What is Splunk? A Guide To Understanding Everything About Splunk

What is Splunk?

What is Splunk? Computers today produce a tremendous amount of data. Some of it is human-readable. A lot of it is not. Splunk is a data management solution that can take large volumes of machine data, analyze it, and produce easy-to-read visual reports.

Splunk, and other similar technologies, are becoming essential to many industries. From marketers seeking to refine their outcomes to web developers trying to route traffic — it’s essential that people can both read and understand machine-generated data.

Below, we will discuss what Splunk is, why it’s used, and why it’s such an important technology. While it’s not the only data-mining and data visualization tool available, it is one of the most popular.

What is Splunk?

Splunk was co-founded in San Francisco in 2003. About two decades later, Splunk is a business worth $2.36 billion in revenue annually. 

Splunk is a utility that is able to index and analyze real-time, machine-generated data. That data is then sent into reports, graphs, alerts, dashboards, and visualizations.

While Splunk isn’t the only competitor within this space, Splunk has made a name for itself as one of the major real-time log management systems. It can be used for a variety of purposes, some very specific, and others generalized.

What is Splunk Used For?

Splunk’s analysis solutions can be used to identify key data patterns, diagnose issues, and provide core metrics. 

For an organization, this provides the most basic advantages of data mining. Organizations are able to identify potential patterns, such as bottlenecks or logistics problems. From there, they can react intelligently to risks before they occur.

Specifically, Splunk is frequently used as a log analysis and monitoring solution. While Splunk can crunch any set of data, the most common application for Splunk is to mine through logs to determine system performance, network performance, or website performance. 

Splunk can also be a key business intelligence solution, if so used. With Splunk, organizations, developers, and individuals can mine data for important insights. Splunk can be used to ensure that applications are properly load balanced and resources are used intelligently, to ensure that security and compliance metrics are met, and to identify revenue-generating opportunities for businesses. 

But because Splunk does have a significant barrier to entry, developing for and configuring Splunk can be a challenge. Splunk administrators and developers work to identify an organization’s data needs and translate it into something that will be usable and easily analyzed by the system. Splunk isn’t entirely “set and forget,” but once understood, it is quite powerful.

How Does Splunk Work?

Splunk imports data in real-time and then analyzes it based on set goals. 

A webmaster, for instance, might be feeding in machine-readable traffic to analyze where traffic is going, where there may be bottlenecks, and whether there may be disruption. A webmaster’s dashboard may alert the webmaster when unusual changes are occurring to traffic, when a malicious attack might be on the way, or when the webmaster may want to procure additional resources.

Splunk is, by its very nature, a flexible product. It’s designed to pull in data, look for metrics, and then analyze and report on those metrics as defined by the organization. 

If a sales professional wants to take a look at specific user demographics, they can; if a business wants to look at logistics data, they can. 

Thus, Splunk is a very agile and robust platform that can be used for the analysis of many types of data. But it does need to be trained to do so. 

Splunk: Zero to Power User

What is Splunk Architecture?

Part of what makes Splunk so useful is that it has a distributed architecture. In other words, searching occurs down a tree of possibilities, rather than linearly. The search goes to search heads, which then traverses down to search peers. 

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Through Splunk’s distributed architecture, organizations can scale upward more easily. And searches can be conducted faster. This type of optimization is critical in data mining and management, when large volumes of data need to be processed. 

Splunk can operate either on-premise or on the cloud. Many organizations use the cloud-based application, which is charged at a variable rate by the amount of resources used. An advantage to using Splunk as a cloud-based service is that it can crunch spectacularly large volumes of data, using the power of the cloud. A disadvantage is that this power does come at a direct cost.

How Do You Learn Splunk?

As Splunk is such a popular suite, there are many classes, seminars, and lessons on its fundamentals. Because Splunk is a very high-level, advanced data management solution, users need to understand the basics of data analytics and data science. In fact, Splunk is one of the most sought-after data science skills.

Splunk itself also provides some basic classes on Splunk fundamentals. But these only form the basics of using the platform. Most users will need to understand the concepts behind data science and analytics, too.

What Are Splunk Certifications?

If you’re trying to learn Splunk, you might be interested in investing in a Splunk certification. A Splunk certification is a boon for any data scientist or developer. The certification path is as follows:

• Splunk Certified Power User. A Certified Power User is someone who is exceptionally confident at using the system. They are well-versed in data importing and extraction, data analysis, dashboards, reports, and more. A Certified Power User is expected to understand the basic fundamentals of Splunk.
• Splunk Cloud Certified Admin. A Certified Admin is someone who can actively administrate the Splunk system. They can use console functions, manage other users, and understand the basics of not only maintaining the system, but also controlling and configuring it. 
• Splunk Certified Developer. A Certified Developer is an individual who is an expert in the Splunk system and who can actively develop around the Splunk platform. Very few people can call themselves a Splunk Certified Developer.

The above certification path can show employers that you understand the ins and outs of Splunk. Splunk itself provides classes and coursework tailored to helping individuals pass these certifications — and the certifications are offered through the company.

What Are the Benefits of Splunk?

There has to be a reason why Splunk is so popular. Splunk is focused on analytics and metrics related to performance, but that’s not all it can do. It has a breadth of functionality. Here are some of the core benefits of Splunk.

• Splunk allows integration with machine learning and AI. Though the learning curve may be steep with Splunk, it isn’t as steep as the standard learning curve for AI. Businesses can take advantage of AI and machine learning by adopting the Splunk platform.
• Splunk is a “data to everything” platform. In other words, it’s a general-purpose utility. Even if it is more frequently used for specific use cases, Splunk can be applied to any volume of complex data.
• Splunk can reduce downtime and disruption. By monitoring system health and performance, Splunk can help an organization reduce costly downtime and avoid potential disruption.
• Splunk can provide smarter insights into data. In terms of Business Intelligence, Splunk can sort through logistics and operational data, identify patterns, and help analyze these patterns with easy-to-read visual reporting. 
• Splunk can improve security systems and performance. Splunk can be used to identify potential intrusion, performance issues, and reliability issues, sending reports and alerts directly to the dashboard.
• Splunk is extremely scalable. Because of the Splunk architecture, Splunk can search through even enormous data sets with ease. Organizations will be able to grow their data without fear that they will eventually outgrow their data management system.
• Splunk can be used through the cloud and on-premise. Splunk can either be downloaded to a machine or can be used on the cloud, providing additional agility. Many other, similar systems can only be used on the cloud.

The clearest benefit to Splunk is that it’s a generalized system. Even though it’s used most frequently for log management, it can also be used for other applications. It’s a robust, flexible, and scalable solution.

What Are the Negatives of Splunk?

That all being said, Splunk isn’t the perfect solution. It isn’t always the most ideal solution for a given project. Negatives of Splunk include:

• It isn’t always cost-effective. For larger projects, Splunk can get quite expensive for larger projects, as its cost goes up when resources are used. An organization may find that it’s spending too much in its data management and data analysis.
• It can be too generalized. Because it isn’t targeted toward a specific use case, its dashboards may be too generalized for certain use cases. For log management, for instance, it may not have enough customization specific to log management.
• It is difficult to learn. There’s a significant barrier to entry when it comes to Splunk. It’s such a comprehensive system that it takes some time to learn, even for simpler tasks. It is a system that’s best for those who would use it frequently, such as marketers or data scientists.

Of course, the latter can also be a benefit. Splunk is very difficult to master. And that means that it’s an extremely in-demand skill in certain markets. Those who have certifications in Splunk or have mastered the technology may not find it difficult to get a job within the field.

What Are Alternatives to Splunk?

Data management is a swiftly growing field. So, it only stands to reason that there are also some popular alternatives to Splunk. Let’s take a look at a few of the most common:

1. Loggly. Founded in 2009, Loggly is a cloud-based analytics and log management solution that provides speedy searches over large volumes of data. Loggly is designed to help organizations identify performance issues quickly by combing through logs in real-time.
2. Sumo Logic. Another cloud-based analytics engine, Sumo Logic is designed for both log management and analytics services. Sumo Logic can be applied to Business Intelligence, operations, logistics, and security. It provides real-time data and metric analytics. 
3. LogZilla. LogZilla is focused not only on log management but also network orchestration, with a focus on ensuring that network performance is always high. Through LogZilla, organizations can reduce the chances of load balancing issues, bottlenecks, and other performance-related problems.
4. logFaces. A log server, aggregator, and viewer, logFaces pulls real-time log streams as well as batch, historical log streams, and mines it for data that could potentially indicate disruption or resource management issues. 
5. Sentry. A performance monitoring system, Sentry pulls logs and mines them for performance-related issues, alerting when relevant. Sentry is a self-hosted, cloud-based error management and performance management solution that can make managing a network easier.
6. Hadoop. Hadoop is a well-known Big Data system that has even more generalized utility than Splunk. Hadoop, managed by the Apache Project, can be used for virtually any Big Data task. It is an extremely popular system. 

These alternatives all have pros and cons in comparison to Splunk. As you might note, most of them have a key focus. Some are focused on log management only, while others can also complete Business Intelligence analytics. Some focus more on security, while others focus more on load balancing.

Depending on your organization or your project, Splunk may be better-suited or worse-suited to your data. Often, the best way to determine the right solution is to try out as many of them as possible. 

Who Uses Splunk?

Many large companies use Splunk: Cisco, IBM, Adobe, Salesforce, Facebook, and Walmart included. 

According to Splunk, over 15,000 customers in 110 countries use the Splunk tool to mine through their data. Splunk is an exceptionally versatile and robust technology – and it’s easy to see why it’s become so successful. 

In terms of work, Splunk is most frequently used by data scientists, data analysts, data engineers, and data architects. But Splunk may also be used by engineers, marketers, web developers, webmasters, and scientists. Anyone who needs to crunch exceptionally large data sets may be able to transition them to the Splunk platform.

Conclusion

So, if you’re wondering, “What is Splunk?” the answer is: Splunk is everything. Splunk is a way to interact with complex data sets. If you have complex, machine-readable data sets, then you can use Splunk to process and analyze them. To learn more about Splunk, there are courses, lessons, and even bootcamps available.