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How machine learning in the Elastic Stack keeps Leaseweb secure

Leaseweb is a global Infrastructure-as-a-Service (IaaS) provider offering customers hosting solutions to boost their business while cutting costs. From our beginning 20 years ago, our founders envisioned how they could use their skills and experience as professional pilots to build out the Internet as a service in hopes of making it accessible and available to everyone. Today, that same vision remains part of our DNA.

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Monitoring Kafka with Elasticsearch, Kibana, and Beats

We first posted about monitoring Kafka with Filebeat in 2016. Since the 6.5 release, the Beats team has been supporting a Kafka module. This module automates much of the work involved in monitoring a Kafka cluster. In this blog post, we'll focus on collecting logs and metric data with the Kafka modules in Filebeat and Metricbeat. We'll be ingesting that data into a cluster hosted on the Elasticsearch Service, and we'll explore the Kibana dashboards provided by the Beats modules.

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Skopos Labs: Our experience with Elasticsearch and Elastic Cloud

Skopos Labs is a legal and financial data provider that has built a novel and extensively validated machine learning platform that analyzes massive amounts of data to provide strategic, real-time forecasts of government policies and their impacts on companies and industries. For example, Skopos provides predictions of how likely bills in Congress are to be enacted into law, as featured on sites such as GovTrack.us.

Elastic Austin Meetup - May 2019

Elastic Bots: Analyzing Conversational AI for Artificial Capability Equivalence, Cognitive assistants, virtual agents, and chatbots have taken the world by storm and are now making their way into the large enterprise space. AI and machine learning initiatives are hot on every CxO ticket for 2019, but most organizations are unsure how they should measure the success of their investment and its effectiveness on the enterprise.
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Configuring SSL, TLS, and HTTPS to secure Elasticsearch, Kibana, Beats, and Logstash

Elastic released some security features for free as part of the the default distribution (Basic license) starting in Elastic Stack 6.8 and 7.1. This new feature offering includes the ability to encrypt network traffic using SSL, create and manage users, define roles that protect index and cluster-level access, and fully secure Kibana. Our getting started blog post that came out shortly after the release explains how to use TLS communication between Elasticsearch and Kibana.

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Welcome Endgame: Bringing Endpoint Security to the Elastic Stack

We are excited to announce that we have entered into an acquisition agreement to join forces with Endgame, Inc. an endpoint security company. We believe that by joining forces, we can bring to market a holistic security product that combines endpoint and SIEM, and is delivered using our unique go-to-market model.

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Tips to secure Elasticsearch clusters for free with encryption, users, and more

With the release of the Elastic Stack 6.8 and 7.1, we’ve made a number of Elasticsearch security features more widely available to everyone by making them free in the default distribution. We’re really excited to share this, but one of the new challenges now is to update all of our documentation and guidance on how to secure the Elastic Stack. Gone are the days of relying on just a proxy server in front of the Stack to secure it!

Deploy a Multi-node Elasticsearch Cluster With Kibana in Minikube Using the Elastic Helm Chart

In 2 minutes / 7 steps easily deploy a multi-node Elasticsearch cluster w/ Kibana in Kubernetes using Elastic Helm Charts. Dan Roscigno from Elastic will show you how to get started - from adding our Helm repo, to grabbing a values.yml for Minikube, to deploying the charts, and finally visualizing sample data in Kibana and enabling monitoring of the entire deployment.
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CDL: Visualising the power of data with Canvas and Elasticsearch

CDL is a top UK tech firm, listed in the Financial Times Future 100. Its customer base comprises high volume retail operations, including over 100 major Internet brands, meaning it processes vast amounts of consumer data in milliseconds. It does this by unlocking the potential of data to help financial services and other industries combat fraud and learn consumer habits.

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Observability of MuleSoft: Using Elastic APM to monitor Mule flows

This is the first post in a series about observability of the MuleSoft stack. I am planning to cover additional uses of the Elastic Stack with the MuleSoft stack in the future, including: Collecting and searching through Mule logs, CloudHub observability with Logstash, Using Canvas for picture-perfect dashboards