Operations | Monitoring | ITSM | DevOps | Cloud

Time series data is becoming more prevalent across many industries. Indeed, it is no longer limited to financial data. As the need to handle time-stamped data increases, the demand for specialized databases to handle this type of data has also grown. The solution: Time series databases. In this introduction guide, we'll explain all the basics you need to know about time series databases, including what they are, how they work and are applied, and some of their benefits.

Deploying database code using pipelines in various CI/CD tools is a common practice among our customers who use Flyway. To enhance security and avoid hardcoding sensitive information like connection strings, they frequently employ variables and secrets in the pipelines.

When cloud service providers first started popping up, many developers were “wowed” by being able to spin up and scale all kinds of infrastructure to deploy their web applications on demand. However, big-box cloud service providers are often complex to use, scaling out is expensive and default monitoring solutions are not very insightful. Besides, we are spoiled developers, and we expect things to be easy.

Monitoring and observability are critical components of modern IT infrastructures, enabling organizations to gain insights into the performance, health, and security of their systems. Agents play a crucial role in gathering and forwarding telemetry from various sources to observability platforms.

Integrating time series data with the power of vector databases opens up a new frontier for analytics and machine learning applications. Time series data, characterized by its sequential order and timestamps, is pivotal in monitoring and forecasting across various domains, from financial markets to IoT devices. InfluxDB, a leading time series database, excels in handling such data with high efficiency and scalability.