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Share: VictoriaMetrics is always improving, with frequent updates adding new features, performance improvements and bug fixes listed at the CHANGELOG page. We usually make at least a single release every month. All the new features and bug fixes go to the latest release. That’s why we recommend periodically upgrading VictoriaMetrics components to the latest available release. But the latest release may also contain bugs in the latest features.

The MongoDB document-oriented database is one of the most popular database tools available today. Developed as an open-source project, MongoDB is highly scalable and can be set up in your environment in just a few simple steps. When running and managing databases, monitoring is a key requirement.

The database is one of the most critical components here at Rollbar and its performance ripples across most of our SLOs. One of our goals last months has been to remove unnecessary or repetitive load from it as much as possible. Caching queries is the 101 solution whenever you need to keep scaling up while maintaining, or even reducing, database costs (very relevant these days). Here’s an example of how just one query has been drastically reduced thanks to caching.

Redis is a widely used in-memory database in the industry. As a consequence of its in-memory database, it can concurrently serve data as a key-value-oriented NoSQL database. Due to the use of in-memory data storage in Redis, you can achieve performance that is challenging with conventional databases. It is crucial to monitor Redis' resource usage since it is an in-memory data store.

Recently, a customer brought me a challenging use case: They were looking to enforce quotas on their internal customers, i.e. other teams in the organization. The analytics team provides services such as searching and reporting capabilities to those other teams, which subscribe to the services through a chargeback model. Each team that subscribes is supposed to limit its ingestion of data to a quota: a maximum permitted ingest per 24-hour period.