Three different businesses, one shared problem: SailPoint, Kushki, and Flexcity were all looking for a hosted solution to help them optimize their telemetry storage, gain more insights from their observability strategy, and keep costs manageable. But what they gained from migrating to Grafana Cloud and working with Grafana Labs was much more. “The engineering team is super sharp. They’re experts. This is the best of the best," said Omar Lopez, head of the observability team from SailPoint.

Many often wonder, “Is there a difference between observability and monitoring?” The thing is as IT environments have become more complex, monitoring alone has become increasingly less effective. That’s because while monitoring is crucial, it isn’t particularly suited to tracking unforeseen or unexpected turns of events. That’s what observability is meant for. This guide will clarify what observability and monitoring are – and how they differ.

Node.js was introduced over 20 years ago and remains a popular choice for web application teams with over 30 million users. Sites such as Netflix, PayPal, and Uber continue to rely on Node.js to build and maintain their applications.

Today at Google Next, Charity Majors demonstrated how to use Honeycomb to find unexpected problems in our generative AI integration. Software components that integrate with AI products like Google’s Gemini are powerful in their ability to surprise us. Nondeterministic behavior means there is no such thing as “fully tested.” Never has there been more of a need for testing in production!

As a manager, figuring out how to talk to your engineering teams about building a strong observability strategy can feel overwhelming. But don't worry! This post will help you navigate the challenges to unlock the full power of observability in your IT environment. Drawing on insights from over 40 discussions with larger enterprises, we've put together a strategy assessment that examines three key focus areas — what we’re calling aspects — each encompassing three actionable steps.

Splunk’s extensible and scalable data platform has been instrumental in helping ITOps teams fully understand their tech environments and tackle any IT use case with data streaming, dashboarding, federated search, AI/ML, and more. But, with the explosion of telemetry and the growing complexity of digital systems, ITOps practitioners who rely solely on a logging solution are missing out on critical insights from their digital systems.

Site reliability engineers (SREs) and security analysts — despite having very different roles — share a lot of the same goals. They both employ proactive monitoring and incident response strategies to identify and address potential issues before they become service impacting. They also both prioritize organizational stability and resilience, aiming to minimize downtime and disruptions.

A few days ago, I was in a meeting with a prospect who was just starting to try out OpenTelemetry. One of the things that they did was to create an observability demo project which contained an HTTP reverse proxy, a web frontend, three microservices, a database, and a message queue. Here’s a rough diagram: Their motivation was to try out OpenTelemetry and see how much effort it took for them to instrument their system.

LogicMonitor’s agentless collection has long provided customers with many benefits for collecting telemetry data directly from network devices. Recently, LogicMonitor added another feature, enabling the discovery of devices/sites and the collection of telemetry data from the Cisco Catalyst Center. Retaining options is essential due to the pros and cons associated with each approach.

Recently, Elastic announced the AI Assistant for Observability is now generally available for all Elastic users. The AI Assistant enables a new tool for Elastic Observability providing large language model (LLM) connected chat and contextual insights to explain errors and suggest remediation.