The digitalization of the economy, of society and, above all, of companies has led in recent years to the development of generated millions of data, usually difficult to understand.. In order to organize them, understand them and try to extract behavioral patterns, methodologies and professional experts in the field have emerged. Big Data. Thanks to this way of processing data, it has been possible to improve decision making using “Analytyics” platforms and, in addition, projecting these analyses towards the prediction environment using “Deep Learning” algorithms (a Machine Learning discipline).
Now, all connected machines and devices generate a series of information that records the different events that take place within its programming and operation.. They are “unstructured” information called logs. This event information is of great value, since it show all the effects of a system (whether through a program, an application, a server, a client click, a point-of-sale transaction, etc.), in addition to representing approximately 75% of the total information in an ICT installation. Its correct storage and analysis can be crucial when making decisions related to a company's IT infrastructure and business decisions.
Now then, whatwhat programs are available on the market that can perform these functions?
Search engines and log indexing today
The concept of this type of program is based on the same model as Google or Bing, but applied to the registration of logs of the different devices of a company. The idea is to index all this information in a search engine and correlate it to allow searches of different types:
- Search structured with different conditioning factors. Example: item «sale» made by user «X».
- Search unstructured, all those in which a certain value, date or word appears.
- Aggregations, such as averages of values.
With one common characteristic: all these searches are performed in , real-time decision support.
The main search and indexing systems on the market today are as follows:
Elastic SearchApache: it is a document-oriented search engine based on Apache. It has a number of features that make it peculiar, such as, for example, that it is document-oriented (JSON'S, based on Apache Lucene), which is schema-free, is distributed (scales dynamically and implements HA), is multi-tenant (operates on multiple indexes at the same time) and is centered in API'S. It performs, as in the example above, structured and unstructured searches and real-time aggregations.
The two main layers that make up Elastic Search are:
- Distributed systemis responsible for implementing the protocols and coordination logic of the nodes in a cluster and the maintenance and management of the cluster's data.
- Search engineindexing and search functionalities for files and documents.
Log TrustLog Trust: as defined on its own website, Log Trust is a Real-time Big Data platform designed to capture and store data for data processing.. The difference with other traditional databases is that the information is stored through events (the famous logs). This means that the classic «overwrite» and «delete» functions of traditional databases are not necessary, since the information recorded is based on time-stamped events. This new concept is based on the so-called WORM (write once, read many, in English).
Log Trust is particularly recommended for managing and drawing useful conclusions from the large volumes of data created by «Machine Data». That is, all the information created by machines without prior human intervention.
Gray LogBig Data solution, just like the three previous ones, which allows for centralized storage of all logs that machines and devices connected to them generated automatically. Ideal for keeping all logs together within a complex architecture, and thus avoiding the frequent problem of dispersed storage that occurs in very complex IT systems, typical of large companies in the industrial sector.
Splunkfrom our point of view, Splunk is the best Big Data software on the market. We have already carried out different projects with this tool, whose main characteristic is that works with machine data, but also with corporate data.. Its main attribute is the ability to correlate data to generate reports and dashboards of indicators and alarms. The main uses of Splunk are the following:
- Application ManagementTroubleshooting and monitoring of performance degradation
- Security and complianceimmediate response to any security-related incident.
- Infrastructure and operations managementProactive monitoring and troubleshooting.
- Web and business analysisvisibility and intelligence of customers, services and transactions and detects trends and behavioral patterns.
- Ability to analyze business eventualitiesSplunk is able to analyze how an incident can positively or negatively influence a company's sales, logistics, business, marketing or financials.
In short, these are the most prominent log-structured Big Data platforms on the market today. Their importance is increasing due to the high (and constantly growing) number of data generated every second by all the machines and connected devices in the world.
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