This month I continued adding features to OnlineOrNot's status page functionality, while also taking the time to fix bugs, and add an integration for Pingdom.

As the Managed Service Provider (MSP) landscape continues to evolve, developing a robust MSP monitoring strategy is essential for MSPs wanting to stay ahead in an increasingly complex digital environment.Rapid advancements in technology, coupled with the growing complexity of IT environments, necessitates a shift in how MSPs approach monitoring. The fiercely competitive MSP market and external pressures on costs such as cloud pricing mean that customer expectations are high but profit margins slim.

Designed in the early 1990s Python was built to emphasize code readability and on the principle that there should be one way to do things. Python is one of the most popular programming languages and is utilized for a range of purposes including machine learning, web applications, and data analysis.

Docker is a popular platform that enables developers to package, distribute, and run applications within isolated environments called containers. Logs play an important role in the use of Docker for numerous reasons. For example, The running of Docker containers in isolation makes it difficult to handle troubleshooting issues and monitor application behavior effectively in the absence of detailed logging.

There's a new metrics service in town – Aiven for Metrics provides Prometheus metrics powered by Thanos. Aiven recently added a new service to our offerings: Aiven for Metrics is now in Early Availability. Similar to Aiven for M3, Aiven for Metrics is a Prometheus-compatible solution powered by Thanos, a CNCF project aimed at providing highly available Prometheus metrics with long term storage capabilities.

We are excited to announce the launch of Elastic's Support Assistant. This blog takes you through a tour of our latest generative AI tool and some common scenarios where it can help with your own use of Elastic technology.

Over the past year since its initial release, the InfluxDB 3.0 product suite has seen numerous new features and performance improvements. These improvements reinforce InfluxDB 3.0’s position as the industry’s leading time series database, offering unparalleled performance with unlimited cardinality, high-speed, independently scalable ingest, real-time querying, and superior data compression using Parquet format on cost-effective object storage.

New capabilities, including faster query performance and management tooling, advance the InfluxDB 3.0 product line InfluxDB Clustered general availability gives developers the power of InfluxDB 3.0 for the self-managed stack.