Whenever a business wants to work with the federal government, they are going to have to comply with certain frameworks to guarantee that, as part of the federal supply chain, it is secured to an appropriate level. The specific frameworks and standards vary based on factors such as impact levels and whether or not you’re in an industry with specific guidelines, like HIPAA or DoD standards.
The bright side of FedRAMP compliance is that every detail, from the overall security framework to the individual security controls, is outlined and plainly detailed in NIST documentation. The downside is that tracking and ensuring compliance with these hundreds of security controls is extremely complex, such that it’s virtually impossible to do manually.
There are numerous options for monitoring and maintaining compliance, as well as performing the initial evaluations, auditing, and analysis, but that just brings up another question: which option do you use? Three of the most common are Splunk, Azure, and Sentinel, so let’s talk about each of these and how they compare.
In broad terms, Splunk is a Big Data firm owned by Cisco, specializing in data processing, handling, and analysis. They offer a variety of data analytics and processing products, including enterprise security monitoring, attack analysis, infrastructure monitoring, and more. Specific groups of products can be used for different use cases, including IT modernization, business process automation, threat detection, and even artificial intelligence.
A business can do a wide range of different things with Splunk. It’s not specifically a compliance platform, but it can be used to track security controls and monitor their implementation. It can also be used for a variety of proactive data analytics and associated features that have nothing to do with FedRAMP or the ATO process. Many businesses already use Splunk for a variety of purposes and have little or no need to pay attention to NIST controls; others use Splunk and want to roll out additional features to track that compliance.
Sentinel is a Microsoft product. It’s a cloud-based security information event manager, or SIEM, platform. It leverages Microsoft’s big data cloud processing abilities in a similar way as Splunk to perform a variety of useful tracking and analytics actions. However, it’s a more focused product.
Sentinel is specifically a security platform that provides information monitoring, event management, security orchestration, automation, and response.
Both of these features come from granting Sentinel a bird’s-eye view of your organization, with the ability to hook into and monitor the most granular security controls relevant to your organization, your impact level, and your role in the supply chain.
Azure is also a Microsoft product. Unlike Sentinel, it’s not a focused product; rather, it’s a hybrid cloud platform that provides big data services in the cloud. It can be used in a huge variety of different ways, from using the processing power of their massive databanks for huge data processing operations, to establishing continuous cloud monitoring systems, to deep and robust analytics, and much more.
Unfortunately, comparing Azure to something like Splunk or Sentinel isn’t a valid comparison. This is because Azure serves a different purpose. More specifically, you can establish data sources and monitoring in your business, feed the data into Azure, and have Azure feed that data into both Splunk and Sentinel.
Technically, Sentinel is even based on Azure itself; many people even call it Azure Sentinel. Sentinel and Azure work side-by-side with Splunk, as well.
For most agencies reading this, your decision is which of these two platforms you want to use. The choice of whether or not to use Azure is made elsewhere and is more foundational to your enterprise. Fortunately, it’s not too impactful; both Sentinel and Splunk can be used with a variety of different data sources, ranging from in-house and bespoke systems to data handled and processed by Azure to data processed by other platforms, including AWS.
Before digging into more direct comparisons, the one area where it’s worth bringing up Azure is that, since both Azure and Sentinel are Microsoft products, they are designed with tight integration in mind. While Splunk can use Azure as a data source, it’s not guaranteed to be as easily or as fully integrated. However, much of this does depend on how well you structure and process your data via any particular platform before feeding it into your SIEM of choice.
One of the biggest differences between Splunk and Sentinel is that Sentinel was designed purely as a platform for security and compliance, largely with NIST security control lists like SP 800-171 and SP 800-54 in mind. Compliance with FedRAMP, CMMC, and other frameworks is built into the expectations of Sentinel; if you’re using Sentinel, you have a clear goal in mind, and it’s built to help you obtain that goal.
Splunk, meanwhile, is a broader platform with more features. This is both a pro and a con. On one hand, it can be more broadly used throughout your organization. If you need big data warehousing, processing, handling, categorization, or analysis, Splunk has features to help you with any or all of those. Microsoft does as well, but – critically – not through Sentinel. You have to spin up and use other systems, like Microsoft E5, rather than doing it all through the one contained platform.
This is a significant decision point. On one hand, the more different systems you need to integrate, the more chance there is for data handling errors. On the other hand, it’s a waste to set up and pay for a huge multifaceted enterprise system and then only use 15% of its features. This is, at the end of the day, a decision unique to each business based on the rest of your processes and infrastructure.
While both Splunk and Sentinel can easily ingest and handle data from a wide range of possible sources, Microsoft really encourages you to stick within their ecosystem. As such, when you’re set up using systems like Azure and E5, you’re able to pull in data from those systems and process it in Sentinel with little or no friction and no added cost. However, the credits you’re given for this data handling and processing don’t extend to outside-of-Azure data sources; if you have data in another system, like AWS, it’s rather likely you’ll see costs for those processing cycles skyrocket.
Meanwhile, since Splunk is designed to ingest data from a variety of other sources, it’s a lot more stable in terms of costs. You can reasonably anticipate and calculate what your expectations should be.
AI for data processing is the next big innovation in technology. Virtually every big tech company – and many more besides – are investing in it, in some form or another. Cisco in particular is leaning heavily in various data processing and AI features. Microsoft, despite acquiring OpenAI, is still more conservative with it.
What this means is that both Splunk and Sentinel offer AI features, but Splunk is more forward with them, while Sentinel uses them for more free-form analysis and less specific tasks. Both can be hammered into whatever shape you need them to take, and both can be very useful.
That said, for the time being, the use of AI is not considered validated for NIST and FedRAMP compliance. It will take some time for the technologies to mature and for them to be worked into current NIST standards, as well as the eventual defined utility and certification other tools have.
All of this means, essentially, that the AI features are useful for secondary analysis and things like incident detection, but data still needs to be processed and validated by a system that is not a “black box” as far as NIST is concerned.
Overall, the use or non-use of AI shouldn’t be a determining factor in whether or not you’ll use Splunk or Sentinel for your FedRAMP compliance, as it’s tertiary to the actual security control and enforcement. At most, it can speed up self-auditing and validation when handled properly.
Microsoft’s Azure and Sentinel are cloud-native applications that leverage the power of Microsoft’s massive array of data centers to perform pretty much any operations you need. Microsoft has ensured that the systems used by these applications are validated with FedRAMP themselves, so there’s no conflict in using them for your own validation.
Splunk, meanwhile, is primarily an on-premises platform. In many ways, this offers more flexibility and control over your data. However, it does mean you lose out on the benefits of off-loading processing and such to the cloud, including big data processing. For larger enterprises capable of spinning up their own server farms and powerful systems, this isn’t a drawback, but for others, it can be a deal-breaker.
Splunk’s wider range of ingestible data sources – and fewer restrictions on them based on credits and fees – makes it a powerful system for businesses that use many different third-party data sources for their compliance data. This is also true if you’re using bespoke systems. Sentinel generally prefers that you maintain use of the Azure-Microsoft-E5-Sentinel ecosystem and disincentivize using third-party systems in conjunction. They don’t prohibit it, but it can be costly and inconvenient.
Many developers also find that Splunk’s syntax and search/query language is more flexible and powerful than the language used by Microsoft. This is also frequently an individual consideration, and your developers may prefer one over the other. But, starting from zero, many seem to prefer Splunk.
For those who want to be at the cutting edge of AI’s use in data management systems, even in the world of compliance, Splunk can be a better option as well. That said, the AI ecosystem is changing rapidly, so this won’t necessarily always be true.
The three biggest advantages that Sentinel has over Splunk are:
Choosing between these systems is largely going to be a matter of your business’s configuration and the other systems you use, as well as the level of compliance you need to attain.
The lower price point is a benefit of Sentinel if you’re within Microsoft’s ecosystem. If you’re relying too much on external sources, however, it can be more expensive.
At the end of the day, your choice between Sentinel and Splunk comes down to what you want out of a platform, what other tools and systems you use in your configuration, and various personal considerations, such as the pricing model and any internal resistance to Microsoft products.
Truthfully, neither option is inherently “better” than the other. Both are certified and validated for use with FedRAMP compliance, so they won’t get in the way of your adherence to NIST security standards.
If you’re seeking a way to accumulate data, aggregate monitoring, and streamline your compliance, but you don’t want to invest fully in the expensive and time-consuming transition to a big data system like Splunk or Sentinel, we can help. Our Ignyte Platform is an excellent option for the transition. You can ditch the tedious, desynchronized, and siloed systems like spreadsheets and non-cloud databases and instead make sure all of your data is kept in one place, easily accessed and analyzed, and ready for audit.
If you’re interested in seeing what we have to offer and how we can streamline your FedRAMP compliance process, we encourage you to book a demo today. If you have any questions, you can also feel free to drop us a line to ask.
*** This is a Security Bloggers Network syndicated blog from Ignyte authored by Max Aulakh. Read the original post at: https://www.ignyteplatform.com/blog/compliance/splunk-azure-sentinel-compliance/