Predictive analytics for networks are helping businesses optimize their network performance, anticipate network capacity related requirements, and eventually forecast future much more efficiently than ever. Gartner has estimated the value of network monitoring software market at roughly $2.1 Billion, this figure is presently increasing at a growth rate of 15.9% annually. The demand for predictive analytics in network monitoring software has grown beyond enterprises and datacentres.

IBM recently announced an expanded Cloud Paks offering with LogDNA. With this offering, developers and engineering teams can easily aggregate and search huge volumes of data from any source to gain real-time insights on their applications. LogDNA is now offered by IBM and deployable on-premise or multi-cloud with all IBM Cloud Paks including Cloud Pak for Applications, Cloud Pak for Data, Cloud Pak for Integration, Cloud Pak for Multi-cloud Management, and Cloud Pak for Automation.

Any search engine needs to be be able to parse language. As the field of natural language processing (NLP) has grown, specific text analysis has been applied to stop words and tokenizing (or marking) them by part of speech. In Elasticsearch (and elsewhere), the most attention has been paid to English, although the ELK stack has built-in support for 34 languages as of this writing.

This is a technical deep dive into the authentication process — a necessary first step before addressing the authorization decisions that are at the core of Elasticsearch security. The following will be a very detailed explanation of the inner workings of a key part of the authentication process: realms. If you'd prefer to start with a broader view of authentication (and authorization) in Elasticsearch, you may want to check out Demystifying authentication and authorization in Elasticsearch.

​Have you used Elastic Maps in Kibana yet? I am very excited about multiple layer support. Heat maps, vector layers from the Elastic Maps Service, and even individual documents all in the same interface! What a fantastic way to analyze and visualize your data. But what about geospatial data that’s not in Elasticsearch? Maybe you want to overlay a shapefile of regional sales territories with sales aggregations.

Augmented analytics is trending. You’ve read about it, you’ve heard about it, you may even be in the process of acquiring systems running it. But what exactly is it, and how can you recognize it? As the guys building augmented analytics, we’re here to dispel some of the hype. On the highest level, augmented analytics is the machine learning processes geared at making data more accessible and actionable for both data scientists and business users.

Have you ever needed to grab a log from a local server that is not part of the Windows Event Channel? Applications like IIS or DNS can write their logs to a local file, and you need to get them into your centralized logging server for correlation and visualization. Graylog sidecar can help by creating and managing a centralized configuration for a filebeat agent, to gather these types of logs across all your infrastructure hosts.

Within software development, application logging plays an important role. As much as we’d like our software to be perfect, issues will always arise within a production environment. When they do, a good logging strategy is crucial. But what is application logging? How should you be using application logs? Where can you find them? And what does all this mean for your own logging strategy? We’ll take a look at each of these questions in this post.

Kibana is a powerful visualization platform designed specifically for log management with Elasticsearch. It already provides a lot built-in, but its open-source nature obviously lends it to some pretty cool simple and complicated additions from its community of devs. Some favorites include adding certain kinds of visualizations, API attachments, better integration between Kibana and other platforms, as well simple add-ons for flair in reports.