Splunk’s Data Platform Drives Enterprise Resilience

For many enterprises, the crux of digital transformation is in using the agility, scalability, and cost-efficiency offered by cloud technology. But, despite the benefits offered by the cloud, the feasibility of a full transition to the cloud varies among organizations and is influenced by a multitude of factors including concerns about the upkeep and consistent updating of data platform software for security and compliance.

While most organizations operate within a multi-cloud or hybrid cloud framework, the underlying systems crucial for ensuring success have lagged in development. This highlights the shift towards maximizing the full potential of data. Organizations are recognizing that their traditional methods of monitoring and resolving issues are inadequate for the increasingly intricate cloud environment and that they need to reevaluate their management strategies across diverse environments and establish a robust data infrastructure as a foundation for progress.

As companies rely more on data and data teams for digital transformation and cloud utilization, the significance of building a unified IT infrastructure amplifies. Within this framework, modern monitoring, investigation, and observability solutions are crucial for creating a connected enterprise while sidestepping unnecessary complications. Splunk assists IT and DevOps teams in sustaining consistent optimal business performance, minimizing downtime, and delivering outstanding digital experiences in the data-driven era.

Turning data into doing

While Splunk’s focus is primarily on security, cybersecurity, security monitoring, incident resolution, compliance, and threat identification, it also addresses high-performance needs for data and analytics capabilities, extending its capabilities to incorporate data from cloud storage providers beyond traditional sources.

The Splunk Cloud Platform plays a crucial role in assisting organizations in achieving stability across their ecosystems, covering security, infrastructure, and application aspects. With visibility into an enterprise’s digital systems, Splunk Cloud Platform facilitates seamless data management at scale, enabling efficient integration and utilization across diverse applications. The Splunk Cloud Platform is an extensible data platform that unifies security, full-stack observability, custom applications, and data on a flexible platform for the hybrid world. The platform leverages various data sources, including SAP, to consolidate information and offer customers a unified platform experience. As Azmir Mohamed, Director, Product Management at Splunk says, “Over the last few years, we have observed the substantial growth of our cloud services, transitioning from predominantly on-premises to a robust hybrid cloud model. From data accessibility, business insights, and usability and collaboration, the Splunk Cloud Platform reflects our dedication to meeting diverse customer needs and maximizing flexibility.”

Customer-driven innovation

At the core of Splunk’s offerings are robust data management capabilities, facilitating seamless data ingestion, routing, filtering, and enrichment. Splunk’s scalable index enables immediate data searchability without the need for complex Extract, Transform, and Load (ELT) processes, supporting over a thousand log formats for comprehensive system visibility. The platform further distinguishes itself with customizable visualization options, including out-of-the-box visualizations and highly adaptable monitoring dashboards suitable for both technical and executive audiences.

Innovations like Federated Analytics and AI-driven capabilities enhance Splunk’s offerings, enabling users to search outside of the Splunk environment and leverage advanced machine learning techniques for data analysis. Central to Splunk’s approach is its commitment to enabling practitioners and organizations to harness diverse data types effectively, encapsulated in the “MELT” (Metrics, Events, Logs, and Traces) framework.

Addressing the challenge of data volume and cost, Splunk has evolved its pricing model to provide greater flexibility and efficiency, ensuring that low-value data does not burden high-cost indexes. This approach aligns with Splunk’s commitment to meeting customer needs while optimizing performance and cost-effectiveness. Additionally, Splunk emphasizes the importance of customer partnership, fostering empathy, and collaboration to deliver tailored solutions. This bidirectional engagement ensures that Splunk remains responsive to evolving customer requirements, further cementing its position as a trusted partner in data analytics and management.

Human-in-the-loop AI for digital resilience

Splunk’s approach to AI is characterized by a focus on domain-specific applications, distinguishing itself from more generalized AI platforms, by prioritizing excellence in security and observability domains. This strategic direction capitalizes on Splunk’s extensive access to security and observability data, enabling the development of specialized models tailored to specific use cases.

Splunk employs both generative AI and traditional powerful machine learning capabilities within its Splunk AI capability set across a variety of product offerings. The company unveiled its latest generative AI innovation, the Splunk AI Assistant preview, at its user conference in 2023, and has been a leader in machine learning for years, offering customizable toolkits and embedding AI functionalities into its products, notably within IT Service Intelligence, an AIOps offering. The focus is on enhancing digital resilience by enhancing detection, investigation, and response capabilities across both security and observability domains. While the company acknowledges the potential of AI to bolster human decision-making by boosting speed and efficacy, it also recognizes its limitations, indicating that human involvement remains indispensable in decision-making processes.

Splunk offers two ways of using AI/ML: using out-of-the-box features integrated into existing product workflows, or through customization. ML is embedded into the Splunk platform within Splunk Cloud Platform and Splunk Enterprise and enables users to detect anomalies, generate forecasts, predict, and group data into clusters to identify misconfigured services.

Additionally, Splunk AI Assistant uses generative AI to provide an interactive chat experience and enables users to author Splunk Processing Language (SPL) using natural language.

Mohamed adds, “The Splunk AI Assistant aims to streamline the query writing process, particularly benefiting security analysts and IT professionals in maximizing Splunk’s value efficiently. This dual approach caters to different user needs: while generative AI focuses on simplifying and enhancing user experiences, traditional machine learning empowers technically skilled practitioners to build custom models based on their data within Splunk. These initiatives reflect a two-fold strategy aimed at improving user accessibility and data analysis capabilities.” Mohamed further emphasizes the significance of understanding user personas, noting the transformative potential of the AI assistant in reducing the learning curve associated with Splunk’s query language (SPL) for end-users. This is also highlighted in Splunk’s efforts to address data overload and noise through automated filtering mechanisms and the use of machine learning to enhance data processing efficiency.

A level playing field – Splunk in the SAP Ecosystem

Within the SAP ecosystem, Splunk serves as a critical data source, offering various tools and applications to enhance visibility and data management. The Splunk     base app marketplace offers a plethora of applications tailored to different user perspectives. These applications fall into two main categories: technical add-ons, simplifying data ingestion by standardizing formats, and dashboard-centric apps for data analysis. Splunk contributes its own apps to broaden the ecosystem, alongside offerings from third-party developers and independent software vendors.

The collaboration between SAP and Splunk aims to simplify monitoring tasks for joint customers, ensuring optimal performance and facilitating seamless integration. Splunk also offers integration-related technical add-ons and dedicated SAP apps compatible with both Splunk Cloud Platform and Splunk Enterprise. These tools provide comprehensive monitoring and analysis capabilities for SAP operations, complemented by Splunk’s IT Service Intelligence product.

While Splunk boasts general key differentiators at the platform level, such as its flexible offering model allowing for on-premises, cloud-based, or hybrid deployments across different cloud environments, there are also specific capabilities worth highlighting. One notable application within this ecosystem is SAP PowerConnect, available on Splunk     base, which facilitates visibility into SAP data environments, particularly favored by large-scale enterprises. SAP PowerConnect consists of two primary components: an SAP add-on that is installed within an SAP environment and the Splunk app. While the PowerConnect Add-On is SAP certified software that installs into NetWeaver ABAP, S/4 HANA, NetWeaver Java, SAP Cloud Platform or TomCat Java based SAP systems and uploads events directly to Splunk Enterprise or Splunk Cloud in real time, The Splunk SAP PowerConnect app provides visualizing, monitoring, and managing SAP systems functionalities.

Expanding portfolio beyond monitoring and observability

While initially focused on cloud-native environments and API-driven systems, observability has evolved to encompass broader technological landscapes. Larger enterprises, particularly, face the challenge of managing both cloud-native applications and legacy systems, underscoring the need for a unified observability strategy to ensure seamless business operations and performance enhancement. Mohamed highlights, “Looking ahead, there is a concerted effort towards unification, recognizing the evolving needs of diverse user personas, from cloud-native startups to more traditional enterprises. This involves bi-directional integration efforts, facilitating seamless access to insights generated by advanced observability products within the broader platform ecosystem.”

Splunk recently expanded its cloud services into Microsoft Azure data centers, alongside existing deployments in AWS and Google Cloud. This expansion into Azure marks a pivotal focus area for the company moving forward. Moreover, advancements in AI capabilities with a particular emphasis on compliance sophistication have been another focus for Splunk. Existing offerings such as Splunk App for PCI Compliance and HIPAA compliance have been augmented with initiatives targeting the public sector, notably with the introduction of FedRAMP (Federal Risk and Authorization Management Program) compliance, catering to federal agencies and the intelligence community.

Federated analytics and search continues to emerge as another key focus area, building upon the 2023 release of Federated search for Amazon S3. This encompasses not only search functionalities but also robust data management and routing capabilities, particularly catering to real-time data acquisition and processing, including investments in edge computing capabilities. Additionally, efforts are underway to unify observability functionalities across the platform, bridging metrics, traces, logs, and events. The introduction of Log Observer Connect allows observability practitioners to leverage the powerful Splunk Platform’s logging in combination with real-time metrics and traces in Splunk Observability Cloud for faster in-context troubleshooting.

What it means for SAPinsiders

Proactive issue prevention: Gain comprehensive visibility into all digital systems to detect and address incidents before they escalate, ensuring minimal impact on customers. Automate response actions upon alert detection to save valuable time and resources.

Swift incident recovery: Streamlining and standardizing workflows enable faster detection and response times. By restoring services promptly, organizations can enhance customer satisfaction and minimize downtime, ensuring uninterrupted operations.

Integrate AI into workflows: Incorporate AI tightly into security and observability workflows to address organization’s specific use cases effectively. By leveraging AI technologies within the workflows, organizations can enhance threat detection, incident response, and overall visibility across your systems.

Agile adaptation: Whether deploying new code, updating legacy infrastructure, or exploring innovative business models, leverage full visibility into the potential impacts of changes on the digital environment.

Conclusion

Organizations are recognizing that their traditional methods of monitoring and resolving issues are inadequate for the increasingly intricate cloud environment and that they need to reevaluate their management strategies across diverse environments and establish a robust data infrastructure as a foundation for progress. Proactive issue prevention, swift incident recovery and agile adaptation, made more efficient through integrated AI are crucial for creating a digitally resilient enterprise while sidestepping unnecessary complications. Splunk assists IT and DevOps teams in sustaining consistent optimal business performance, minimizing downtime, and delivering outstanding digital experiences in the data-driven era.