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.

Today is an exciting day for Loki, as we have decided it’s time for Loki to graduate out of beta and into a 1.0.0 GA release! It’s been just about a year since we announced Loki at KubeCon + CloudNativeCon North America in Seattle, and in that time over 137 contributors have made more than 1,000 contributions. Here’s a look at where the project is today.

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.

Paytm Insider’s motto is “to make every day less everyday,” says Hitesh Pachpor, Technical Manager for the popular platform for buying event tickets in India.

As users adopt Kubernetes, Elastic products move fast to support their evolving needs. Whether you are trying to run Elasticsearch workloads to Kubernetes or want to gain better visibility into container workloads running across different environments, we are doubling down on building cloud native tools to support these efforts. This blog covers recent advancements to support Kubernetes initiatives:

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.