We at Qovery are excited to offer our Preview Environments for free to all open-source projects. A Preview Environment is like a sandbox where developers can see how changes to the code will work before these changes are final. This is great for projects where many parts, like the backend, frontend, and databases, must talk to each other.

Digital innovation is transforming finance. Advances in financial technology such as mobile money, peer-to-peer (P2P) or marketplace lending, robo advice, and insurance technology (InsurTech) are reshaping many areas – from payments to wealth management. Over the past decade, fintechs have already driven enhanced access to financial services for retail users. Technology advances in connectivity, data processing, and storage have contributed to the current wave of technology-based finance.

At Datadog, we have always been deeply involved with open source software—producing it, using it, and contributing to it. Our Agent, tracers, SDKs, and libraries have been open source from the beginning, giving our customers the flexibility to extend our tools for their own needs. The transparency of our open source components also allows them to fully audit the Datadog software that is running on their systems. But our commitment to open source only starts there.

Technical folks in OSS communities often find themselves in permanent learning mode. Technology changes constantly, which means learning new things — whether it’s a new feature in the latest OSS release or an emerging industry best practice — is, for many of us, simply a natural part of our jobs. This is why it’s important to think about how we learn, and improve the skill of learning itself.

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.