Hello. How can we help you?
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DEVICE INTEGRATION
- Palo Alto (Device Integration)
- Dell Cylance Endpoint
- McAfee Web Gateway
- Imperva WAF
- Darktrace
- Forescout CounterACT
- Juniper Cortex Threat
- Zscaler
- Sophos
- Sophos Endpoint
- Trend Micro
- Sophos Cyberoam Firewall
- Radware-WAF
- NetScaler WAF
- Ubuntu
- Juniper SRX
- Forcepoint Websense
- FireEye
- Forcepoint DLP
- F5 BIG-IP ASM
- CyberArk PIM
- CheckPoint
- Bluecoat Proxy
- Accops Hyworks
- Barracuda WAF Syslog
- Forwarding F5 Distributed Cloud Services Logs to DNIF over TLS
- JIRA CLOUD
- Aruba ClearPass
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CONNECTORS
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- 1Password Connector
- Abnormal Security
- Akamai Netstorage
- Atlassian
- Auth0 Connector
- AWS CloudTrail
- AWS Kinesis
- AWS S3
- AWS S3 (Optimized)
- AWS S3 Optimized Cross Account Connector
- Azure Blob Storage Connector
- Azure Event Hub
- Azure NSG
- Beats
- Box
- Cisco Duo
- Cloudflare Logpull Connector Setup Guide
- CloudWatch Connector
- Cortex XDR
- CrowdStrike
- Cyble Vision
- Device42
- Dropbox Connector
- GCP
- GCP PUB/SUB
- GitHub
- Google Workspace
- Haltdos
- HTTP Connector
- Hub Spot Connector
- Indusface
- Jira Connector
- Microsoft Graph Security API
- Microsoft Intune
- Mimecast
- Netflow
- Netskope Connector
- Network Traffic Analysis
- NextDLP Reveal
- Office 365
- Okta
- OneLogin
- Orca
- PICO Legacy Connector
- Prisma Alerts
- Prisma Incidents
- Salesforce
- Salesforce Pub/Sub Connector
- Shopify Connector
- Slack
- Snowflake
- Snyk Connector
- Syslog
- TCP
- Tenable Vulnerability Management Connector
- TLS
- Trend Micro Audit Logs
- Workday HCM Connector
- Zendesk
- Zoom
- Jumpcloud Connector
- Sophos connector
- Tenable Security Center Connector
- AWS GuardDuty Connector
- Trend Micro Vision One Connector
- RediffMail Pro Connector
- Microsoft Sentinel
- Microsoft Exchange Online Connector
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DATA INGESTION
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HUNTING WITH WORKBOOKS
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- Your first FIND with the HYPERCLOUD
- Create a Search Block
- Create a Signal Block
- Create a Text Block
- Create an Outlier Block
- Create a DQL Block
- Create an SQL Block
- Create a Code Block
- Create a Visualisation Block
- Create a Call Block
- Create a Return Block
- Create a Notification Block
- Schedule a Workbook
- Native Workbook
- Workbook Functions
- How to view Workbooks?
- Add Parameters to Workbook
- Working with Pass through Content
- How to create a Workbook?
- Workbooks
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DNIF Query Language (DQL Language)
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SECURITY MONITORING
- Streamline Alert Analysis with Signal Tagging
- Workbook Versioning: Track, Collaborate, and Restore with Ease
- What is Security Monitoring?
- Creating Signal Suppression Rules
- Why EBA
- Signal Suppression Rule
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- What are signals?
- View Signal Context Details
- Suspect & Target
- Source Stream
- Signal Filters
- Signal Data export
- Signal Context Details
- Signal Confidence Levels
- Raise and View Signals
- Investigate Anywhere
- How to add a signal to a case?
- Graph View for Signals
- Global Signals
- False Positives
- Add Multiple Signals to a Case
- Add comment to the signal
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OPERATIONS
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MANAGE DASHBOARDS
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MANAGE REPORTS
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USER MANAGEMENT & ACCESS CONTROL
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BILLING
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MANAGING YOUR COMPONENTS
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GETTING STARTED
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INSTALLATION
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SOLUTION DESIGN
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AUTOMATION
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- Active Directory
- AlienVault
- Asset Store
- ClickSend
- Domain Tools
- Fortigate
- GreenSnow
- JiraServiceDesk
- Microsoft Teams Channel
- New Relic
- Opsgenie
- PagerDuty
- Palo Alto
- ServiceNow
- Slack Configuration
- TAXII
- Trend Micro
- URLhaus
- User Store
- Virustotal
- Webhook
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TROUBLESHOOTING AND DEBUGGING
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- TLS ( Troubleshooting Procedure)
- TCP (Troubleshooting Procedure)
- Syslog (Troubleshooting Procedure)
- Salesforce ( Troubleshooting Procedure)
- PICO
- Office 365 (Troubleshooting Procedure)
- GSuite
- GCP (Troubleshooting Procedure)
- Beats (Troubleshooting Procedure)
- Azure NSG ( Troubleshooting Procedure)
- Azure Eventhub
- AWS S3 (Troubleshooting Procedure)
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LICENSE MANAGEMENT
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RELEASE NOTES
- May 6, 2026 - Content Update
- March 31, 2026 - Content Update
- March 16, 2026 - Application Update
- February 26, 2026 - Content Update
- January 19,2026 - Content Update
- December 23, 2025 - Application Update
- December 4,2025 - Content Update
- November 27, 2025 - Application Update
- October 28, 2025 - Content Update
- August 20, 2025 - Content Update
- August 5, 2025 - Application Update
- July 15, 2025 - Content Update
- June 13, 2025 - Content Update
- May 21, 2025 - Content Update
- April 17, 2025- Content Update
- March 25, 2025- Content Update
- March 18, 2025 - Application Update
- March 5, 2025 - Application Update
- January 27, 2025 - Application Update
- January 29, 2025 - Content update
- December 30, 2024 - Content Update
- December 12, 2024 - Content Update
- December 3, 2024 - Application Update
- November 15, 2024 - Content Update
- October 26, 2024- Application Update
- October 23, 2024 - Content Update
- October 16, 2024 - Application Update
- September 04, 2024 - Application Update
- September 04, 2024 - Content Update
- August 27, 2024 - Application Update
- July 30, 2024 - Application Update
- June 04, 2024- Application Update
- April 24, 2024- Application Update
- March 26, 2024 - Application Update
- February 19, 2024 - Application Update
- January 09, 2024 - Content Update
- January 09, 2024 - Application Update
- November 27, 2023 - Content Update
- November 27, 2023 - Application Update
- October 05, 2023 - Application Update (Release Notes v9.3.3)
- May 30, 2023 - Application Update (Release Notes v9.3.2)
- November 29, 2022 - Application Update (Release Notes v9.3.0)
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API
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POLICIES
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SECURITY BULLETINS
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BEST PRACTICES
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DNIF AI
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DNIF LEGAL AND SECURITY COMPLIANCE
Scaling Datanodes
Considerations
- DNIF Datanodes are designed such that compute is decoupled from the storage requirement.
- DNIF leverages data compaction and compression techniques to achieve near 10:1 compression over your event data including the raw log, processed and enriched fields. This lets you retain all your data online at no extra cost.
- DNIF does not cap the storage on a datanode so we only need to size for compute requirements.
- All datanodes in your tenant (previously known as cluster) must be of identical hardware specifications.
Recommendations
- Our recommended minimum datanode configuration is 32vCPUs with 64GB RAM per datanode and no caps on storage. This configuration will enable effective search and correlation over upto 1TB of daily log ingestion.
- You will need 32vCPUs for every additional TB of your daily log volume.
- It is preferable to have fewer datanodes with higher CPU density.
| Average EPS | Daily Raw Volume | vCPUs | Disk Speed | Memory | Disk Space |
| 15K EPS | ITB | 32 vCPUs | 400 MBps | 64GB | 18TB |
| 25K EPS | I.7TB | 64vCPUs | 400 MBps | 128GB | 30.6TB |
| 50K EPS | 3.5TB | 128 vCPUs | 2000 MBps | 256GB | 63TB |
| 100K EPS | 7TB | 224vCPUs | 3000 MBps | 448GB | 126TB |
| 500K EPS | 35TB | 1120vCPUs | 5000 MBps | 2240GB | 630TB |
| Note:For Daily Raw volume an average log size is of 800 bytesFor Disk Space we are considering three month retention period and zero replications | |||||
15K EPS / 1TB Daily Ingestion
- 15K EPS at an average raw log size of 800 bytes equates to around 1TB of daily log ingestion.
- This setup will require a minimum of 32 vCPUs which can be met by a single 32vCPU datanode.
- Recommend use of storage with minimum read/write speed of 400 MBps.
25K EPS / 1.7TB Daily Ingestion
- 25K EPS at an average raw log size of 800 bytes equates to around 1.7TB of daily log ingestion.
- This setup will require a minimum of 64vCPUs which can be met by 2x 32vCPU datanoes or a single 64vCPU datanode.
- Recommend use of storage with minimum read/write speed of 400 MBps.
50K EPS / 3.5TB Daily Ingestion
- 50K EPS at an average raw log size of 800 bytes equates to around 3.5TB of daily log ingestion.
- This setup will require a minimum of 128 vCPUs which can be met by 4x 32vCPU or around 2x 64vCPU datanodes.
- Recommend use of storage with minimum read/write speed of 2000 MBps.
100K EPS / 7TB Daily Ingestion
- 100K EPS at an average raw log size of 800 bytes equates to around 7TB of daily log ingestion.
- This setup will require a minimum of 224 vCPUs which can be met by 7x 32vCPU or around 4x 64vCPU datanodes.
- Recommend use of storage with minimum read/write speed of 3000 MBps.
500K EPS / 35TB Daily Ingestion
- 500K EPS at an average raw log size of 800 bytes equates to around 35TB of daily log ingestion.
- This setup will require a minimum of 1120 vCPUs which can be met by 18x 64vCPU or around 12x 96vCPU datanodes.
- Recommend use of storage with minimum read/write speed of 5000 MBps.
