Observability pipelines help cybersecurity teams maximize the value of their data by giving them critical visibility into telemetry. This visibility allows them to eliminate visibility gaps, enhance security operations center (SOC) efficiency, and reduce spending on high-cost SIEM tools. Until recently, the observability space has been dominated by point solutions like Cribl, Monad, and Observo.

As cyberattacks rise in number and sophistication, many CISOs are pushing their organizations to adopt modern SIEM solutions to better monitor and investigate threats to their applications and infrastructure. Enterprises with a large Microsoft Azure or Windows-based footprint in particular are increasingly eyeing Microsoft Sentinel to consolidate their security stack and workflows.

The current era of distributed work requires delivery of truly borderless digital applications and services powered by the cloud, delivered via a secure network centered on high performance and best in class user experience. It is essential that your organization has visibility and real-time insights into the data flow across the extended enterprise network as well as the ability to apply the necessary People, Process & Technology safeguards for data in transit and rest.

As outlined in a previous post, OpenTelemetry and Splunk Observability Cloud can provide great visibility when security teams investigate activity in modern environments. In this post, we look at another aspect of this visibility: how you can use traces to see directly into the workings of an application to find a potential threat. Let’s imagine we’re the security analyst, and a message comes across from the Security Operations Center (SOC).

Companies spend a huge amount of their budget trying to build, manage, and protect cloud environments. Since there is no industry standard for sharing data feeds between development and security, each team is on an island trying to figure out how to keep their side of the room clean. The most robust security incident response teams understand the incredible value of using observability telemetry for security workflows, but are unsure how to make it happen in practice.

Bolster your organization’s observability and security capabilities on one platform with AI, anomaly detection, and enhanced attack discovery Organizations in today’s digital landscape are increasingly concerned about service availability and safeguarding their software from malicious tampering and compromise. The traditional security and observability tools often operate in silos, leading to fragmented views and delayed responses to incidents.

Observability, especially in the context of cloud-native applications, is important for several reasons. First and foremost is security. By design, cloud-native applications rely on multiple, dynamic, distributed, and highly ephemeral components or microservices, with each microservice operating and scaling independently to deliver the application functionality.

As your business evolves to serve more users, your applications and infrastructure will generate an increasing volume of logs, which may contain sensitive data such as credit card numbers, IP addresses, and tokens. When you collect sensitive data, you may be subject to laws such as GDPR—which restricts the transfer of personal data across borders, and you may face legal consequences if this data is exposed outside your infrastructure.

Site reliability engineers (SREs) and security analysts — despite having very different roles — share a lot of the same goals. They both employ proactive monitoring and incident response strategies to identify and address potential issues before they become service impacting. They also both prioritize organizational stability and resilience, aiming to minimize downtime and disruptions.