Operations | Monitoring | ITSM | DevOps | Cloud

Until recently, Grafana Mimir — our open source, horizontally scalable, multi-tenant time series database (TSDB) — has exclusively used Prometheus’ PromQL engine to evaluate queries. While the PromQL engine works great, it sometimes needs a lot of memory to run, specifically in the Mimir querier component. To address this memory consumption issue, we recently introduced Mimir Query Engine (MQE).

Performance testing is critical to build reliable applications, but testing at scale, especially inside modern Kubernetes environments, can be a challenge. For example, how do you coordinate tests across multiple nodes, test private services without compromising security, or even do both at once? And most importantly, how do you do all this without adding too much operational complexity to your stack?

Companies rely on a variety of services to streamline their workflows, which often requires data synchronization or information sharing across platforms. But are your tools flexible enough to connect with external systems? ServiceNow is widely recognized for its robust and complex workflow support for enterprises. However, it may not always offer the most intuitive or user-friendly experience when handling incidents.

We recently released Grafana Assistant into public preview for Grafana Cloud, and we’ve been excited to see how our customers have already made it part of their daily observability routines. At the same time, Assistant is becoming a go-to companion for developers right here at Grafana Labs, whether they’re debugging on-call issues, helping customers, or trying to remember tricky PromQL syntax.

At Grafana Labs, we believe that effective alerting is the cornerstone of any robust observability strategy. That’s why we’re constantly listening to your feedback and working to improve the Grafana user experience so it’s easier for you to manage and interact with your alert rules. Today, we’ve excited to tell you about an update in Grafana Alerting that’s built to address some of your biggest pain points.

When your database stops accepting connections or your mail server becomes unreachable during business hours, the impact is immediate and costly. Fortunately, the right monitoring strategy can help you detect these TCP connection failures early on, and prevent them from impacting the user experience.

When multiple teams use Grafana, it can start to feel a bit messy. Dashboards pile up, permissions become unclear, and teams accidentally overwrite each other’s work. To help you and your organization stay clear, collaborative, and secure, we recommend putting all users in a single Grafana Cloud stack and managing access with teams, roles, and folders. To illustrate this, I’ll share a hypothetical example of how you can put this into practice across three teams. Let’s dive in!

A year ago, we hit a wall. Our Grafana OSS releases were excruciating to execute. The process was confusing and hard to follow, security patches were non-trivial, and many engineering hours were lost to an overly manual process. We needed to move fast, cut through ambiguity, and pull in just the right people without waiting on roadmaps or org charts.

Since its launch in 2020, the Infinity data source for Grafana has become the go-to solution to seamlessly query and visualize data from JSON, CSV, XML, and GraphQL endpoints within Grafana. Allowing users to integrate diverse data formats via HTTP-based APIs, the Infinity data source has enabled a wide range of use cases within our community over the years — from visualizing cloud computing costs to popular Pokémon games.

There’s a new way to ingest AWS metrics into Grafana Cloud that makes observing your AWS resources more cost-effective, easier to operate, and more accurate. You can now stream metrics into the AWS Observability app in Grafana Cloud in near real-time thanks to our new integration with Amazon CloudWatch and Amazon Data Firehose. We’re already using it internally, and we’re finding that it’s not only easier to operate—it’s at least five times more cost-effective.