Splunk Observability Cloud integrates with existing systems through multiple native connection methods, including APIs, agents, SDKs, and direct connectors. The platform supports both modern cloud environments and legacy infrastructure, using standardised protocols and secure data collection methods. Integration complexity varies by system type, but most organisations can establish comprehensive observability coverage across their entire technology stack within weeks.
What is Splunk Observability Cloud and how does it connect to existing infrastructure?
Splunk Observability Cloud is a comprehensive infrastructure observability platform that provides real-time visibility across applications, infrastructure, and business processes. The platform connects to existing systems through a distributed architecture that collects metrics, traces, and logs from multiple sources simultaneously.
The platform’s core architecture relies on lightweight data collectors and agents that integrate directly with your infrastructure components. These collectors establish secure connections to databases, servers, containers, and cloud services without requiring significant changes to existing systems. The platform supports more than 300 pre-built integrations covering major technology stacks, from traditional on-premises infrastructure to modern containerised environments.
Connection methods include real-time streaming for high-volume data sources and batch processing for less critical systems. The platform automatically discovers new services and infrastructure components, making it particularly effective for dynamic environments where resources frequently change. This discovery capability ensures comprehensive coverage as your infrastructure evolves.
What integration methods does Splunk Observability Cloud support for different system types?
Splunk Observability Cloud supports four primary integration approaches: agent-based collection, REST APIs, software development kits (SDKs), and direct service connectors. Each method addresses specific infrastructure types and data collection requirements.
Agent-based integration involves installing lightweight collectors on servers, containers, or virtual machines. These agents automatically gather system metrics, application performance data, and infrastructure health indicators. The agents require minimal system resources and can be deployed through configuration management tools or container orchestration platforms.
REST API integration enables custom applications and services to send telemetry data directly to the platform. This method works particularly well for proprietary applications or systems that need custom instrumentation. The APIs support both real-time streaming and batch data submission.
SDK integration allows developers to embed observability capabilities directly into applications during development. Available for major programming languages, including Java, Python, Node.js, and .NET, these SDKs automatically capture application traces, metrics, and custom business events.
Direct service connectors provide preconfigured integrations for popular platforms such as AWS, Azure, Google Cloud, Kubernetes, and major databases. These connectors often require only authentication credentials and basic configuration to begin collecting comprehensive telemetry data.
How do you integrate Splunk Observability Cloud with cloud platforms and containerised environments?
Cloud platform integration typically involves configuring service-specific connectors and installing platform agents within your cloud environment. Major cloud providers offer native integration paths that minimise configuration complexity and ensure comprehensive coverage.
For AWS integration, you configure the AWS integration through IAM roles and CloudFormation templates. The process involves creating appropriate permissions, installing the Smart Agent on EC2 instances, and enabling CloudWatch metrics forwarding. Container environments require the Splunk OpenTelemetry Collector deployed as a DaemonSet in Kubernetes clusters.
Azure integration uses similar principles with Azure Active Directory authentication and Resource Manager templates. The platform connects to Azure Monitor APIs and deploys agents across virtual machines and container instances. Application Insights data can be forwarded directly to Splunk Observability Cloud.
Google Cloud integration leverages service accounts and Cloud Deployment Manager. The platform collects data from Stackdriver APIs while agents monitor Compute Engine instances and Google Kubernetes Engine clusters.
Kubernetes environments require special consideration for dynamic container discovery. The OpenTelemetry Collector automatically discovers new pods and services, applying appropriate monitoring configurations based on labels and annotations. This ensures new deployments receive immediate observability coverage without manual intervention.
What are the common challenges when integrating Splunk Observability Cloud with legacy systems?
Legacy system integration presents three primary challenges: limited API availability, outdated communication protocols, and restricted system access for agent installation. These obstacles require creative approaches and often involve intermediate data collection strategies.
Mainframe and proprietary systems often lack modern APIs or agent support. Solutions include deploying network-based monitoring for infrastructure metrics and using log forwarding from existing monitoring tools. Many organisations implement a hybrid approach in which legacy systems send data to intermediate collection points that then forward information to Splunk Observability Cloud.
Older applications may not support modern instrumentation methods. In these cases, synthetic monitoring and external health checks provide visibility into system availability and performance. Database monitoring can often be achieved through existing database management tools that support metric export.
Security restrictions in legacy environments may prevent direct agent installation. Alternative approaches include agentless monitoring through SNMP, WMI queries, or log file analysis. These methods provide essential visibility while respecting existing security boundaries.
Data format compatibility presents another common challenge. Legacy systems may produce logs or metrics in proprietary formats requiring transformation before ingestion. The platform’s data transformation capabilities can normalise this information during the collection process.
How do you maintain data security and compliance during Splunk Observability Cloud integration?
Data security during integration requires implementing encryption in transit and at rest, proper access controls, and compliance-aware data handling practices. All data transmission to Splunk Observability Cloud uses TLS encryption with certificate validation.
Access control begins with implementing least-privilege principles for integration credentials. Service accounts used for data collection should have read-only permissions limited to necessary metrics and logs. Multi-factor authentication should be required for all administrative access to integration configurations.
Data classification and retention policies must be established before integration begins. Sensitive information should be filtered or masked during collection to prevent accidental exposure. The platform supports data transformation rules that can remove or obfuscate sensitive data before storage.
Compliance requirements vary by industry and region. GDPR compliance may require specific data handling procedures and retention limits. Healthcare organisations need HIPAA-compliant data processing, while financial services require adherence to regulations such as PCI DSS. The platform provides compliance-ready configurations for major regulatory frameworks.
Network security considerations include implementing proper firewall rules and network segmentation. Integration traffic should flow through designated network paths with appropriate monitoring and logging. VPN or private network connections may be required for highly sensitive environments.
Regular security audits of integration configurations help identify potential vulnerabilities or compliance gaps. This includes reviewing access permissions, data handling procedures, and encryption implementations to ensure they meet current security standards and regulatory requirements.
Expert Splunk Observability Cloud Integration Support
WeAre is a leading Splunk consulting partner specialising in observability solutions and complex system integrations. Our team of certified Splunk experts helps organisations successfully implement and optimise Splunk Observability Cloud across diverse infrastructure environments, from legacy systems to modern cloud-native architectures.
Whether you’re planning your first observability implementation or looking to expand existing monitoring capabilities, our experienced consultants provide end-to-end support including integration planning, security configuration, and ongoing optimisation.
Ready to transform your infrastructure observability? Contact our Splunk specialists for a consultation, or explore our comprehensive Observointi ja Data offerings to discover how we can accelerate your observability journey.