Operations | Monitoring | ITSM | DevOps | Cloud

Any existing InfluxDB user will notice that InfluxDB underwent a transformation with the release of InfluxDB 3.0. InfluxDB v3 provides 45x better write throughput and has 5-25x faster queries compared to previous versions of InfluxDB (see this post for more performance benchmarks). We also deprioritized several features that existed in 2.x to focus on interoperability with existing tools. One of the deprioritized features that existed in InfluxDB v2 is the task engine.

The commercial version of InfluxDB 3.0 is a distributed, scalable time series database built for real-time analytic workloads. It supports infinite cardinality, SQL and InfluxQL as native query languages, and manages data efficiently in object storage as Apache Parquet files. It delivers significant gains in ingest efficiency, scalability, data compression, storage costs, and query performance on higher cardinality data.

Node.js logging is an important part of supporting the complete application life cycle. From creation to debugging to planning new features, logs support us all the way. By analyzing the data in the logs, we can glean insights, resolve bugs much quicker, and detect problems early and as they happen. In this post, we will talk about the who, what, when, where, how, and why of Node.js logging. Later in this post, the “how” section will give insights into using code.

Want to hear a sad but true fact? 70% of companies overshoot their cloud budgets. Why is that? Although the cloud is a mighty tool for speed, scalability, and innovation, the inability to see costs can lead companies to limit cloud usage, which hampers innovation and puts them at a disadvantage against the competition. Rather than limiting cloud usage, adopting the FinOps approach provides the insights you need to feel confident about your cloud costs.