Operations | Monitoring | ITSM | DevOps | Cloud

Data enrichment is the process of adding additional context or attributes to telemetry data at the source that increases its value during analysis. OpenTelemetry, a collaborative open source telemetry project with the largest organizations in the observability space, can be configured to enrich logs and metrics from dozens of sources. This blog will show you the basics of how to use BindPlane OP to easily deploy and configure OpenTelemetry to enrich data from a source.

Earlier this month I hosted the “Everything You’ve Heard About Observability is Wrong (Almost)” webinar– thanks to all of you who attended. I wanted to follow-up with the attendees as well as those who were not able to join. As promised, it wasn’t the same old Observability presentation that we have grown accustomed to you know, all marketing with little value.

Splunk and Amazon Web Services (AWS) are celebrating 10 years of strategic collaboration — an incredible milestone which demonstrates our commitment to teamwork, co-innovation and exceptional, data-driven outcomes for our joint customers.

Observability is the ability to see and understand the internal state of a system from its external outputs. Logs, Metrics, and Traces, collectively called observability data, are three external outputs widely considered to be three pillars of observability. Now more than ever, organizations of all sizes must employ the necessary processes and technologies to harness the power of their data and make it more actionable.

So your team has access to a logging tool? Great! What’s the first thing you want to find? The latest config change gone wrong? Data from 30 days ago when a specific server was at high capacity? Or maybe you’d like to access logs for a certain IP on a certain day for specific HTTP and servers with counts and averages. Hopefully there was training to teach you the specific query languages and expert skills required to answer these questions.

Logs are a critical aspect of any production workload, as they give you insight into what is happening in your system and tell you which components may be having issues. The traditional method of looking at logs involves basic Linux commands like tail, less, or sometimes cat.

Large organizations often rely on multiple monitoring tools, security platforms, and auditing systems to meet the diverse needs of their observability, security, engineering, and compliance teams. Because these teams may use the same logs for many different use cases—including detecting potential threats or breaches, troubleshooting errors, and gauging the effectiveness of new features—it can be difficult to effectively standardize and route data.

Whether you’re rushing to troubleshoot an incident or proactively performing a security audit, the trial-and-error process of searching through millions of logs for key information can be time-consuming and cumbersome. To help you quickly surface important details from large swaths of log data, Datadog’s Log Explorer allows you to search and filter your logs, create visualizations, as well as group your logs by fields, patterns, or transactions.

Today, Cribl is releasing The State of Security Data Management 2022 in collaboration with CITE Research. The report examines the challenges that enterprises are facing as they work to balance evolving business priorities with cyber threats. The report was conducted in September 2022 and surveyed 1,000 senior-level IT and security decision-makers. The survey found that, although most organizations are confident in their data management strategy, few believe it’s actually sustainable.

As businesses generate, capture, and seek to analyze more data than ever before, they often find themselves limited by high data storage costs, expensive data processing fees, and high management overhead. For organizations who wish to expand their log analytics programs and become more data-driven, maximizing cost efficiency has become a critical operational objective.