is an updated version of an earlier blog post that now includes links to our documentation. Full-text searches are a marvel of modern computing. In less than a second, search engines can match a query against hundreds of millions of documents. In the early days of search engines, you often had to use specific search operators and terms to get accurate results.

In the first post, we introduced system tables and how to use them to inspect your cluster. In this follow up, we’ll explain some techniques to improve the speed of system table queries.

In today's data-driven world, businesses need to collect, process, and analyze large volumes of data in real-time to make informed decisions. Amazon Kinesis, a powerful streaming platform, helps companies build scalable and resilient data pipelines. However, ensuring that the pipeline functions efficiently requires robust monitoring practices.

The cloud financial landscape is expanding with more vendors for companies to choose from to maintain healthy cloud costs. As the market grows, it’s important to partner with a third-party cloud financial management tool built on FinOps innovation and consistently adapt to meet future customer needs. A credible source recommending the right cloud cost tool can help you make an informed choice that positively impacts your cloud cost optimization.

As an InfluxDB Cloud Dedicated or Clustered user, you may want to inspect your cluster to gain a better understanding of the size of your databases, tables, partitions, and compaction status. InfluxDB stores this essential metadata in system tables (described in Section 1), which help inform decisions about cluster performance and maintenance.