Elasticsearch is a search and analytics tool capable of near-instant search and deep-dive analytics for any type of data.

Elasticsearch is based on the ELK stack: Elasticsearch – the search engine, Logstash – the database where data is stored and parsed, and Kibana – the visualization tool. Additionally, Elastic has the Beats solution which gathers file logs, network data, Windows event logs or uptime for systems.

With the recent addition of X-Pack, the capabilities of Elasticsearch have increased to create machine learning jobs and personalized notifications for different types of events.

Our Elasticsearch expertise includes:

  • Data collection;
  • Data parsing;
  • Data modeling into visualizations and dashboards;
  • Machine learning jobs;
  • Custom development;
  • Watcher notifications;
  • Cluster Upgrades.

This service covers gathering data, cleaning it, enriching it, parsing it and modeling it into visualizations and dashboards.

Based on your desired goal, we will implement the ELK stack into your infrastructure together with the appropriate Beats solution in order to start gathering data. This data is then brought to a generalized format through parsing to make it easier to model. 

Using the parsed data, we create visualizations and put them together into dashboards to help you extract actionable information.

Added to this are Machine Learning capabilities that help you find patterns and anomalies within your data.

Monitoring can cover the following areas:

  • Infrastructure
  • Cluster
  • Application Performance
  • Security

All of the above will be actively monitored with the help of the appropriate Beats solution and detailed in Kibana visualizations. In addition to visualizing the state of your infrastructure, personalized notifications can be sent at different thresholds in order for immediate action to be taken.

With the recent addition of X-pack, Elasticsearch’s security capabilities have increased greatly.

By gathering and analyzing data from within your infrastructure various security threats or vulnerabilities can be indentified. These vulnerabilities can be signald through personalized notifications as they happen for quicker response time. In addition, by implementing machine learning jobs, anomalies within data can be found indicating unwanted behaviour from either within the organization hinting to an insider threat or from outside the organization hinting at a possible security breach.

For a list of our certifications click here.