Infrastructure Monitoring and Observability Solution

Infrastructure monitoring is the process of tracking, measuring, and analyzing the performance, availability, and health of IT infrastructure components, including servers,  storage, databases, network, and other cloud resources. It helps IT teams detect issues early, maintain uptime, and ensure optimal performance for applications and business services.

Monitoring involves collecting predefined metrics and logs from servers, networks, storage, and applications to detect known issues and trigger alerts. It tells you that a problem exists, but often doesn’t provide the full context for why it happened.

Observability, on the other hand, is about understanding the internal state of systems based on the data they produce. By combining metrics, logs, traces, and events, observability enables IT teams to analyze, diagnose, and predict issues, even those that were previously unknown.

Agentless infrastructure monitoring collects performance and health data from servers, networks, storage, and applications without installing software agents on each device. Instead, it uses standard protocols and APIs, such as SNMP, WMI, SSH, REST, or cloud provider APIs, to pull metrics, logs, and status information remotely.

IT-Conductor leverages agentless monitoring to correlate infrastructure metrics with application and business process performance, providing end-to-end visibility and automated remediation across on-prem, cloud, and hybrid environments.

Effective alerting ensures your IT team responds to issues promptly without being overwhelmed by noise.

Here are some best practices that you can follow:

1. Define meaningful thresholds: Set thresholds based on historical performance and business impact rather than default values. For example, trigger alerts when CPU usage consistently exceeds 80% for 10 minutes, not on a single spike.

2. Use dynamic baselines and anomaly detection: Leverage automated tools to detect deviations from normal behavior instead of static thresholds.

3. Prioritize alerts: Categorize alerts by severity (critical, warning, informational) so your team can focus on high-impact issues first.

4. Correlate alerts across systems: Avoid alert storms by grouping related events across servers, networks, and applications.

5. Automate remediation where possible: Integrate alerts with automated actions, like restarting services or scaling resources, to reduce downtime.

6. Review and adjust regularly: Continuously analyze alert patterns to reduce false positives and improve effectiveness.

Securing monitoring data is critical to protect sensitive information and maintain compliance.

Best practices include:

1. Encryption in transit: Use protocols like TLS/SSL to encrypt all data transmitted between monitored systems, cloud services, and your monitoring platform.

2. Encryption at rest: Store metrics, logs, and traces in encrypted databases or storage systems using strong encryption standards (e.g., AES-256).

3. Access control and authentication: Restrict access to monitoring data with role-based access control (RBAC), multi-factor authentication (MFA), and secure API keys or service principals.

4. Audit and logging: Maintain logs of who accessed monitoring data and when, helping detect unauthorized access.

5. Secure network connections: Use VPNs or private endpoints when connecting to cloud monitoring APIs or hybrid environments.