Get excited about Grafana Tempo 2.2! Not only is this release on time, but it is also chock full of TraceQL features and performance improvements. I was honestly a little shocked by how much we have accomplished in the last three months when summarizing the changelog.
It’s no secret that anyone can download our open source software and run it, because — once more with feeling — open source is in our DNA. But it can be hard to set up and configure a whole stack from scratch, which is why we offer Grafana Cloud as a fully managed observability platform.
Feature management is an emerging set of tools and techniques for developing and testing software based around feature flags. It’s intended to increase productivity and performance, as well as improve software quality. Of course, you’ll also need to keep tabs on all those feature flags, so it only makes sense to pair feature management with observability for a more holistic view of your software development cycles.
This blog post was co-authored by Igor Shvartser, Senior Technical Product Manager at Amazon Timestream, and Michael Mandrus, Senior Software Engineer at Grafana Labs. Grafana Labs Senior Software Engineers Stephanie Hingtgen and Kevin Minehart also helped with the content.
I’ve been working with Grafana Tempo for about half a year now, and one thing I like about it is that Tempo requires only object storage for storing traces, which is easy to set up in both cloud environments and on-premises. Another outstanding feature is TraceQL, which allows searching for relevant traces with a powerful query language.
In addition to the built-in user authentication that utilizes usernames and passwords, Grafana also provides support for various mechanisms to authenticate users, so you can securely integrate your instance with external identity providers. We are excited to announce that with the release of Grafana 10.0, we have introduced a new user interface that simplifies the configuration of SAML authentication for your Grafana instances.
In the observability space, it seems like everyone is talking about how to reduce costs and control the explosion of Prometheus metrics. It’s no wonder — our recent analysis of user environments suggests 20% to 50% of metrics generated are never used, but users are still stuck paying for them.
Interest in generative AI and large language models (LLMs) has exploded in popularity thanks to a slew of announcements and product releases, such as Stable Diffusion, Midjourney, OpenAI’s DALL-E, and ChatGPT. The arrival of ChatGPT in particular was a bellwether moment, especially for developers. For the first time, an LLM was readily available and good enough that even non-technical people could use it to generate prose, re-write emails, and generate code in seconds.
We’re excited to introduce a dedicated Grafana Cloud solution for Apache Mesos, an open-source project for managing clusters in your data center and at cloud scale. Apache Mesos is a distributed systems kernel, running on every machine in a cluster and providing easy orchestration of every resource in the cluster. This allows you to treat compute units, memory, and disk as a single pool of resources.
According to the World Bank, two-thirds of adults around the globe currently make or receive digital payments. Businesses have come to expect quick, reliable processing, and one company at the forefront of that is Worldline. The global payment service provider (PSP) is a leading payment processor and payment provider in Europe, with about 3.4 billion e-commerce transactions made in 2022.
