C1000-189 Questions and Answers

Instana uses Sensors as specialized software components embedded within its agents to monitor and extract telemetry from various supported technologies. The verified documentation states: "Sensors are built-in modules that detect, identify, and monitor specific technologies such as databases, servers, run-times, and messaging systems." These components ensure that the agent collects targeted metrics, events, and traces optimized for individual stacks like MySQL, Kafka, or Java. When deployed, the Instana agent automatically discovers technologies running in the environment and loads corresponding Sensors dynamically, requiring minimal user configuration. Tracers handle transaction propagation, Profiling covers code-level performance, and Service is a higher abstraction in application topology—not individual monitoring logic. The Sensor concept remains core to Instana’s automatic discovery and observability architecture as validated in IBM’s architectural reference sections.

IBM Instana integrates natively with Prometheus to unify metric ingestion without disrupting existing telemetry setups. The configuration parameter remote_write enables this linkage. The official documentation states: "The remote_write configuration enables Prometheus to send data to Instana, where those metrics are displayed either as Prometheus entities or merged into process custom metrics." Instead of storing them only within Prometheus, Instana pulls remote_write relay feeds to create comprehensive, unified metrics views in its dashboard. This approach avoids duplicate monitoring systems and allows alerting across both Prometheus and Instana data seamlessly. The parameter does not configure outbound writing by Instana back into Prometheus—data always flows from Prometheus to Instana in this architecture. This integration respects Prometheus scraping principles yet centralizes analysis within Instana, achieving correlation between imported numerical time-series values and native metrics at the application or process layer.

Instana traces and analyzes every request. Services and endpoints are automatically discovered, and relationships between services, endpoints, and your infrastructure are autocorrelated and stored in our Dynamic Graph.

Based on the data that is collected from tracers and sensors, KPIs are calculated for calls, latency, and erroneous calls. KPIs help you discover the health of every individual service and then the health of your entire infrastructure.

Services are a part of application monitoring and provide a logical view of your system. Services are derived from infrastructure entities such as hosts, containers, and processes. Incoming calls are correlated to infrastructure entities and enriched with infrastructure data; for example, the Kubernetes pod label or SpringBoot application name. After this infrastructure-linking processing step, a service mapping step maps the enriched calls to generate a service name per call based on a set of rules. Instana comes with an extensive set of predefined rules to generate the best possible service name for you automatically. To fine-tune the service mapping, you can create your own custom rules, see customize service mapping.

Per IBM Instana's security documentation, management of two-factor authentication (2FA) is controlled directly via administrative functions in the web UI. The guidance reads: "Administrators can remove a user’s 2FA association by navigating to Settings > Users, choosing the user, and using the remove or reset 2FA option in the UI." This workflow is safe, auditable, and leaves a traceable event in the audit log, satisfying enterprise security policy requirements. Direct API or CLI deletion of 2FA is not the recommended (or documented) method for Instana-managed users, and database-level manipulation (D) is unsupported as it risks data corruption. The UI approach is verified for both on-premises and SaaS installations.

IBM’s product migration matrix for Instana confirms strict usage boundaries between different self-hosted editions. The documentation clarifies: "Instana Self-Hosted Standard Edition does not support migration of data from the Self-Hosted Classic Edition." Each edition uses different architectural components, storage formats, and telemetry databases. Therefore, upgrading from Classic to Standard Edition requires a fresh install, without direct movement of monitoring history or historical configuration. Upgrades are only supported within the same product branch, ensuring compatibility and stability. Attempting migration from the Classic Edition is unsupported and risks operational deviation. Standard Edition can be newly installed but not upgraded from the Classic base, as per IBM’s verified change and upgrade path guidance.

IBM Instana supports direct monitoring ofAWS Lambdavia serverless-specific agents that bridge trace, metric, and log data between Lambda executions and the Instana backend. The documentation specifies: "Instana's serverless agents enable tracing and monitoring of AWS Lambda functions—including cold start events, performance, and error metrics—correlating invocation traces with upstream and downstream services." Lambda is the only public cloud-native serverless runtime natively and fully integrated with Instana’s instrumentation and tracing. Azure Redis Cache, AWS Kinesis, and AWS SQS are data stores or message services, not supported for full serverless agent instrumentation (though they may be monitored via associated infrastructure and integration sensors). Instana’s Lambda agent is deployed as a Lambda layer or sidecar, delivering first-class observability for serverless architectures.

IBM Instana Observability supports deploying and managing components like Synthetic PoPs and monitoring collectors through Helm charts in Kubernetes environments. The official documentation explicitly states: "To customize the configuration of Instana Synthetics deployments using Helm, specify values either directly with the --set flag or via a configuration file passed with the -f flag during the Helm install or upgrade command." This approach aligns with Kubernetes best practices by maintaining immutable packaged charts while permitting flexible, environment-specific configurations through overrides. The --set parameter allows single-line value changes from the command line (for example, setting API keys or namespace values), whereas using a YAML file provides structure for multi-parameter updates and offers version control capability. IBM warns against manual edits in default Helm charts or direct environment-based configurations as these can be overwritten during automation or chart upgrades. Following Helm’s configuration model ensures predictable, replicable deployments consistent with declarative infrastructure management—an integral philosophy behind the Instana operator ecosystem. The combination of -f and --set enables a scalable and consistent way to customize Synthetics installation across clusters.

The Instana Operator is the officially recommended and supported method for deploying the Instana host agent on Kubernetes clusters. The IBM Instana Observability documentation states, "The recommended method to install the Instana agent on Kubernetes clusters is via the Instana Operator, which uses Custom Resources to simplify lifecycle management." The Operator pattern in Kubernetes automates not just installation, but also upgrades, configuration, and management of agents across the entire cluster. This ensures security and reliability because the Operator reacts to cluster changes and can self-heal agent deployments. Other install options such as Homebrew, direct binary, or RPM are for traditional VM or bare-metal hosts—not for orchestrated container environments like Kubernetes. Only with the Operator does Instana support automated scaling, configuration through CRDs, and native Kubernetes best practices. Helm charts are also often involved in configuring the Operator, further streamlining agents’ deployment in public, private, or hybrid cloud clusters.

According to IBM Instana Observability documentation, the Infrastructure map’s primary goal is to present a real-time, interactive graphical overview of monitored hosts, nodes, VMs, and cloud instances, organized by zones or clusters. The verified statement is: "The Infrastructure map provides a dynamic, interactive view of all monitored systems—grouping resources by logical or physical zones and delivering actionable context for troubleshooting and planning." Users can zoom, filter, and select entities to drill into system health and configuration, identify relationships, and pinpoint issues in geographic or topological layouts. Static images are not produced; instead, the map updates in real-time as agents detect new hosts, containers, or state changes, reflecting additions, removals, or migrations instantly. Option D describes the Service map, which visualizes application and service dependencies rather than the underlying infrastructure. Thus, C best matches the IBM documented description for Infrastructure map functionality.

Instana Smart Alerts provide intelligent, context-aware alerting capabilities. In Advanced Mode, administrators can choose between two distinct threshold types: Static and Adaptive. The IBM Instana documentation details: "Advanced Mode supports both static and adaptive thresholds, letting users define explicit limit values or rely on adaptive baselines derived from historical data." Static thresholds are fixed, user-defined values best suited for predictable workloads or regulatory uptime scenarios. Adaptive thresholds use machine learning on time-series historical behavior to automatically adjust boundaries when traffic patterns or operating baselines change. This significantly reduces false positives and ensures that alerts reflect true anomalies rather than normal variance. Both threshold types can trigger multi-level alerts and integrate with escalation policies. Static measures remain critical for SLIs requiring consistent control, while adaptive techniques optimize monitoring of microservices under fluctuating loads. IBM emphasizes combining these in practice to balance detected sensitivity across mixed systems, leveraging AI-driven dynamic configurations in adaptive mode as a key differentiator in its observability platform.

IBM Instana agents use HTTPS, the industry standard secure protocol, to transmit telemetry data to Instana’s backend servers or clusters. Instana documentation says: "All agent-to-backend traffic is encrypted and transmitted via HTTPS, meeting data confidentiality and compliance requirements." The use of HTTPS prevents unauthorized data interception by using strong TLS encryption on every packet exchanged between agent and backend, regardless of whether the deployment is on-premises or SaaS. FTP, SSH, and NFS are protocols for file transfer, system access, or storage mounting but are never used for telemetry transmission in Instana's architecture. Secure HTTP is essential for privacy by design, is policy-enforced, and supports audit-friendly observability in all supported Instana versions per IBM standards.

According to IBM Instana's integration documentation, webhook notifications support Basic Authentication by embedding the username and password into the URL as part of the standard format (https://user:password@hostname/path). The exact extract from IBM states: "For webhooks requiring basic authentication, username and password must be specified by prepending these values to the webhook hostname in the URL." This approach is supported by most HTTP libraries and ensures ease of integration with third-party endpoints. Instana also allows other advanced authentication mechanisms for webhooks, but this is the documented approach for standard Basic Auth scenarios. Additional header configuration (B) is possible but not required for basic authentication, and option D is incorrect as Basic Auth is explicitly supported (and documented). Limiting to only the Authorization header (C) oversimplifies the supported authentication workflows.

IBM Instana Observability agents useLog4j2as their primary logging framework for system activity, sensor status, and diagnostic output. The documentation confirms: "The default logging framework for Instana agents is Apache Log4j2, providing structured log output, multi-level verbosity, and integration with most enterprise log aggregation environments." Log4j2 is a standard for Java-based environments, supporting dynamic log rotation, filtering, and formatting. Instana agent log files follow Log4j2 conventions, enabling easy parsing by SIEM tools and adapters. Serilog (A) is a .NET framework, not used by Instana agents. JSNLog (C) is for JavaScript applications, while Loggly (D) is a SaaS log analytics platform. Log4j2’s mature design lets administrators tune performance, verbosity, and log destinations in rich deployment scenarios, directly aligning with best practices in Instana’s monitoring ecosystem. This was reconfirmed in agent reference guides and environment setup sections.