Continuous Monitoring - definition & overview

Continuous monitoring is a technology and process that IT organizations implement to enable rapid detection of compliance issues and security risks within the IT infrastructure. Continuous monitoring is one of the most important tools available for enterprise IT organizations, empowering SecOps teams with real-time information from throughout public and hybrid cloud environments and supporting critical security processes like threat intelligence, forensics, root cause analysis, and incident response.

Continuous monitoring, sometimes referred to as ConMon or Continuous Control Monitoring (CCM) provides security and operations analysts with real-time feedback on the overall health of IT infrastructure, including networks and applications deployed in the cloud.

The goal of continuous monitoring and the reason that organizations implement continuous monitoring software solutions is to increase the visibility and transparency of network activity, especially suspicious network activity that could indicate a security breach, and to mitigate the risk of cyber attacks with a timely alert system that triggers a rapid incident response.

Continuous monitoring can also play a role in monitoring the operational performance of applications. A continuous monitoring software tool can help IT operations analysts detect application performance issues, identify their cause and implement a solution before the issue leads to unplanned application downtime and lost revenue.

IT organizations may also use continuous monitoring as a means of tracking user behavior, especially in the minutes and hours following a new application update. Continuous monitoring solutions can help IT operations teams determine whether the update had a positive or negative effect on user behavior and the overall customer experience.

Ultimately, the goal of continuous monitoring is to provide IT organizations with near-immediate feedback and insight into performance and interactions across the network, which helps drive operational, security and business performance.

Software vendors create robust and versatile solutions that enable IT organizations to effectively monitor network traffic, detect anomalies or suspicious patterns of activity and develop actionable insights. The implementation of a continuous monitoring software solution can be described in five basic steps:

1. System definition - The IT organization must determine the scope of its continuous monitoring deployment. Which systems are under the purview of the IT organization? Which systems should be subject to continuous monitoring?

2. Risk assessment - The IT organization should conduct a risk assessment of each asset it wishes to secure, categorizing assets based on the risk and potential impact of a data breach. Higher-risk assets will require more rigorous security controls, while low-risk assets may require none at all and could even serve as a "honeypot" –– a decoy system that hackers might target before they find something important.

3. Choosing and implementing security control applications - Once a risk assessment has been completed, the IT organization should determine what types of security controls will be applied to each IT asset. Security controls can include things like passwords and other forms of authentication, firewalls, antivirus software, intrusion detection systems (IDS) and encryption measures.

4. Software tool configuration - As the IT organization coordinates the desired security controls to protect key informational assets, it can begin to configure a continuous monitoring software tool to start capturing data from those security control applications. Continuous monitoring software tools incorporate a feature called log aggregation that collects log files from applications deployed on the network, including the security applications that are in place to protect information assets. These log files contain information about all events that take place within the application, including the detection of security threats and the measurement of key operational metrics.

5. Ongoing assessment - Collecting data from throughout the IT infrastructure is not the ultimate goal of continuous monitoring. With millions of data points generated and centralized each day through log aggregation, information must be assessed on an ongoing basis to determine whether there are any security, operational or business issues that require attention from a human analyst. Many IT organizations today are leveraging big data analytics technologies, including artificial intelligence and machine learning, to analyze large volumes of log data and detect trends, patterns or outliers that indicate abnormal network activity.

IT organizations that develop the capability to monitor their IT infrastructure and security controls in real-time can enjoy a significant competitive advantage, especially against competitors that are still doing batch analysis or periodic analysis of older data. The main benefits associated with continuous monitoring are:

• Increase visibility and transparency of the network
  Real-time monitoring gives SecOps teams a window of visibility into the inner workings of the IT infrastructure. The ability to aggregate, normalize and analyze data from throughout the network using automated processes ensures that important events and trends are not missed because of a lack of visibility into systems.

• Enable rapid incident response
  Continuous monitoring eliminates the time delay between when an IT incident first materializes and when it is reported to the incident response team, enabling a more timely response to security threats or operational issues. With access to real-time security intelligence, incident response teams can immediately work to minimize damage and restore systems when a breach occurs.

• Reduce system downtime
  The objective of IT operations is to maintain system uptime and performance. With continuous monitoring, ITOps can react more quickly to application performance issues and rectify errors before they lead to service outages that negatively impact customers.

• Drive business performance
  User behavior monitoring is a frequently overlooked benefit of continuous monitoring software tools. ITOps teams can measure user behavior on the network using event logs and use that information to optimize the customer experience and direct users to their desired tasks and activities more efficiently.

Sumo Logic's cloud-native platform is an ideal continuous monitoring solution for IT organizations that wish to enhance the security and operational performance of their cloud-based IT infrastructure and applications. Features like automated log aggregation, data analytics, and configurable alerts help IT SecOps teams automate key security monitoring processes, respond more quickly to security incidents and mitigate the risk of a costly data breach.

What role does continuous monitoring play in compliance with industry regulations and compliance standards?

Continuous monitoring ensures compliance with industry regulations and standards by providing real-time visibility into an organization's security posture. Organizations can promptly identify deviations from compliance requirements by continuously monitoring security controls and rapidly detecting and addressing potential threats or security incidents. This proactive approach helps organizations maintain continuous compliance, mitigate risks and demonstrate adherence to regulations.

What should I look for when evaluating a continuous monitoring solution?

A continuous monitoring solution should provide real-time visibility into security controls across the entire organization, identify security threats promptly, monitor for potential threats continuously, ensure compliance with security standards and regulations, offer vulnerability management capabilities, allow ongoing awareness of emerging threats and enhance the organization's security posture through proactive risk monitoring.

How does continuous monitoring use AI technology?

AI can analyze vast amounts of data in real-time to detect anomalies, suspicious activities and potential threats that may go unnoticed by traditional methods. Using machine learning algorithms, AI can help automate monitoring, reduce false positives and improve response times to security incidents.