It’s a warm, sunny day as you lie in the sand under a big umbrella. Suddenly, you feel the waves crashing against your feet, only to look down and see numbers, letters, usernames, and timestamps. You try to stand up, but you feel the tide of big data pulling you under…
With a jolt, you wake up, realizing that you were having another nightmare about your security Data Lake and analytics. Everyone has anxiety dreams, but your ability to transform security telemetry into useful insights shouldn’t be causing nightmares.
Data pipeline management tools may be the next phase of security enabling technology, but not all organizations need heavy-hitting tools. A tool that’s too complex creates extra work that requires additional skills. A tool that’s too simplistic won’t give you the data necessary to scale your security analytics.
By understanding what a data pipeline is and what to look for in a solution, you can make an informed decision and find the solution that is the “just right” fit for your organization’s needs.
What is a data pipeline?
A data pipeline consists of automated digital processes that collect, transform, and deliver data from various sources to make analysis and visualization easier. It facilitates the systematic movement of structured, unstructured, and semi-structured data through the following steps:
- Ingestion: collecting data from sources
- Processing: cleaning and organizing data
- Transformation: applying a standard format to the data
- Data enrichment: supplementing with additional data to provide context
The two primary types of data pipelines are:
- Batch processing: handling large data volumes at scheduled intervals
- Real-time processing: handling data as it streams in from the source
What are the key components of a data pipeline?
A data pipeline enables you to aggregate, parse, and normalize data generated by diverse sources so you can normalize the format and send it to a desired destination, like a data warehouse or Data Lke. By understanding the key components, you can determine the type of technology necessary for your needs.
Data sources
In data analytics, your data sources can include everything from relational databases to business applications or even external datasets. In security, your environment, including your cybersecurity tools, generates the data.
Some examples of data sources include:
- Identity and access management (IAM) tools
- Operating systems
- Software and web applications
- Application Programming Interfaces (APIs)
- Endpoint detection and response (EDR)
- Devices, including Internet of Things (IoT) and network devices
Data ingestion
The ingestion or collection layer brings the data from the sources. With a security solution, you might use a listener or pull inputs.
Listener inputs wait for an application to push data. Some examples include:
- Syslog
- Beats
- CEF TCP/UDP
- IPFIX UDP
- NetFlow
- Raw/Plaintext TCP/UDP
Pull inputs reach out to an endpoint, typically using a method like an API. Some examples include:
- AWS CloudTrail
- AWS Kinesis/CloudWatch
- AWS Security Lake
- Azure Event Hubs
- Microsoft Defender for Endpoint
- Palo Alto Networks
- Google Workspace
Data processing
Data processing transforms raw data into a consumable format. At a high level, this process:
- Parses: splits data into elements, like fields
- Manipulates: analyzes and reorganizes data elements for business need
Data processing can include operations like filtering and sorting to make data usable.
In security, data processing uses pipeline rules that allow for the inspection, transformation, and routing of log data according to specified criteria before storing or indexing the data.
Data storage
You can choose to send your data to whatever repository makes sense. Some people use a data warehouse while others implement a Data Lake. Processing your data before sending it to the storage repository makes on-demand use easier. Your data pipelines should be optimized to ensure efficiency and reliability for processing and analysis.
Data consumption
At the consumption layer, you’re using your data for analytics and visualization. Essentially, this is the user interface that extracts and utilizes data from the chosen repository so you can engage in activities like:
- Searching data
- Using analytics
- Creating real-time reporting dashboards
Data governance
With the vast amounts of data that your environment generates, you need to have strong user access controls in place. In security, your data pipeline might contain sensitive information like:
- Names
- Birthdays
- Usernames
- Passwords
To meet compliance requirements, your data pipeline should enable you to limit who can access this data.
Benefits of Data Pipelines for Security Telemetry
Data pipelines organize your security telemetry so that you can derive insights across disparate tools and formats. By transforming data for analysis, you can improve the quality of your analytics to gain insights and automate repetitive tasks.
Real-time insights with security analytics
Real-time data pipelines transform your data as it streams from the sources. In cybersecurity, your data pipelines enable you to leverage security analytics that improve alert fidelity. For many organizations, having an end-to-end solution that parses, normalizes, and applies security analytics is optimal. Not every organization needs its own data science team, so having a solution that gives you what you need in a way that makes sense for your organization is key.
Efficient data processing to reduce costs
Every time your data passes through the pipeline, you incur processing costs. When implementing data pipelines, you want to limit the number of times the technology processes the data. Every time a data pipeline processes the data, you run the risk of losing or misinterpreting contextual data. Depending on your organization’s needs, you may want a solution built to streamline data processing so you can gain the insights you need while reducing the overhead costs.
Scalability with data routing
As you add more data sources, your data pipeline solution should be able to handle the increasing volumes without sacrificing performance. In security, this means having the ability to access critical data on-demand and managing data retention to ensure compliance. A data pipeline management solution should enables data routing that processes security telemetry efficiently into different categories, including:
- Active data: information processed, indexed, and stored for quick access, like real-time analysis, alerting, and troubleshooting
- Standby data: data that should be accessible, indexed, and in the original format to be retrieved on an as-needed basis
- Long-term storage: historical data stored in cost-efficient Data Lakes or S3 buckets
Data routing enables scalability because your pre-processed data is ready for on-demand use, meaning that you reduce overall processing costs by doing it before you store and have access to it when you need it.
Cost effective when using built-in tools
Building complex data pipelines from scratch can require specialized skills, especially when managing complex formats used in security logs. However, cost effective solutions that can process data and normalize it offer a way to get more value from your security telemetry. For example, you should look for solutions that provide:
- Intuitive interface
- Easy-to-navigate rule structures, like “when, then” statements
- Built-in functions
These capabilities mean you don’t need a sophisticated data science team to gain the benefits of a data analytics model.
Graylog: Security Data Pipelines Done Right
Graylog is one of only three vendors with 15+ years of experience offering a unified platform for centralized log management (CLM) and security information and event management (SIEM). Regardless of your deployment, Graylog gives you the versatility necessary to build data pipelines that uplevel your threat detection and incident response (TDIR). Our rapid search and investigation capabilities are built on the core foundation that you should have usable access to your data. Our data management capabilities enable you to log everything without sacrificing budget, efficiency, or compliance so that you can improve your IT operations and security capabilities in a way that fits your organization’s needs.
