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What is Single Pane of Glass? A Complete Guide to Unified IT Management

Ever felt overwhelmed juggling multiple monitoring tools and dashboards? You're not alone. Today's IT environments are more complex than ever, and keeping track of everything can feel like watching a dozen TV screens simultaneously. That's where Single Pane of Glass comes in – it's like having a universal remote for your entire IT infrastructure.

Leveling up your observability practice - Part 2

Lessons from the front lines: Challenges in your observability maturity journey In our previous blog, we explored the observability maturity spectrum — revealing that while only 7% of organizations consider themselves experts, the majority (43%) are actively working to improve their practices. We saw how mature organizations achieve better outcomes, from faster root cause analysis to reduced user-reported incidents.

Adding AI to Observability 2.0 for Dynamic Observability

The original premise of observability was to ensure system health, identify issues, and resolve those issues efficiently. As I recently outlined, the legacy approach (sometimes called Observability 1.0 now) relied heavily on metrics and tracing because logs were seen as too noisy or challenging. But, as most forward thinkers have identified now, logs are exactly the telemetry type that we need the most.

Emergency Observability with Coroot

If you’re an experienced engineer, you likely have comprehensive observability and monitoring set up for your production systems. So if issues arise, you’re empowered to resolve them quickly. Yet, there are way too many systems out there, especially smaller and simpler ones, which are running with only rudimentary observability systems, or no observability at all. This means when an application goes down or starts to perform poorly, it may be very hard to pinpoint and resolve the issue.

Leveling up your observability practice - Part 1

Lessons from the front lines: Moving to observability maturity What separates the observability experts from the novices? It's a question that's been on my mind lately, especially after diving into our recent 2024 State of Observability Survey of over 500 practitioners. In my past roles as a DevOps engineer and a site reliability engineer (SRE), I've seen firsthand how a mature observability practice can be the difference between sleepless nights and smooth sailing.

Easily control observability collectors at scale with Fleet Management in Grafana Cloud

Managing observability workloads can quickly overwhelm even the most experienced admin. Maybe you’re dealing with multiple departments, each needing its own collector configurations and pipelines. Every time you have to run a test or roll out a change, the process is cumbersome and introduces risk. Or perhaps you’re responsible for tracking hundreds of collectors across different environments and regions. In a scenario like this, troubleshooting individual issues feels nearly impossible.

Splunk's Path Towards Achieving FedRAMP Moderate Authorization for Splunk Observability

Splunk continues to partner with government agencies on their digital transformation journeys to help deliver their missions and provide faster and more intelligent services. We are committed to the success and support of the security requirements of our public sector customers, and I am thrilled to share the latest strategic investments Splunk is making to expand our FedRAMP program to include Splunk Observability Cloud for government customers.

The Schrödinger's Cat Challenge of Observing Cloud-Native Applications

The Schrödinger's Cat thought experiment highlights the paradox of determining a system's state without direct observation—an apt analogy for the challenges of observing cloud-native applications. These systems' complex, ephemeral, and distributed nature often makes them appear as black boxes. Coupled with the operational complexities of multi-cloud and hybrid environments, gaining a clear picture feels impossible.

There Is Only One Key Difference Between Observability 1.0 and 2.0

We’ve been talking about observability 2.0 a lot lately; what it means for telemetry and instrumentation, its practices and sociotechnical implications, and the dramatically different shape of its cost model. With all of these details swimming about, I’m afraid we’re already starting to lose sight of what matters.