Introduction

Security is paramount for almost any sized organization. With the rapid pace of technological advancements and the increasing reliance on digital infrastructure, organizations face an ever-evolving landscape of cyber threats and risks. Protecting sensitive data, intellectual property, and customer information is no longer optional; it is a critical component of maintaining trust and credibility in the marketplace.

A security breach can have devastating consequences, including financial losses, legal repercussions, reputational damage, and the erosion of customer trust. Enterprises must prioritize robust security measures to safeguard their operations, maintain regulatory compliance, and ensure business continuity. 

Here are just some of the costs associated with Security breaches:

• Average Cost of a Data Breach: The average cost of a data breach in 2021 was $4.45 million globally, according to the IBM Cost of a Data Breach Report 2023
• Average Cost of a Ransomware Attack: Ransomware attacks cost companies an average of $1.82 million per breach, according to Sophos' "The State of Ransomware 2023” Report
• Phishing as a Top Threat: Phishing attacks cost companies an average of $4.65 million per breach, according to the IBM Cost of a Data Breach Report 2023 
• Global Cybercrime Costs: The annual global cost of cybercrime is expected to reach $10.5 trillion by 2025, according to Cybersecurity Ventures 
• Impact on Stock Price: Companies that experience a cyber attack see a drop in stock price by 3.5% on average according to the IBM Cost of a Data Breach Report 2023

It should be clear that security incidents must be avoided at all costs. There are tools that can help detect and even prevent security incidents and mitigate these risks such as SIEM platforms. A SIEM, or Security Information and Event Management platform, is a comprehensive cybersecurity solution that provides real-time analysis of security event logs and other telemetry data from various sources within an organization's IT infrastructure. The primary goal of a SIEM is to monitor and manage security-related events, detect threats, and respond to security incidents promptly.

One of the challenges of SIEMs and other security tools is that the data these tools analyze are growing by leaps and bounds - as much as 35%-40% a year for some organizations. With all that data to analyze, meaningful insights may be buried among noisy data that swamps SIEM indices and slows the work of SecOps teams.  In this blog, we will discuss why an Observability Pipeline is a must-have for ensuring security across your enterprise.

What is an Observability Pipeline and What Does it Have to Do with Security

An Observability Pipeline is a sophisticated system designed to manage, optimize, and analyze telemetry data (like logs and  metrics) from various sources. It helps Security and DevOps teams efficiently parse, route, and enrich data, enabling them to make informed decisions, improve system performance, and maintain security within budgetary constraints. Observo.ai elevates this concept with AI-driven enhancements that significantly reduce costs and improve operational efficiency.

The disconnect for some people is that Observability is often viewed as the purview of DevOps only and not applicable to Security teams. The reality, however, is that observability is about understanding how your environment is behaving whether that's from a security perspective or a performance, availability, or storage perspective. 

DevOps and Security teams are asking different questions of their telemetry data and have differing goals, but the mechanism of how that data gets into analytical tools is often very similar. If it makes more sense for you to think of a term like telemetry data pipeline, that’s what we mean when we use the broader category of Observability Pipeline.

Why are Observability or Telemetry Pipelines So Important for Security

Comprehensive security means looking at all of the data that matters. This includes data from a wide range of sources both internally and externally. Because most SIEM tools charge by data, many security teams feel they have to be very stingy with what data they can afford to analyze. Omitting data sources from our security practice introduces blind spots that can end up costing a lot more than what you may be saving. If security teams can reduce the volume of a new data source and their existing data by as much as 80%, they can afford to add all of the data they need to ensure the highest standard of security.

At the same time, all security data is growing at 25-40% a year. For most organizations, it doubles in fewer than 3 years - about the same time most SIEM contracts renew. By controlling the growth of this data, organizations won’t get an unpleasant surprise every few years when it comes time to renew. Observo.ai also makes it easy to change or add new SIEMs by transforming the data you have and sending it to any mix of tools that make sense. No longer does changing tools require deploying agents to collect the same data in a different proprietary format. 

Especially verbose security data can threaten daily ingest limits. For some tools, exceeding these limits can bring stiff fees. Manually turning off data sets to avoid these overages or random sampling can help control the volume but it introduces blind spots and you never know if the alert that matters most was sampled out of your data set.

This massive and growing dataset makes security much harder. False positive rates are high and data correlation isn’t accurate enough to know what alerts are the most urgent to investigate. This makes detecting a security breach very difficult - according to a report by IBM in 2021, it can take as long as 212 days to identify a breach and 75 additional days to contain it. Concrete processes and tools to control the number of alerts and prioritize them can speed this process dramatically. 

What Should Security Teams Expect by Using an AI-Powered Observability Pipeline 

Data Optimization and Reduction: We found that only about 20% of your log data has value. Observo.ai uses AI and machine learning techniques to right-size data without having to set static rules that require the user to be an expert on their data and what is useful or not. Observo.ai optimizes data by creating intelligent groupings of data that can reduce noise by 80% or more. Observo’s smart summarizer has optimization transforms specifically built for each data type you want to analyze including VPC Flow logs, Firewall logs, OTEL, OS, CDN, AD, SSO, DNS, Application logs and others. These deep learning techniques are constantly learning and looking for improvements to recommend further optimization. As your data changes, so do the optimizations. This steep reduction in data sent to your SIEM tools keeps your SIEM index lean and filled with only the most important data - dramatically cutting storage and computing expenses. This allows most security teams to reduce the total cost of their SIEM by 50% or more.

Smart Routing: Observo.ai transforms data from any source to any destination - allowing you to choose what types of data need to be analyzed by the most expensive tools and which can be routed to a more cost-effective tool. Gone are the days of collecting data in different formats for every tool. With Observo.ai, you can collect data once and route it to the right tool or storage destination in whatever format is required. Our AI-based models automate this so you don’t need an expert to establish a long list of rules and you can be optimized and running in under an hour. Avoid vendor lock-in and maintain the flexibility to route data to where it holds the most value

Anomaly Detection: The Observo.ai pipeline learns what is normal for any given data type. Observo’s AI models detect anomalies and assign “sentiment” based on pattern recognition. Sentiment dashboards add valuable insights and help reduce alert fatigue by helping Security and DevOps teams discern meaningful alerts from run-of-the-mill items that don’t require immediate attention. Observo.ai can integrate with common alert/ticketing systems like ServiceNow, PagerDuty, and Jira for real-time alerting. By focusing on the right signals and tuning out the noise, Observo.ai can speed the resolution of critical incidents 40% faster.

Data Enrichment: Observo.ai enriches data to add context. Observo.ai can also enrich logs with third party data like Geo-IP and threat intel to make data more actionable. Adding the right data can significantly speed up queries in downstream tools and reduce the compute toll on indexing engines.

Searchable, Low-cost Data Lake: Observo.ai recommends taking a copy of full-fidelity data and routing it to inexpensive cloud object storage like AWS S3, Azure Blob, or Google Storage. Observo.ai transforms log data into Parquet format, a highly compressible data format that allows search using natural language queries through tools like Athena. Storing data in Parquet format in cloud object storage can cost as little as 1-2% of storing it in block storage attached to your SIEM index. This allows customers to keep more data for longer periods, which bolsters their ability to investigate incidents like breaches, which often occur months, if not years before being discovered. It also helps them comply with log retention standards and regulations which for some industries require storing logs for up to seven years. Observo.ai can “rehydrate” this data at any time and route it back to your SIEM should you need to investigate this data on demand.

Retain more data, spend less money, and be more flexible.

Compliance and Sensitive Data Discovery: Observo.ai detects sensitive data allowing you to secure it through obfuscation or hashing. Unlike static tools that set rules for what is sensitive data, Observo’s ML models use pattern recognition to discover all sensitive data, even if it’s in an unexpected field or metric. Observo.ai automates compliance with privacy regulations like GDPR, CCPA, and PCI. Observo.ai helps you keep all sensitive data safe and protected. Earn customers' trust by securing all PII to stay in compliance.

Conclusion

Observability Pipelines aren’t just for Observability and DevOps data. The same techniques used to optimize and route data to logging tools can be used for security data. If the name bothers you, think of them as Telemetry Data Pipelines or even Security Data Pipelines. Whatever you call them, they can have a huge positive impact on maximizing your security while minimizing risk. They can reduce data by 80% or more and help you cut the total cost of operating your SIEM by 50% or more. They help you optimize and route security telemetry data more flexibly to whatever tool makes the most sense. And, they free security teams from mundane, manual workarounds, prioritize anomalies, and eliminate alert fatigue which can speed incident resolution by over 40%.

To learn more, read our white paper titled 'Elevating Observability: Intelligent AI-Powered Pipelines'— just pretend it's called 'Elevating Security...'