Reducing Splunk Costs With Telemetry Pipelines

    4 MIN READ
    4 MIN READ

    With 85 of their customers listed among the Fortune 100 companies, Splunk is undoubtedly one the leading machine data platforms on the market. In addition to its core capability of consuming unstructured data, Splunk is one of the top SIEMs on the market. Splunk, however, costs a fortune to operate – and those costs will only increase as data volumes grow over the years. 

    Due to these growing pains, technologies have emerged to control the increasing costs of using Splunk. One of these technologies is telemetry pipelines. These pipelines make routing data easy and have the added benefit of reducing the costs of using Splunk by lowering ingestion costs.

    Let’s dive in and see how. 

    Costs Associated with Using Splunk

    Splunk is known as one of the most expensive tools on the market for what it does. While most companies accept this cost due to Splunk’s best-in-class capabilities, it may lose its appeal over time as prices continue to grow and executives become more cautious with the budget. 

    Speaking of costs, Splunk has three licensing models:

    • An ingest-based model
    • A workload-based model
    • An entity-based model

    Ingest-Based Model

    The ingest-based model works by metering data as it’s ingested. In this model, your company agrees to stay within a specified limit (measured in gigabytes per day of data ingested). However, it’s common for companies to hit multi-terabyte ingestion rates, which can result in eight-figure bills spread out over several years. Blowing your budget is easy, and it’s not uncommon for teams to ask their executives for more money. That’s why having an observability pipeline is essential when you opt for the ingest-based model. That way, the pipeline can route and transform data to reduce size before ingestion – thus lowering the cost of using Splunk. 

    Workload-Based Model

    A workload-based model is different, as it removes the cost associated with indexing data and moves it toward searching that data. Price is determined based on the number of vCPUs indexing and searching the data. An observability pipeline will be less effective in reducing costs on this model type since the prices are relative to searching. 

    Entity-Based Model

    Entity Pricing is a value-oriented metric directly correlated with business outcomes. In the entity-based model, the asset count in your tech stacks for IT, Security, and Observability Cloud solutions is the primary determinant of your investment. Assets include protected devices or hosts, depending on your product selection.

    What Is a Telemetry Pipeline?

    Telemetry pipelines are a collection of functions that data is pushed through to help route and transform the data while it’s in motion and before it’s ingested into a logging platform, where it will rest. Such pipelines help reduce costs and route data more efficiently. In addition, they also increase the efficiency of the overall logging platform. 

    Think of them as similar to oil pipelines. Like oil, data needs a medium to flow through before it can reach its final destination. Telemetry pipelines are the medium through which the oil (or data, in this case) travels before reaching its goal. 

    How Do Telemetry Pipelines Work?

    Telemetry pipelines use tags to route data to where it needs to go based on predefined rules. They also transform the data into a more user-friendly format. At the same time, it’s in motion using methods such as unrolling XML, utilizing Logs2Metrics, removing white spaces, sampling large data sets, deduplicating data, and pre-aggregating data over time. For example, pre-aggregating data over a specified time interval can transform large amounts of raw data into a single aggregated event, reducing the amount of data ingested into Splunk and thus lowering costs.

    Furthermore, telemetry pipelines allow companies to replicate data and send unique flows to specific processors and destinations, meaning companies can leverage other data stores if they do not require all their data in real-time within Splunk. By utilizing telemetry pipelines, companies can route different types of lower-value data to slower and cheaper storage tiers, reducing overall costs while maintaining proper data retention on infrequently-accessed data.

    In summary, telemetry pipelines help reduce costs and increase efficiency by routing and transforming data before it is ingested into a logging platform like Splunk. They use predefined rules and methods to convert the data, allowing companies to replicate data and route it to specific processors and destinations, reducing overall costs and improving data retention. Utilizing telemetry pipelines gives companies greater control over how their data is routed and processed, resulting in optimized Splunk spending and better control over their data.

    Reducing Splunk Costs With a Telemetry Pipeline

    Whether your goal is to keep costs flat and allow your data to grow over time or to reduce your overall spending on Splunk, there are a few ways to achieve it. 

    Data Reduction 

    The most popular way of reducing costs is to reduce and transform raw data coming into the Splunk platform before it is indexed. This can consist of pre-aggregating the data or creating clean key-value pairs from chatty logs with irrelevant data bloating the file size.

    Storage Optimization

    Storage costs are another major factor associated with storing and analyzing data. Accessing that data quickly to gain insights is precious for companies, but this ability entails expensive storage options. A telemetry pipeline gives companies more flexibility, as they can easily duplicate and route different types of lower-value data to slower and cheaper storage tiers. This will significantly reduce your overall storage spending because you can maintain proper data retention on infrequently-accessed data. 

    Faster Search Speeds

    Cleaning up your data before ingestion results in faster search speeds on the Splunk platform. If your data has been pre-processed and refined into clean key-value pairs before it’s ingested, it will take Splunk less time when extracting and searching for that data. Consequently, you’ll see exponential increases in search speeds, lessening the need for more compute resources when onboarding more users to the platform. 

    Telemetry Pipelines Can Save Your Budget

    Whether your goal is to reduce Splunk spend or keep costs flat, a telemetry pipeline is your golden ticket to make it happen. Identifying chatty logs and reducing volume size combined with routing data to different storage tiers should allow you to realize six- or seven-digit savings, making executives happy. 

    At Mezmo, our telemetry pipeline solution puts you in control of how your data is routed and processed, resulting in a lower total cost than ingesting all of your data directly into a tool like Splunk and retaining it there indefinitely. By leveraging Mezmo’s Telemetry Pipeline, you can optimize your Splunk spending and gain better control over your data. 

    Visit our telemetry pipeline page today to learn more about how our solution can help you achieve high observability at a lower cost.