Operations | Monitoring | ITSM | DevOps | Cloud

Keeping smooth and safe operations now relies entirely on observability. But as there's more and more data to keep track of, the costs are going up. This makes it hard for your companies to balance how well things are running and their budgets. OpenTelemetry can help by making a standard way to collect and process all the data. We're going to share how OpenTelemetry can save you money on observability and why having too much data can be costly.

Logstash serves as a real-time event processing engine within the OpenSearch ecosystem, which comprises OpenSearch, Beats, and OpenSearch Dashboards. Logstash acts as a centralized pipeline that collects data from numerous sources before forwarding it to OpenSearch.

Developed in the mid-1990s, Ruby is a dynamic, open-source programming language. The tool has grown in popularity from its initial release, having been used in modern systems covering a variety of corporate and academic use cases. Ruby gained further traction after the release of Ruby on Rails, a powerful web application framework written in pure Ruby.

Last time we spoke, I told you about our (then) brand-spankin’-new OTel over HTTP implementation, in both our OpenTelemetry Source and Destination. That was a little over a year ago, also known as a lifetime in tech! I wanted to take another opportunity to speak to you and introduce some of our new OpenTelemetry features, and share how you can put them into practice!

Observability is undergoing a massive shift as enterprises drive adoption of modern technologies, including cloud and microservices, along with disruptive technologies, such as generative AI (GenAI). To keep pace with the complex requirements of the modern tech stack, operations teams need to consider and adopt next-generation observability. Splunk users are often challenged by using products that provide fragmented observability, hampering their ability to modernize their environments.

As applications grow in complexity, the ability to gather, process, and analyze logs becomes crucial for maintaining system health and troubleshooting issues. Two popular open-source log collectors have emerged as frontrunners in this space: FluentD and FluentBit. But how do you choose between them? This article dives deep into the FluentD vs FluentBit debate, exploring their features, performance, and use cases to help you make an informed decision.

We are excited to announce the launch of Elastic's Support Assistant. This blog takes you through a tour of our latest generative AI tool and some common scenarios where it can help with your own use of Elastic technology.

Docker is a popular platform that enables developers to package, distribute, and run applications within isolated environments called containers. Logs play an important role in the use of Docker for numerous reasons. For example, The running of Docker containers in isolation makes it difficult to handle troubleshooting issues and monitor application behavior effectively in the absence of detailed logging.

Designed in the early 1990s Python was built to emphasize code readability and on the principle that there should be one way to do things. Python is one of the most popular programming languages and is utilized for a range of purposes including machine learning, web applications, and data analysis.