Splunk Reviews & Pricing

Key Features

• Data Integration: Pull data from on-premise, cloud, streaming sources and machines. Include relational databases using Splunk DB, an add-on module. Splunk doesn’t support SQL databases otherwise.
• Device Diversity: Gather user and system data from personal and network devices, servers and IoT sensors. Access reports and dashboards on a web interface from iPads, TVs and phones.
• SPL: Search, filter and analyze data with a powerful query language. Boost adoption with natural language commands using Splunk AI.
• Interactive Dashboards: Create custom KPI displays using the dashboard editor. Click on visualizations to link to other dashboards, drill down and run new searches.
• Reporting: Understand data using statistics and create advanced reports using the existing BI tech stack. Calculate typical values in a dataset using averages and medians. Measure how each value differs from the mean and each other.

Splunk Enterprise

• Automate: Take advantage of AI and machine learning. Plan for unplanned demand spikes or downtime and identify fraud.
• Predict: Forecast trends by analyzing time-series data with the predict command. Train and deploy deep learning models on the ingested data. It works with Jupyter Notebooks, PyTorch and TensorFlow.
• Control Data: Transform data before it enters Splunk with Ingest Actions. Modify it as desired, choose where to send it and decide where to store it.

Splunk Observability

• Gather Data: Collect data using an event collector and a universal forwarder. Pull information about how users interact with the app, how different parts of the system are performing, and machine data using the OpenTelemetry Collector.
• Understand: See how users interact with your app and how code changes affect performance.
• Remediate: Detect issues using streaming data and root-cause analysis.

Approach to Common Challenges

• Data Integration: Unreliable connections and messy data management can ruin everything. Splunk provides readymade connections and tools to clean and transform data. It even takes care of it after its usefulness is over by archiving it.
• Data Quality Issues: Dirty data can result in unusable results. Splunk tackles this by monitoring quality with a dedicated console. Governance rules also act as gatekeepers for controlling access.
• Data Complexity: Splunk saves on data storage by archiving older data in low-cost locations, ensuring speed and affordability. Plus, it can search all data without moving it from the source, making complex analyses super fast.
• Data Storage: Data issues arise from the various types and also due to inefficient storage. Splunk has a powerful indexing engine that can scale with complex and high-speed data streams.
• Scalability: Lags when handling large volumes are the bane of enterprises. Splunk is built to scale on demand and has analytics maturity, thanks to machine learning. It deploys additional indexers and search heads when needed.

Cost of Ownership

• Ingest pricing depends on the amount of daily ingested data measured in GB/day. Enterprises with predictable data volumes might find it a good fit. However, data manipulation and analysis will incur additional charges.
• Workload pricing incurs charges for searches and analysis measured in Splunk Virtual Compute units. It’s suitable for organizations with fluctuating data needs, and the upside is that no data gets left behind.
• Entity-based pricing depends on the number of devices. It’s ideal for enterprises seeking security or IT service management.

Limitations

• Due to high CPU usage, it might not be able to handle complex queries without risking system slowdowns or even crashes.
• Extensive connectivity requires additional effort and customization.
• There’s a steep learning curve.

Training Resources

• Training: Access free courses and eBooks on the vendor’s website.
• Certification: The vendor conducts regular boot camps as part of Splunk University. Opt for a one-year basic subscription and follow it up by getting certified as a power user, cloud administrator or search expert.
• Use Cases: Read about the product in action with the Splunk blog.
• Documentation: Learn about system architecture, requirements, apps and services, tutorials and onboarding guides on the vendor’s website.
• Community: Ask and answer questions in online communities of Splunk students and users. Sign up to join user groups that meet online and in person to share tips, use cases and learnings.

FAQs

• It isn't a traditional SQL or NoSQL database but uses its proprietary indexing technology to store and analyze machine data.
• It uses SPL, not SQL, for querying.
• Unlike SQL databases that have pre-defined schemas, it designs schemas on the fly, enabling the ingestion of unstructured data.
• It stores data in a particular format for use cases, not in a traditional database.