Elastic on GCP

by Justin Cook

Elasticsearch is a popular NoSQL database based on the open-source Lucene search engine, which facilitates fast search across large datasets. Elasticsearch provides the Elastic on Google Cloud solution, which lets you deploy Elasticsearch clusters on the Google Cloud Platform. It supports four deployment options, which provide different capabilities:

• Elastic Enterprise Search — lets you create customized search experience, ingesting any data format, from storage services based on Google Cloud or elsewhere.

• Elastic Observability — lets you visualize log and metrics data, analyze it, identify anomalies in real time and respond to them.

• Elastic Security — lets you monitor IT environments, integrating with SIEM integration and endpoint protection solutions. This Elasticsearch deployment model provides a machine learning engine that helps identify misconfigurations and attacks against your infrastructure.

• Elastic Stack — a “plain van

But what if you are GCP shop, and want to deploy this as soon as possible?

On Google Cloud Platform (GCP), Elasticsearch is provided as a managed service through Elastic Cloud. It allows you to deploy, manage, and scale Elasticsearch clusters without having to handle the complexities of setting up, configuring, and maintaining the underlying infrastructure.

Here’s what you need to know about Elasticsearch on GCP:

1. Elastic Cloud (Managed Service):

• Elastic Cloud is the official managed service for Elasticsearch and is offered by Elastic (the company behind Elasticsearch).

• It is fully integrated with GCP and can be used to deploy Elasticsearch clusters with just a few clicks through the Elastic Cloud Console or through the GCP Marketplace.

• Elastic Cloud also provides other Elastic Stack components, such as Kibana for data visualization and Beats and Logstash for data shipping and transformation.

2. Features:

• Managed Deployment: Elastic Cloud on GCP takes care of the operational aspects like provisioning, scaling, and patching Elasticsearch clusters, allowing you to focus on your application.

• Scalability: You can easily scale your Elasticsearch cluster up or down depending on your needs.

• Security: Elastic Cloud offers built-in security features such as encryption, access control, and secure communication between cluster nodes.

• Kibana Integration: Kibana, the visualization tool for Elasticsearch, is included and can be used to explore and visualize the data stored in your Elasticsearch cluster.

3. Integration with Google Cloud Services:

• Logging & Monitoring: Elasticsearch on GCP is often used in combination with other GCP services like Google Cloud Logging(formerly Stackdriver), Google Cloud Monitoring, and Google Cloud Pub/Sub. This allows for centralized log analysis, monitoring, and event processing.

• BigQuery Integration: Elasticsearch can be used alongside BigQuery for data warehousing and analytics, providing a powerful combination for search and analytics workflows.

• Machine Learning: You can integrate Elasticsearch with Google Cloud AIand Machine Learning APIs to perform advanced analytics on the data.

4. Elastic Stack:

• When using Elasticsearch on GCP, you’re often working with the Elastic Stack (previously known as the ELK Stack), which includes:

• Elasticsearch: The search and analytics engine.

• Kibana: For visualizing and analyzing the data stored in Elasticsearch.

• Logstash: A data collection and processing pipeline that can ingest data from various sources.

• Beats: Lightweight data shippers for various types of data, such as logs, metrics, and network data.

5. Use Cases:

• Log and Event Data Analysis: Collecting logs and monitoring data from applications, servers, and devices.

• Full-Text Search: Providing powerful search capabilities on websites, applications, or large document stores.

• Data Analytics: Performing real-time analytics on structured and unstructured data.

• Security Information and Event Management (SIEM): Storing, analyzing, and visualizing security data for real-time threat detection.

6. Billing and Pricing:

• Elasticsearch on GCP is typically billed based on resource usage, including storage, CPU, and memory for the deployed clusters. Elastic Cloud offers flexible pricing plans that can be tailored to your specific usage patterns.

7. Deployment via GCP Marketplace:

• Elasticsearch can be deployed directly through the Google Cloud Marketplace, which provides pre-configured solutions for easy setup. The marketplace also offers additional integration options with other Google Cloud services.

I would try out Elasticsearch on GCP alone for the scalable search and analytics engine that integrates well with other Google Cloud services. It’s a great choice for anyone looking to run Elasticsearch without managing the infrastructure themselves while still being able to leverage Google Cloud’s powerful ecosystem.