I’ve already discussed how monitoring applications is vitally important. With companies continuing to operate at a vast global scale and build applications that need to interact with a wider array of users than ever before, it's important that they understand the respective issues they may face to better cater to them and make a success out of their monitoring strategy. And being prepared for these challenges and knowing how to handle them will make it easier for you to make a success out of your monitoring efforts.
Dealing with volumes of data
The most important challenge that companies need to be prepared for and ready to overcome quickly is in dealing with the vast amounts of data that will be gathered through application monitoring. And this is on top of the data needs that are required just for users and system operation. Managing large volumes of data is more than simply provisioning the appropriate places to store data, but requires the right strategies and thought to be able to work with large volumes of data.
To effectively manage very large volumes of data, meticulous organization is essential. First of all, companies must know where their data is stored. It sounds obvious, but with monitoring taking place on every node, server, and part of an application at a global level, it's important that companies know the different sources of data to ensure they are collecting everything they need. It’s not just about knowing where the data is stored though, but knowing which data is needed and which is not is just as vital. We can capture all manner of data through different monitoring solutions, but just because you can capture it, doesn’t mean it is needed and so only the appropriate data must be gathered from the tools with the rest deleted or archived.
Following this, it's important that data is correctly labeled and categorized across the different sources and metrics that it is representing. It’s important that monitoring tools do not place a great load on the rest of the application infrastructure and so as such, the data needs to be shaped in a manner that matches the needs of the visualization or reporting software to allow for quick processing.
Data should also be sorted into different locations based on their retention, with data that needs to be kept and analyzed over time stored in an appropriate location, while other data is moved to a separate archiving location or deleted entirely once it no longer needs to be retained.
The category to which each piece of data belongs, as well as its owner, must therefore be clearly defined and sorted out to be of use for analysis and if this is not done right, it's easy to misrepresent the data and miss insight it can provide.
Fragmentation of data and environments
From reading the above it’s probably clear to see that data fragmentation is likely. With data stored in different locations based on their need, it's easy for data to be duplicated across multiple locations creating huge caches of secondary data that aren't essential to business operations and affect storage capabilities. This can place a great strain on your data infrastructure and while some level of fragmentation is inevitable, it's important that companies find a way of managing thousand not storing too much data in the process.
An important thing to look out for here is how different tools are storing data and whether there are redundancies in the information being gathered. Having a more effective organization of the data is also helpful, as it makes it easier for you to prioritize which data is more important than others and then know when and which data to delete to prevent resources from becoming too constrained.
Thanks to the cloud, there are also many different options of low-cost volume storage that can be used for archiving should you ever need s[pecifc data in the future and so it’s important to explore all these options to better understand how you can better mitigate this issue in your own organization.
Tool Sprawl
Another common issue is that of tool sprawl. With so many different tools available that offer benefits in tracking or monitoring data across different aspects of your application and infrastructure, it can be easy to get stuck with many different tools which now need to be operated, maintained, and updated. And which will likely require significant training from engineers to become familiar with. So, while there are many great tools out there that can assist with many different aspects of monitoring, try and minimize the usage of tools and do an in-depth investigation into the different strengths of weaknesses of each before deciding on the few that you feel will best meet your needs. Yes, there may be compromises that need to be made, but these can be worked around and customized over time.
Data privacy
Managing data privacy is always a critical and complex thing for any organization. With monitoring applications processing copious amounts of data through your different applications, it is important that any specific sensitive data is not accessible from your monitoring tools. And where it is required, stringent data security protocols are in place so that only a specific tool can access that information and that it is stored in an isolated data store where certain sensitive data like identification numbers and card numbers are further hashed or removed entirely.
There are also the various legal aspects that need to be considered because while monitoring application performance might not be critical, monitoring customer usage on an application can be sensitive and it should be clear to customers in the terms and conditions that this is being done, but that it is also clear how this is kept anonymous and - again - with all sensitive data removed.
Team Collaboration
It’s likely that your data will be gathered across systems and applications involving many different teams. And if there isn’t a consistent approach to monitoring or a willingness to conform among teams, it's likely that the company will be left with a vast array of different monitoring approaches that will only exasperate all the fragmentation problems already mentioned. It’s important that a company solidifies its strategy around this and gets teams working together on monitoring to ensure that the correct data is gathered and that they can provide the business with the important information it needs while also allowing each team to effectively manage and respond to issues that are important to them too.
Choosing the Right Graphical Representations
One of the big issues with storing lots of data is finding the appropriate way to visualize it. Monitoring is only effective if it can be easily read, understood, and provide the right sort of information so that decisions can be made from it. Understanding how the data needs to be visualized and graphed is key to ensuring your monitoring meets the required objectives. Doing this is far more complicated though and it’s important that thought is put into place to ensure this information is shown in the right way.
Many tools offer a lot of prebuilt dashboards that can help with this, but often companies need to rely on more customizable visualization tools like Grafana or New Relic to better showcase the information in a way that makes sense to them and allows them to tell the story that is needed.
Many companies put a lot of effort into gathering the right information but forget the importance of its representation and in order for management to best make decisions on this data, it's vital to get this need addressed early. Especially considering that how data will be visualized, may determine how it is shaped and stored to provide the required level of detail and performance.
The good news though is that as a company you are not alone in facing these issues and many companies have already gone through them. Many of the existing tools provide easier management of application and system monitoring and data, but there are also many different best practices guides and tools that cna be leveraged from different companies that can help with this. What’s important though is that as a accompany, you put in the effort to best understand these problems, how they might affect you, and then appropriately mitigate them - otherwise all that monitoring data might end up consuming and overwhelming you rather than adding value.