Splunk - everything you need to know | FAQ edition

Splunk is a data analytics platform, a leading market solution for observability and SIEM tools. It allows companies to collect and process large amounts of data, transforming it into useful dashboards, charts and business insights. Read our article to find out what Splunk is, how it works, and what challenges you might face.

What is Splunk?

Officially, Splunk is a US company that develops software for searching, monitoring and analysing large amounts of data. Less formally, people refer to it as its products, services and other offerings.

Splunk employees are called Splunkers, and the name comes from the word "spelunking" - the exploration of caves and mines.

Splunk was founded in 2003 and is headquartered in San Francisco, California, USA. Since 2024, Splunk is now officially part of Cisco, a global leader in IT and computer networking.

Splunk products include:

Observability category:

• Splunk Observability Cloud
• Splunk AppDynamics
• Splunk IT Service Intelligence (ITSI)

Security category:

• Splunk Enterprise Security
• Splunk User and Entity Behavior Analytics (UEBA)
• Splunk SOAR

Platform category:

• Splunk Cloud Platform
• Splunk Enterprise

How does Splunk work?

As mentioned, there is more than one product under the Splunk umbrella. However, the company is known for two main ideas - turning data into doing (regardless of the source) and helping to build the digital resilience of the enterprise.

Splunk takes in data from websites, applications, sensors, devices, and other sources. After ingestion, Splunk indexes the data stream and parses it into a series of individual events that you can view and search.

Can Splunk be used for monitoring?

Yes, Splunk can be used for monitoring, but its capabilities go beyond that. Splunk powers cybersecurity, observability, network operations and data-driven business decisions. In 2025 Gartner Magic Quadrant research, Splunk has been named leader in the market for observability and SIEM solutions.

Whether on-prem, hybrid or multicloud, Splunk provides instant visualization, real-time alerts, and directed troubleshooting.

How is Splunk typically managed and maintained?

Splunk management depends on how the platform is deployed. 

With Splunk Cloud, core platform operations and upgrades are handled by Splunk. With Splunk Enterprise, those responsibilities are managed by your team or a trusted partner. 

In both cases, data sources, add-ons, agents, and onboarding still need the right oversight to keep everything running without problems end to end. A reliable Splunk setup is not only about the platform, but it starts with the right data, safe upgrades, and a clear path to business value. 

Data sources, add-ons, and agents evolve over time, so updates should be handled in a controlled way to protect continuity.

What is the difference between Splunk Cloud and Splunk Enterprise?

Splunk Cloud is a SaaS 24/7 managed service where Splunk handles core platform operations and upgrades. Your subscription to the Splunk Cloud Platform service is at most times workload-based and is sized for resource capacity.

Splunk Enterprise is an on-prem / private cloud that gives organizations more direct control over upgrades, scaling, and platform management. 

In both models, data sources, apps, add-ons, and installing, configuring, and managing forwarders still need our attention and careful management, including maintaining version compatibility. You can find a detailed technical comparison of the differences between both solutions here.

What data can Splunk handle? What can we index?

Ingested data can be almost anything. Splunk can collect data from multiple sources (applications, cloud services, servers, network devices, and sensors) and structure it for analysis within seconds. Splunk platform can index all IT streaming, machine, and historical data, such as event logs, web server logs, live application logs, network feeds, metrics, change monitoring, message queues, archive files, and more.

However, ingestion should be driven by business use cases. Not all data needs to be indexed. Splunk is an analytics platform, not an archive. The focus should be on ingesting data that creates insight and measurable value.

How to make ingested data useful for the business? Our approach is that first, we define the business question and the role that will use the dashboard. Then we confirm what data is available and what context is needed so the results are meaningful. 

From there, we use Splunk dashboards, reports, charts, and pivots to turn the data into clear views that help teams spot issues faster and make better decisions.

You do not always need to start from zero. Many Splunkbase apps and add-ons already include useful dashboards and reports. We can adapt them to your environment and refine them based on your use cases.

Splunk integrations - what can we connect to Splunk? When to use Splunkbase add-ons?

Splunk is built to connect data across your environment, not just one tool. Besides ITSM and ticketing, we commonly integrate Splunk with cloud platforms, applications, API’s, CI/CD pipelines, and internal systems so teams can see what is happening end to end and respond faster.

In some cases, Splunk is also connected to automation and AI workflows, including LLM-based solutions to route alerts and context to the right team with less manual effort.

Most integrations can be handled with existing Splunkbase apps and then tailored to your environment.

A custom app is needed when you have a custom system or API, and there is no ready add-on available. In that case, we build a small integration so that the data is collected and usable in Splunk.

How can Splunk reduce ticketing noise?

Splunk pulls data from different systems into one place, spots important patterns, and can automatically trigger alerts or actions. That means tickets get to the right team faster, with the context they need, cutting down on back-and-forth and delays.

Automation works best when alerts are reliable. Focus on filtering out noise and creating better alert rules so tickets are only created when something actually needs attention.

How to handle Splunk upgrades and patches?

Splunk upgrades should be planned around relevance, stability, and supportability. 

The best approach is to stay aligned with supported versions and apply updates that fit your environment and goals. 

Splunk Cloud handles core platform upgrades automatically, while Splunk Enterprise upgrades should be managed carefully to support continuity and protect data.

How do you make complex data sources usable in Splunk?

We start by understanding the use case and what the data needs to answer. Then we apply parsing, normalization, and enrichment so the data becomes consistent, searchable, and easier to use for dashboards and alerts.

And pro tip: do the enrichment early. Adding the right context at ingestion makes searches faster and reduces confusion later.

Why should you optimize data in Splunk instead of ingesting everything?

The short answer is cost, because Splunk licensing is based on ingestion. Second, the storage. Keeping data searchable is expensive. Retention compliance requirements often force you to keep data for a year or more. 

Data optimization helps you get more out of Splunk without storing everything. The idea is to focus on the data that actually matters and supports real use cases. Sometimes some of the data may be moved to the archive.

The result is cleaner data, more useful dashboards and alerts, and better control over data volume and costs as your environment grows.

What Splunk licensing model is best for our use case?

It depends on your data volume, usage patterns, and growth plans.

Splunk mainly offers two licensing approaches: ingest-based and workload-based. Ingest licensing is often suitable for moderate volumes, such as around 1 TB per day. As data volume or usage complexity increases, the situation needs to be assessed carefully.

In some cases, the workload model is more appropriate, especially when use cases are limited. In other cases, even with higher costs, staying on an ingest model may still be more beneficial. There is no universal answer.

How can we optimize Splunk licensing costs?

Optimization starts with understanding the purpose of the data. 

Not all data delivers the same business value. The first step is to assess what insights the organization actually needs and which data support those outcomes.

From there, our approach is to review ingestion rules, data sources, and retention policies. Low-value or unused data can be filtered, adjusted, or refined. At the same time, high-value data should be prioritized. 

Unused license capacity should be aligned with defined business use cases. Available capacity can support additional insights without increasing licensing cost.

How do we optimize data ingestion in Splunk?

Splunk provides several built-in capabilities to manage data within the ingestion pipeline.

Optimization starts with using the right tools at the right stage. Data can be parsed, filtered, enriched, or routed before it is indexed. Features such as Ingest Actions, Ingest Processors, Edge Processor, and forwarder configurations allow better control over what data is stored and how it is structured.

• Data volumes naturally fluctuate, so it is wise to plan for a healthy buffer.
• In many environments, keeping around 20–30% headroom helps support flexibility, smoother scaling, and changing data needs over time.

We also implement proactive monitoring, ingestion spike alerts, and clear governance practices for onboarding new data sources.

Regular reviews of data usage help ensure the license remains aligned with actual needs.

The goal is to prevent surprises by combining planning, visibility, and ongoing assessment.

Why is my Splunk slow? And how to improve its performance?

In Splunk, it’s about optimizing searches, data models, indexing strategies, and resource usage:

• Always structure searches efficiently (starting with index and sourcetype), avoid leading wildcards, and use Data Models, Summary Indexing, or KV Store to reduce load on raw log searches.
• Common causes include inefficient searches, excessive ingestion, or architectural bottlenecks. 
• Slow performance often results from inefficient SPL, noisy or poorly structured data ingestion, and insufficient hardware resources like CPU, RAM, or disk I/O.

To do a health check, you can use Splunk's basic functions and analyze the data yourself with the Splunk checklist or let Splunk Partner conduct a comprehensive audit for your infrastructure.

Is Splunk worth it?

As with any technology decision, it's essential to assess your company's needs, resources, and budget.

Splunk offers an extensible data platform that powers unified security, full-stack observability, and limitless custom applications. We don’t know if it fits into your expectations, but here are some reasons why customers choose Splunk:

• Process large amounts of data from various sources without scaling issues
• Ensure compliance with applicable regulations on combating digital threats
• Turn data into business insights and know if it’s a market drop, or your internal problem
• Resolve issues faster and mitigate downtime before it impact customers 

About Peakforce 

Peakforce is a remote-first software house based in Wrocław, Poland. We are a team of consultants with deep technical experience in the Atlassian and Splunk domains. As an official partner in both technologies we help companies reach their peak with consulting, health-checks, implementations, and more. We believe in building long-term relationships with our partners, based on trust, open communication, proactive approach and delivering results.

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