Endpoints are the user devices that are used to access services, applications, or products. All external devices connected to the IT infrastructure need to be authenticated to boost security and usually, a series of checkpoints and protocols are set for a device that wants to connect to the IT infrastructure.  If the endpoint cannot match the necessary criteria, it cannot be allowed to connect due to security issues.

So far, businesses have been using EPPs (Endpoint Protection Platforms) to ensure that only authenticated devices are connected to the IT infrastructure. However, traditional EPPs are unable to cope up with increasing complexity. The sudden surge in remote working coupled with the rise of AI data analytics monitoring tools has forced businesses to adopt an AI strategy. Some firms take an extra step and implement round-the-clock monitoring of endpoints. With many system administrators,  you can ensure round-the-clock endpoint monitoring. However, hiring too many system administrators also comes with cost hassles.

AI for application monitoring can aid businesses in reducing manual labor for endpoint monitoring. With a reliable endpoint monitoring solution, you can authenticate all files, applications, and packets that connect to your IT infrastructure via an external device.

The challenges faced by businesses in managing end-users

You cannot wait for a threat to occur from one of your endpoints. Treating a threat after it has occurred will have a severe impact on service availability. AI for application monitoring can help organizations in taking proactive steps for ensuring endpoint security.

Remote working means employees will connect to our environment from remote areas. In such cases authenticating the user and device identity and managing productivity becomes a challenge.

Many mobile devices connect to an organization’s infrastructure for interacting with the products/services. Mobile devices are such endpoints that spend much time being offline. With traditional endpoint protection platforms, organizations cannot manage threat detection when the endpoint is offline.

Lack of automatic alerts via endpoint monitoring and low observability forces organizations to use real-time user monitoring tools that generate automatic alerts.

Why use AI for endpoint monitoring?

An AIOps based monitoring platform will ensure round-the-clock security with its proactive monitoring approach. All layers that are involved with endpoints are monitored via an AIOps based analytics platform. Different layers associated with endpoints are network devices, APIs, databases, servers, and native applications. The pros of using AIOps for endpoint monitoring are as follows:

• AIOps based real-time user monitoring tools will check the authenticity of an endpoint before allowing it to connect to your organization’s internal network.
• Usually, AIOps based platforms take biometric input from users at frequent intervals to ensure authenticity.
• An AIOps based analytics platform will also collect information about usage time. It determines how much time an endpoint is connected to your organization’s internal network. For example, if the endpoint is a laptop, then an AIOps platform will analyze the mouse and keyboard usage.
• An AI automated root cause analysis solution can help you find the endpoint easily from where a threat has emerged.
• An AIOps based platform will analyze the user behavior and report the endpoint that shows anomalous behavior.
• You can learn about processes or applications operating at the endpoint with AIOps based analytics platform.

Healthy practices for endpoint monitoring

1. Blocking outdated applications

It is a challenge for businesses to launch an update/patch and ensure all endpoints have installed it. You need to identify those endpoints that are still using outdated or insecure versions.IT automation with AI can aid in ensuring all endpoints are using the latest version of the application. Many businesses roll out forced updates to boost their endpoint security.

2. Compliance policies

You can define a device policy for the endpoints connected to your IT infrastructure. All the endpoints will have to prove compliance before getting access to your organization’s internal network.

3. Control endpoint interaction

You can control the endpoint behavior to boost security. For example, you can block USD usage for endpoints to make sure your content isn’t duplicated. You can also ask users to enter specific credentials like username and password to gain access to your organization’s internal network.

4. Resolve threats

Before a threat at any endpoint affects the IT infrastructure of your organization, you need to resolve it. Real-time user monitoring tools can aid in resolving threats before they affect the IT infrastructure.

Businesses are using AIOps based analytics platforms for gaining enhancing observability into endpoints. You can also adopt an AI strategy for boosting your endpoint monitoring and security. Start using AIOps and boost your endpoint security!