Last October, Splunk Observability Evangelist Jeremy Hicks wrote a great piece here about the Four Golden Signals of monitoring. Jeremy’s blog comes from the perspective of monitoring distributed cloud services with Splunk Observability Cloud, but the concepts of Four Golden Signals apply just as readily to monitoring traditional on-premises services and IT infrastructure.

Observability solutions can easily and rapidly get complex — in terms of maintenance, time and budgetary constraints. But observability doesn’t have to be hard or expensive with the right solutions in place. The future of your observability can be a bright one.

Data Lakes can be difficult and costly to manage. They require skilled engineers to manage the infrastructure, keep data flowing, eliminate redundancy, and secure the data. We accept the difficulties because our data lakes house valuable information like logs, metrics, traces, etc. To add insult to injury, the data lake can be a black hole, where your data goes in but never comes out. If you are thinking there has to be a better way, we agree!

After the craziness of the last few years, it is understandable that IT, DevOps, and operations teams want more stability in their personal lives and professional roles. However, there appears to be a disconnect between their desire for stability and the vision from the top.

The Accelerate State of Devops Report highlights four key metrics (known as the DORA metrics, for DevOps Research & Assessment) that distinguish high-performing software organizations: deployment frequency, lead time for changes, time-to-restore, and change fail rate. Observability can kickstart a virtuous cycle that improves all the DORA metrics.

Understanding what's happening within your systems is a necessity. Have you ever wondered how experts keep an eye on systems to make sure everything's running smoothly? That's where observability tools come in! Observability tools are like helpers that give you a peek inside your tech. In this blog, we will talk about observability tools and how they can be used in different situations so it's easier for you to choose the right one for your organization.

The needs of observability workloads can sometimes be orthogonal to the needs of compliance workloads. Honeycomb is designed for software developers to quickly fix problems in production, where reducing 100% data completeness to 99.99% is acceptable to receive immediate answers. Compliance and audit workloads require 100% data completeness over much longer (or "infinite") time spans, and are content to give up query performance in return.

In the world of observability, having the right amount of data is key. For years Apica has led the way, utilizing synthetic monitoring to evaluate the performance of critical transactions and customer flows, ensuring businesses have important insight and lead time regarding potential issues.

Application performance monitoring (APM) is much more than capturing and tracking errors and stack traces. Today’s cloud-based businesses deploy applications across various regions and even cloud providers. So, harnessing the power of metadata provided by the Elastic APM agents becomes more critical. Leveraging the metadata, including crucial information like cloud region, provider, and machine type, allows us to track costs across the application stack.

In today's market, companies undergoing digital transformation require secure and reliable systems to meet customer demands, handle macroeconomic uncertainty and navigate new disruptions. Digital resilience is key to providing an uninterrupted customer experience and adapting to new operating models. Companies that prioritize digital resilience can proactively prevent major issues, absorb shocks to digital systems and accelerate transformations.