IT-Monitoring
Using Elastic Stack to Monitor Your Data

IT Monitoring Made Easy With Elastic Stack

  • Blog Editorial Team
  • User Productivity, Publisher Advisory
  • Elastic Stack, IT-Monitoring, Data Management, Business Intelligence

IT monitoring is all about overseeing and analyzing big amounts of heterogeneous data. This is often made difficult by the sheer complexity of the material. This article explains how you can use open source technology like Elastic Stack – specifically its search function – to simplify IT monitoring, enable real-time system monitoring and to throw up effective safety nets by working out the worrying signals.

Logs, Metrics and Traces: The 3 Pillars of IT Monitoring

Essentially the entire IT infrastructure creates some form of simple logs, metrics and traces. Logs record all the events happening within a system: Log-ins, user interaction, transactions, errors and system failure, hence producing a comprehensive, discrete list of activities.

Metrics – occasionally called telemetric data –are different. They represent a steady stream of numerical values originating from monitored components like processor, memory and hard disk utilization, as well as network and memory activities in the systems or transaction times and conversion rates in applications.

Traces come directly from the individual applications like e-commerce shops or business applications written in Java, Go or one of the other programming languages. Traces contain information about the performance capabilities of the application at a distinctly granular level, for instance methods, functions, exceptions or queries in a database. Developers love traces as they let them peer beneath the hood of an application almost in real-time, enabling an even quicker introduction of bug fixes.

The benefit to business is obvious: Faster troubleshooting in the development phase and in productive operations as well. Take just the lower costs of operation, the shorter times to resolve problems and the leverage of customer satisfaction.

The Difficulties in Monitoring All

As if it weren’t enough that logs, as text-based records of events, are fundamentally different to the steady stream of numerical data found in metrics (time series’) and that traces are records of function, method and database retrievals within an application: It becomes even trickier when the systems generate each of these data in their own special formats. This dissimilarity in formatting and structure was among the reasons why data from varying sources was processed separately and then stored and analyzed in different systems.

As if it weren’t enough that logs, as text-based records of events, are fundamentally different to the steady stream of numerical data found in metrics (time series’) and that traces are records of function, method and database retrievals within an application: It becomes even trickier when the systems generate each of these data in their own special formats. This dissimilarity in formatting and structure was among the reasons why data from varying sources was processed separately and then stored and analyzed in different systems.

Until now, administrators or developers summoned in the middle of the night to deal with a system failure were forced to bulldoze their way manually through billions and even trillions of differently formatted text entries in log files, before they could find what was causing the problem. The absence of a uniform format for varying infrastructure sources and applications merely compounded the predicament in complex and separated environments. You only need to consider the dynamics and challenges of the currently popular container orchestration, for instance with Kubernetes and Docker.

How Elastic Stack Makes IT Monitoring Significantly Easier

Simple search and retrieval of log files by indexing the logs

Admins and developers were the first users that flocked to open source search technologies like Elastic Stack. Indexing logs from a number of systems was the perfect application scenario to analyze heterogeneously structured texts at petabyte level. Users were able to retrieve important log files in mere seconds.

All the same, the administrator and sometimes the developer still had to establish the cross referencing of metrics (that indicate the impact on the system) and the underlying logs or even traces by hand. Some equipped with sufficient courage and enough time even developed their own user interfaces in order to merge specific instances of log data, metrics or traces from different applications.

Quick indexing, storage and analysis

The platforms got better as the search technology became more advanced, incorporating new and improved functions to import, index, store and analyze numerical and time-based data. Eventually, these advancements yielded the ability to analyze all data in a simple way and in the same application, regardless of their original source.

Meaningful overviews of interaction between hard- and software

Viewed together, logs, metrics and traces have the potential to deliver a brilliantly transparent overview of the complex interactions between hard- and software platforms for all applications and users in any environment. Administrators and developers have at their fingertips comprehensive, analyzable information that they can deploy to optimize performance, boost efficiency and produce more precise statements on the causes of failures.

Figure 1: Example of a Kibana dashboard showing customer activities and revenues in real time
Figure 1: Example of a Kibana dashboard showing customer activities and revenues in real time, source: Elastic Stack

From quicker responses, to forecasts and prevention

By using search as the repository, administrators have more capabilities than only to detect anomalies and determine causes faster than before. They are now able to model and analyze large quantities of historical data – not only to learn from past failures, but also to recognize patterns, trends, precursors and alarming signals.

Modeling of these trends means that search can be used as a platform for real-time system monitoring and notification that sends alerts even before the system fails. If we add machine learning to these models, we become able to add considerably more precision while developing them faster as well.

IT Monitoring Made Easy With Elastic Stack
Figure 2: Example of a Kibana dashboard used for the detection of anomalies in system and user behavior, source: Elastic Stack

Now logs, metrics and traces are not just the base material used to locate acute problems but are becoming important tools in the optimization of hardware, software and even business processes as well.

IT Monitoring Made Easy With Elastic Stack
Figure 3: Example of a Kibana dashboard used for error impact analysis, source: Elastic Stack

How Companies can Benefit

The capacity to store, monitor and analyze all data on one flexible platform has since grown beyond the simple enhancement of data center resilience and efficiency.

Many conventional systems for analyzing logs, metrics and traces build on relational database technologies. Before, applications were developed for the analysis of particular relationships, and users were restricted to predefined data structures. In contrast, users can split and group data stored in Elasticsearch any way they like. This created the option of researching new relationships and correlations quickly and according to all conceivable patterns.

Not only did this freshly acquired freedom give IT system administrators and developers the opportunity to switch from problem solving to system optimization, it also created a new and even more important role for log, metric and trace analysis in the whole company.

The fine granular modeling of how users interact with IT systems and applications means that the combined data also shows how customers, prospectives, suppliers, partners and employees interact with the business processes in real time. This way, analysis of operational data from IT is increasingly becoming an essential tool for the analysis, modeling and monitoring of human behavior and for business process optimization.

Do You Want to Learn How to Get Started with IT Monitoring?

Let’s discuss the topic together and find a way to integrate IT monitoring into your business.

  • Thursday 20 December 2018

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