Tech Insights: Processing Video CDN Logs at Scale

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The task of processing video CDN logs at scale is a significant challenge for companies in the media and streaming industry. Our recent webinar, "Processing Video CDN Logs at Scale" (>> watch on-demand), brought together industry experts to discuss their experiences and best practices in managing vast amounts of log data efficiently and cost-effectively. This blog post summarizes the key insights and strategies shared during the event, featuring insights from G&L, Touchstream, and Paramount.

The Challenge of Video CDN Logs

Handling video CDN logs is a multifaceted problem that involves dealing with massive data volumes, ensuring data normalization across different vendors, and managing costs. Logs from CDN providers are essential for understanding user behavior, diagnosing issues, and optimizing content delivery. However, the sheer volume of data and the diversity of log formats can make this a daunting task.

Key Motivations and Strategies

Alexander Leschinsky (CEO of G&L) and Brenton Ough (CEO of Touchstream) highlighted the need for better log analytics tools that go beyond simple data aggregation. Both emphasized the importance of developing solutions that provide deeper insights into streaming issues, enabling quicker root cause analysis and more intuitive data visualization.

Sean McCarthy (Director of Product at Paramount) shared how Paramount focuses on CDN optimization and operational visibility. The team at Paramount has developed in-house tools to handle CDN logs, which are crucial for real-time troubleshooting and performance monitoring. One of their primary goals is to achieve operational visibility across their CDN infrastructure, allowing for quick identification and resolution of streaming issues. They also believe in coupling client-side health – as covered in our CMCD workshop (>> watch on-demand) – with back-end health (CDN).

Data Normalization

A critical aspect of managing CDN logs is data normalization. Each CDN provider has its own logging format, which can complicate data analysis. Paramount's approach involves normalizing logs to create a common set of fields. This standardization allows for consistent metric derivation and simplifies the comparison of performance data across different CDNs.

McCarthy explained that Paramount's system involves normalizing raw logs into a unified format, enabling effective operational analysis and root cause detection. This normalization process also facilitates the creation of comprehensive reports and dashboards that can be used by various stakeholders, from engineers to business analysts.

Sampling and Cost Management

Managing the cost of processing and storing CDN logs is a significant concern. Lyle Scott (Director of Software Engineering at Paramount) discussed the importance of log sampling as a cost-control measure. By sampling logs – particularly focusing on error logs while sampling success logs at a different rate – Paramount can reduce the volume of data processed without losing critical insights.

Scott also mentioned the potential of middleware solutions to implement session-based sampling, which can provide more granular data without overwhelming storage and processing capabilities. This approach helps in maintaining a balance between data comprehensiveness and cost efficiency.

Advanced Processing Techniques

Touchstream's approach to log processing involves several advanced techniques to enhance data interchange, transformation, and visualization:

Data Interchange: Efficiently transferring summarized data between systems is crucial. This requires clear requirements and robust metadata tracking to handle any data gaps or delays.
Data Transformation Pipelines: Utilizing discrete, autonomous services for data processing ensures that each component can be optimized for speed and efficiency. Techniques like data typing, caching with Redis, and using fast APIs for lookups significantly improve performance.
Custom Dashboards: Developing intuitive visualizations that operational teams can easily interpret is vital. Dashboards should be designed to present data in a way that is immediately actionable, linking to other tools for deeper analysis when necessary.

Storage Solutions

G&L employs several storage solutions to manage costs while handling large data volumes. Alexander Leschinsky highlighted the use of Hydrolix, a provider of next-generation data lake technology that integrates ClickHouse with object storage. This setup provides high compression rates and independent scaling of components, making it a cost-effective choice for storing and querying large log datasets.

By decoupling storage from computation, systems like Hydrolix enable organizations to manage vast amounts of data economically. For example, using S3-compatible storage like Wasabi can further reduce costs without sacrificing performance.

Leveraging AI and Machine Learning

While the primary focus of the webinar wasn't on AI, the potential of machine learning in enhancing log analysis was acknowledged. AI can play a significant role in anomaly detection and predictive analytics, but it requires well-normalized data to be effective. As the industry advances, integrating AI-driven insights will likely become more common, further optimizing log processing and analysis.

Conclusion

There are a lot of challenges and solutions associated with managing CDN logs. Key takeaways include the importance of data normalization, intelligent sampling, advanced processing techniques, and cost-effective storage solutions. By leveraging these strategies, companies can enhance their operational visibility, optimize performance, and manage costs effectively.

For organizations dealing with large-scale video CDN logs – as technology continues to evolve – staying ahead of the challenges will be crucial for delivering seamless and high-quality streaming experiences.