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BASIC

The steps below will guide you to quickly finish setting up your Grafana
installation.

tutorial
Data source and dashboards

GRAFANA FUNDAMENTALS

Set up and understand Grafana if you have no prior experience. This tutorial
guides you through the entire process and covers the “Data source” and
“Dashboards” steps to the right.

complete

ADD YOUR FIRST DATA SOURCE


Learn how in the docs

dashboards

CREATE YOUR FIRST DASHBOARD


Learn how in the docs



DASHBOARDS





STARRED DASHBOARDS

RECENTLY VIEWED DASHBOARDS




LATEST FROM THE BLOG




Oct 15


VISUALIZE ATLASSIAN STATUSPAGE, CLOUDFLARE, AND NETLIFY DATA: WHAT’S NEW IN
GRAFANA ENTERPRISE DATA SOURCE PLUGINS

As part of our big tent philosophy here at Grafana Labs, we believe you should
be able to access and derive meaningful insights from your data, regardless of
where that data lives. One of the ways we stay true to that philosophy is
through our Enterprise data sources. Available in Grafana Enterprise and Grafana
Cloud, including in our generous free-forever tier, Enterprise data source
plugins allow you to connect to external systems from within Grafana, so you can
visualize data from a wide range of sources using the Grafana dashboards you
already know and love.
Oct 11


KEY PROMETHEUS CONCEPTS EVERY GRAFANA USER SHOULD KNOW

Prometheus has become an essential technology in the world of monitoring and
observability. I’ve been aware of its importance for some time, but as a
performance engineer, my experience with Prometheus had been limited to using it
to store some metrics and visualize them in Grafana. Being a Grafanista, I felt
I should dig deeper into Prometheus, knowing it had much more to offer than just
being a place to throw performance test results.
Oct 10


GRAFANA'S PROMETHEUS LIBRARIES: HOW WE BUILT LIBRARIES TO CREATE A TRULY
VENDOR-NEUTRAL DATA SOURCE

Over the summer we told you about an update to our core Prometheus data source,
which was part of a larger shift in our effort to meet users where they are.
It’s a change we’re really excited about, as it represents our biggest step yet
toward enabling the creation of truly vendor-neutral data sources for Grafana.
As part of this effort, we deprecated AWS authentication from the original
Prometheus data source, and we created a new dedicated Amazon Managed Service
for Prometheus data source plugin that will specifically cater to the AWS use
case.
Oct 08


INSIDE PROMQL: A CLOSER LOOK AT THE MECHANICS OF A PROMETHEUS QUERY

Even though I’m a Prometheus maintainer and work inside the Prometheus code, I
found many of the details of PromQL, the Prometheus query language, obscure.
Many times I would look something up, or go deep into the code to find out
exactly what it did, only to forget it again the next month. So, trying to live
up to my job title of Distinguished Engineer at Grafana Labs, I resolved to
write the definitive guide: what really happens when I execute a PromQL query?
Oct 07


GRAFANA FOR BEGINNERS: QUICK TIPS TO ADD A DATA SOURCE, CHOOSE A VISUALIZATION
TYPE, AND MORE

In the observability space, ease-of-use has always been a key differentiator for
Grafana. As much as we want to offer a powerful observability platform to our
users, we also want to ensure they can get up and running as quickly as
possible. Still, for those of you sitting down to build your first dashboard, we
totally understand that a little guidance can go a long way. In this post —
which was inspired by our “Grafana for Beginners” YouTube series — we offer
quick tips and step-by-step advice to help you and your team ramp up with
Grafana.
Oct 04


ADDRESSING METRIC OVERLOAD: A DEEP DIVE ON ADAPTIVE METRICS

When it comes to metrics, development teams often have a “better safe than
sorry” mindset of collecting anything and everything. But that can translate to
explosive growth of time series data, which can lead to higher costs and noisy
signals. It’s a challenge we saw many of our users facing, which is why we
developed Adaptive Metrics, a feature in Grafana Cloud that helps cut costs by
aggregating unused and partially used metrics into lower cardinality versions.
Oct 03


HOW TO USE PROMETHEUS TO EFFICIENTLY DETECT ANOMALIES AT SCALE

When you investigate an incident, context is everything. Let’s say you’re
working on-call and get pinged in the middle of the night. You open the alert
and it sends you to a dashboard where you recognize a latency pattern. But is
the spike normal for that time of day? Is it even relevant? Next thing you know,
you’re expanding the time window and checking other related metrics as you try
to figure out what’s going on.
Oct 02


CONTAINER MONITORING WITH GRAFANA: HELPFUL RESOURCES TO GET STARTED

In simple terms, containers are a standard package of software that enable
applications to run consistently across different computing environments. Often,
these applications are broken down into smaller collections of independent
services known as microservices. For many organizations, these
microservices-based applications have replaced traditional monolithic
applications because they offer increased performance, flexibility, and scale.
And within these distributed environments, observability is crucial to ensure
smooth operations and high performance. In this blog post, you’ll learn more
about using Grafana alongside Docker, Kubernetes, and Helm Charts, and some of
the resources we offer to help you get started.
Oct 01


OBSERVABILITYCON ON THE ROAD: WHAT TO EXPECT

Last week, we hosted ObservabilityCON 2024 in New York City. As in previous
years, our flagship observability conference was a great opportunity for our
community members to hear about all the latest updates to Grafana Cloud and the
Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces,
and Mimir for metrics), attend technical deep-dive sessions, learn from user
success stories, and more. Not to mention, it was a whole lot of fun.
Sep 30


HOW TO BUILD AUTOMATIC REMEDIATION WORKFLOWS IN GRAFANA CLOUD

When incidents occur, engineers must jump into action to get systems back to
running at peak performance. However, there are a myriad of challenges that can
prevent them from resolving the issues swiftly. Imagine a scenario where a team
of DevOps engineers manages a cloud-based e-commerce platform that experiences
occasional spikes in traffic during peak shopping seasons. During one of those
major sales events, the team notices a sharp spike in CPU usage across several
critical application servers.