Dashbird

A monitoring and logging solution tailored for serverless architectures, addressing unique security challenges.

AWS Proprietary Cloud Service Only
Category Serverless Security
Last page update 19 days ago
Pricing Details Contact for pricing details.
Target Audience Developers and security teams working with serverless architectures.

Dashbird addresses the unique security challenges of serverless architectures by providing a tailored monitoring and logging solution. The core challenge in serverless environments is the lack of visibility and control over transient resources, which can lead to blind spots in security monitoring.

Dashbird's technical architecture involves integrating deeply with serverless platforms like AWS Lambda, API Gateway, and other cloud services. It collects and analyzes logs, metrics, and traces from these sources, offering real-time insights into function execution, errors, and performance issues. The tool utilizes a combination of agentless data collection and native service integrations to minimize overhead and ensure comprehensive visibility.

Operationally, Dashbird is designed to handle the high volume and variability of serverless logs. It includes hundreds of pre-configured alarms and insights that help identify security anomalies and performance issues quickly. However, the tool's effectiveness can be limited by the volume of data it needs to process, particularly in large-scale deployments where log retention and query performance may become significant considerations.

From a technical standpoint, Dashbird supports various logging protocols and can handle sub-second granularity for many metrics. It also provides detailed visualizations and investigative tools to help developers and security teams drill down into specific issues. While it excels in real-time monitoring, historical analysis may incur additional costs due to data retention requirements, especially in multi-account setups. Overall, Dashbird offers a robust solution for securing and monitoring serverless environments, but it requires careful management of data volumes and retention strategies to maximize its benefits.

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