Entering a Golden Age of Data Monitoring
June 13, 2018

Thomas Stocking
GroundWork Open Source

Share this

The importance of artificial intelligence and machine learning for customer insight, product support, operational efficiency, and capacity planning are well-established, however, the benefits of monitoring data in those use cases is still evolving. Three main factors obscuring the benefits of data monitoring are the infinite volume of data, its diversity, and inconsistency. However, it's these same factors that are fueling a Golden Age of systems monitoring.

1. Data Availability is Increasing

The trend over the last several years has been to collect more data – more than can ever be analyzed by humans. Data monitoring tools, by their very function, are in and of themselves a significant source of data. With the advent of NoSQL databases, optimize-on-read technologies, and the availability of very fast data consumers (influxdb, Opentsdb, Cloudera, etc.), the amount of data from monitoring systems is exploding.

2. Monitoring Data is Diverse

You would think more is better, as is often the case with data. That is what we learned in high school stats class, after all. However, more isn't always better, and in fact, most of the data we gather from monitoring is rather difficult to analyze programmatically. There are many reasons for this such as the complexity of modern IT infrastructures as well as the diversity of data.

Data diversity is an old IT problem. We collect data on network traffic, for example, using SNMP counters in router and switch MIBs. We also use netflow/sflow and do direct packet capture and decoding. So to even answer the question, "Why is the network slow?" we have at least three potential data sources, each with its own collection method, data types, indices, units and formats. It's not impossible to do analysis on the data we collect, but it is hard to gain insight when dealing with what my colleagues and I call "plumbing problems."

3. Monitoring Data is Inconsistent

You would think after all this time monitoring systems there would be a standard for the storage and indexing of metrics for analysis. Well, there is. In fact, there are several (Metrics 2.0, etc.). Yet, we are still dealing with inconsistency across tools in such basic areas as units, time scales, and even appropriate collection methods. With these inconsistencies, sampling data at five minutes vs. five seconds can yield vastly divergent results.

Benefits from Monitoring Data

Despite these issues, we are moving into a Golden Age of analysis. It's clear the most consistent parts of the monitoring data stream such as availability (as determined by health checks, for example) can be mined for very useful data, and used to create easily understood reports. If you combine this with endpoint testing, such as synthetic transactions from an end-user perspective, the picture of availability becomes much clearer and can be used to effectively manage SLAs.

Delving a level or two deeper, measurements of resource consumption over time can reveal trends that help with capacity planning and cost prediction. Time series analysis of sets of data that are consistent can reveal bottlenecks and even begin to point the way to root cause analysis, though we are still far away from automating this aspect.

The Future of Data Monitoring

There's a revolution in monitoring data with the advent of the cloud. We are suddenly able to gather a lot of data on the availability and performance of nearly every aspect of our systems that we run in the cloud.

In fact, as far as APIs go, there are even services that will consume all of your application traffic and analyze it for you, opening the possibility of dynamic tracing of transactions through your systems. If you are going cloud-native, you can take advantage of this area of unprecedented completeness and consistency of data, with minimal "plumbing" to worry about.

However, expect your job to get both easier and harder. Easier, since you will have more data, and sophisticated systems to analyze it. These systems and data it produces are becoming more homogeneous with cloud technologies and more consistent as the monitoring industry settles on standards. This will provide you better data for the systems you buy to analyze.

It will also be harder. When your systems fail, you won't easily find the data needed to fix things yourself. Similar to your cloud vendor, your monitoring system will be a complex and powerful toolset that will need time to learn, and you will absolutely be reliant on your providers for their expertise in its finer points.

Despite these challenges, the potential impact of effective data monitoring is significant. Effective data monitoring can help reduce outage and availability issues, support capacity planning, optimize capital investment, and help maintain productivity and profitability across an entire IT infrastructure. As IT systems become increasingly more complex, data monitoring becomes increasingly more vital.

Thomas Stocking is Co-Founder and VP of Product Strategy at GroundWork Open Source
Share this

The Latest

September 19, 2019

You must dive into various aspects or themes of services so that you can gauge authentic user experience. There are usually five main themes that the customer thinks of when experiencing a service ...

September 18, 2019

Service desks teams use internally focused performance-based metrics more than many might think. These metrics are essential and remain relevant, but they do not provide any insight into the user experience. To gain actual insight into user satisfaction, you need to change your metrics. The question becomes: How do I efficiently change my metrics? Then, how do you best go about it? ...

September 17, 2019

The skills gap is a very real issue impacting today's IT professionals. In preparation for IT Pro Day 2019, celebrated on September 17, 2019, SolarWinds explored this skills gap by surveying technology professionals around the world to understand their needs and how organizations are addressing these needs ...

September 16, 2019

Top performing organizations (TPOs) in managing IT Operations are experiencing significant operational and business benefits such as 5.9x shorter average Mean Time to Resolution (MTTR) per incident as compared to all other organizations, according to a new market study from Digital Enterprise Journal ...

September 12, 2019

Multichannel marketers report that mobile-friendly websites have emerged as a dominant engagement channel for their brands, according to Gartner. However, Gartner research has found that too many organizations build their mobile websites without accurate knowledge about, or regard for, their customer's mobile preferences ...

September 11, 2019

Do you get excited when you discover a new service from one of the top three public clouds or a new public cloud provider? I do. But every time you feel excited about new cloud offerings, you should also feel a twinge of fear. Because in the tech world, each time we introduce something new we also add a new point of failure for our application and potentially a service we are stuck with. This is why thinking about the long-tail cloud for your organization is important ...

September 10, 2019

A solid start to migration can be approached three ways — all of which are ladder up to adopting a Software Intelligence strategy ...

September 09, 2019

Many aren't doing the due diligence needed to properly assess and facilitate a move of applications to the cloud. This is according to the recent 2019 Cloud Migration Report which revealed half of IT leaders at banks, insurance and telecommunications companies do not conduct adequate risk assessments prior to moving apps over to the cloud. Essentially, they are going in blind and expecting everything to turn out ok. Spoiler alert: It doesn't ...

September 05, 2019

Research conducted by Aite Group uncovered more than 80 global eCommerce sites that were actively being compromised by Magecart groups, according to a new report, In Plain Sight II: On the Trail of Magecart ...

September 04, 2019

In this blog, I'd like to expand beyond the TAP and look at the role Packet Brokers play in an organization's visibility architecture. Here are 5 common mistakes that are made when deploying Packet Brokers, and how to avoid them ...