Handling PCAPs for Compliance, Security, and Scalable Network Analysis: A CloudShark Enterprise Case Study

When a global enterprise specializing in workflow automation and business transformation expanded its network operations, it deployed CloudShark Enterprise across 24 data centers worldwide. Their objective: enable secure, compliant, and scalable PCAP analysis without transferring sensitive data out of their data centers. Here, we’ll walk through how this major organization tackled its unique challenges and explore best practices inspired by its deployment strategy.

1. Data compliance and security: localized PCAP analysis across data centers

For this enterprise, data compliance was paramount. Their network data contained sensitive Personally Identifiable Information (PII) and customer information that must stay within each data center for regulatory and privacy reasons. CloudShark Enterprise allowed them to maintain on-site analysis, keeping data local and secure.

Best practices for localized data security:

Deploy CloudShark Enterprise in each data center to keep data where it’s generated, eliminating the need to transfer sensitive files and reducing compliance risks.
Disable file downloads to ensure data never leaves the secure environment, preventing unauthorized access or external handling.
Use auto-delete policies to remove unused data after 60-90 days, keeping only necessary files for active troubleshooting and maintaining compliance standards.

This setup allowed the company to retain data securely in each data center, meeting compliance requirements while ensuring data integrity.

2. Controlled access through authentication and access control

In an organization of this scale, network operations, customer support, and other teams need targeted access to PCAP data that did not cross any security or permission boundaries. The company used CloudShark’s SAML-backed authentication and group permissions to control and separate access to meet these needs.

Best practices for secure access control:

Implement SAML authentication for secure access that ties into existing identity management systems, providing Single Sign-On (SSO) capabilities.
Assign group-based permissions to restrict data access by team or role, allowing only authorized personnel to access relevant data.
Regularly audit and adjust permissions to maintain compliance and keep pace with organizational changes.

With these measures, the organization restricted data viewing to specific teams, minimizing the risk of unauthorized access.

3. Simplified troubleshooting with filtering and visualization

This enterprise observed a challenge common to large-scale network operators: traditional PCAP analysis requires a high skill level. To address this, they wanted to lower the barrier to analysis, allowing more team members to troubleshoot effectively. CloudShark Enterprise’s powerful graphical tools provided an intuitive starting point for filtering and analysis, making it easier for non-experts to identify issues.

Best practices for accessible analysis:

Begin analysis with graphical traffic representations to spot anomalies quickly, allowing users to zoom in on specific streams or issues.
TCP analysis flags and window scaling graphs can be used to diagnose network performance issues visually without sifting through raw data.
Apply capture filters at the point of capture to narrow down traffic. This will make it easier for users to find relevant data without opening large files.

CloudShark Enterprise’s visualization tools allowed this organization's network team to let junior analysts find problem areas quickly in PCAP data without sacrificing the expert-level details needed for root-cause analysis.

4. Efficient data management for high-volume environments

Managing the sheer volume of network data across 24 data centers was challenging. The company implemented efficient data retention practices to keep their system clean and compliant, while ensuring they had relevant data available for active troubleshooting.

Best practices for managing large PCAP data sets:

Set up ring-buffer or time-limited captures to retain only the most recent data, minimizing storage strain while keeping necessary data for immediate troubleshooting.
Use graphical summaries to look at high-level traffic trends without needing to download or open every capture file.
Configure automatic cleansing processes for long-term data retention, ensuring compliance by anonymizing or cleansing data that requires longer storage.

Through these strategies, the organization kept their data storage lean, allowing for efficient access to fresh data while discarding outdated files.

5. Fostering collaboration and skill development across teams

The company recognized the shortage of skilled PCAP analysts, so they focused on making analysis tools accessible to a broader range of users. By configuring CloudShark Enterprise for team-wide access, they promoted cross-functional collaboration and made it easier for team members to leverage packet data insights.

Best practices for enabling collaborative analysis:

Share CloudShark Enterprise access with key teams (e.g., Network Operations, Support) to enable collaborative problem-solving and reduce troubleshooting time.
Use profiles to help visualize pcap data in the right way for the right problems across teams.
Use annotations and tagging to document insights directly within captures, facilitating knowledge sharing and enabling more seamless collaboration.
Provide training on CloudShark’s tools so users can quickly grasp filtering and graphing options, lowering the skill barrier for PCAP analysis.

This approach allowed the company to leverage CloudShark Enterprise fully, turning network data into a shared resource and making analysis more accessible.

Looking forward: future-proofing network analysis with CloudShark Enterprise

The organization anticipates evolving its PCAP analysis in the coming years, reducing reliance on manual analysis and exploring automation to make insights even more accessible. CloudShark Enterprise is a crucial part of their forward-thinking strategy, enabling scalable, compliant, and efficient network analysis that meets today’s demands and sets the stage for the future.