Today, I’ll cover Shift Left Monitoring: A Pathway to Optimized Cloud Applications and how left-shifted troubleshooting of Spring Boot code issues using observability tooling can avoid production issues, unnecessary costs and improve product quality. Shift-left is an approach to software development and operations that emphasizes testing, monitoring, and automation earlier in the software development lifecycle.

DevOps is a software development philosophy that helps organizations achieve faster delivery, better quality, and more reliable software, making it easier to adapt to changing business needs and customer demands. However, implementing DevOps can be challenging on many levels. It requires changes in culture, processes, skills, knowledge, and tools, which can encounter resistance from traditional silos within organizations. So, how can you successfully implement DevOps within an organization?

Hello again! Continuing from our previous blog, in today’s blog we will delve into a crucial decision that organizations often face when considering AIOps implementation—the build vs. buy dilemma. During our LinkedIn Live event on Mapping the impact of AIOps for CIOs, CTOs, and IT managers, we explored the factors to consider when making the build-versus-buy decision and how it impacts an organization’s journey toward efficient IT operations.

While support for logging in the OpenTelemetry Python project is listed as 'experimental,' it's completely possible to send logs from your Python application. The Opentelemetry Collector has support for numerous existing logging systems, effectively exporting log data from wherever you were sending logs currently; you can also use the filelog receiver to tail and send logs from files. The only 'experimental' portion of the Python SDK is sending logs directly from code-level instrumentation.

In our service-driven world, businesses must provide the best user experience possible. Great service helps you retain long-term customers while also growing your customer base — to keep tabs on service performance, a few key metrics and signals come into play.

So you have been adding more and more logs to your Graylog instance, gathering up your server, network, application logs, and throwing in anything else you can think of. This is exactly what Graylog is designed for, to collect all the logs and have them ready for you to search through in one place. Unfortunately, during your administration of Graylog, you go to the System -> Overview screen and see the big bad red box, saying you are having indexing failures.

Before we do a detailed dive into what Prometheus and Datadog are, let's look at the key comparison points. Both Prometheus and Datadog are monitoring tools, but Prometheus is open source and Datadog is proprietary. Prometheus is the de facto tool for monitoring time-series for Kubernetes, and Datadog is an all-around APM, logs, time-series, and tracing tool.

This is the 25th year of the Open Source movement, and as with any social enterprise there is a constant effort to maintain and at times renegotiate the meaning of terms and the values behind them. Open Source is a child of the Free Software movement. It uncritically inherited its values and philosophy from its parent, but are those still sufficient today?