Google Elastic Cloud

  • Author: Ronald Fung

  • Creation Date: 9 June 2023

  • Next Modified Date: 9 June 2024

A. Introduction

Elastic is the leading platform for search-powered solutions. We help you find what you’re looking for to accelerate results that matter.

With solutions in Enterprise Search, Observability, and Security, Elastic helps you enhance customer and employee search experiences, keep mission-critical applications running smoothly, and protect against cyber threats. Elastic Cloud is the best way to consume all of Elastic’s products across any cloud.

B. How is it used at Seagen

Seagen can use Google Cloud Elastic Cloud to run their applications on a scalable, reliable, and secure infrastructure. Here are some steps to get started with Google Cloud Elastic Cloud:

  1. Create a Google Cloud account: Seagen can create a Google Cloud account in the Google Cloud Console. This will give them access to Google Cloud Elastic Cloud and other Google Cloud services.

  2. Create an Elastic Cloud cluster: Seagen can create an Elastic Cloud cluster in the Google Cloud Console, which represents a group of virtual machines that can run their applications. They can specify the cluster size, region, and other cluster settings.

  3. Deploy the application: Seagen can deploy their application to the Elastic Cloud cluster using a variety of deployment methods, such as Docker containers, Kubernetes, or App Engine. They can specify the application configuration, such as the environment variables, ports, and network settings.

  4. Monitor the application: Seagen can monitor their application using Google Cloud Monitoring, which provides real-time visibility into their application performance, resource utilization, and other metrics. They can set up alerts, dashboards, and reports to track their application health and performance.

  5. Scale the cluster: Seagen can scale their Elastic Cloud cluster up or down as needed, to handle changes in traffic or workload. They can add or remove virtual machines from the cluster, or configure auto-scaling policies based on metrics such as CPU usage or network traffic.

  6. Secure the cluster: Seagen can secure their Elastic Cloud cluster using Google Cloud Identity and Access Management, which provides fine-grained access control and security policies. They can configure firewall rules, SSL certificates, and other security measures to protect their application and data.

Overall, by using Google Cloud Elastic Cloud, Seagen can run their applications on a scalable, reliable, and secure infrastructure, and focus on their core business instead of managing their own IT infrastructure. With its support for different deployment methods, powerful monitoring and scaling capabilities, and easy-to-use interface, Google Cloud Elastic Cloud is an excellent choice for businesses and individuals who need to deploy and scale their applications quickly and efficiently.

C. Features

Elastic Observability

Bring logs, metrics (from servers, containers, and databases), and traces from your applications and infrastructure together at scale in a single stack. Monitor all your cloud resources and applications, as well as services you use including, but not limited to, those on Google Cloud.

Elastic Security

Stop threats quickly and at cloud scale, with a best-in-class platform for prevention, detection, and response, including SIEM, endpoints, and containers.

D. Where Implemented

LeanIX

E. How it is tested

Testing Google Cloud Elastic Cloud involves ensuring that the applications are running correctly, that the cluster is scalable and reliable, and that the security and compliance controls are properly configured. Here are some steps to test Google Cloud Elastic Cloud:

  1. Create a test application: Create a test application that mimics the production application as closely as possible, including the application configuration, environment variables, and network settings.

  2. Create a test Elastic Cloud cluster: Create a test Elastic Cloud cluster that mimics the production cluster as closely as possible, including the cluster size, region, and other cluster settings.

  3. Deploy the application: Deploy the test application to the Elastic Cloud cluster using the same deployment method as the production application, such as Docker containers, Kubernetes, or App Engine.

  4. Monitor the application: Monitor the test application using Google Cloud Monitoring, which provides real-time visibility into the application performance, resource utilization, and other metrics. Set up alerts, dashboards, and reports to track the application health and performance.

  5. Scale the cluster: Scale the test Elastic Cloud cluster up or down as needed, to handle changes in traffic or workload. Add or remove virtual machines from the cluster, or configure auto-scaling policies based on metrics such as CPU usage or network traffic.

  6. Verify the security and compliance: Verify that the test Elastic Cloud cluster is secure and compliant with industry and regulatory standards, such as HIPAA. Configure firewall rules, SSL certificates, and other security measures to protect the application and data.

  7. Repeat the process: Repeat the process as needed, creating additional test applications and cluster scenarios to test different deployment methods or to simulate different application usage scenarios.

Overall, by thoroughly testing Google Cloud Elastic Cloud, users can ensure that their applications are reliable, scalable, and secure, and that they are complying with industry and regulatory standards. Additionally, users can reach out to Google Cloud support for help with any technical challenges they may encounter.

F. 2023 Roadmap

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G. 2024 Roadmap

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H. Known Issues

While Google Cloud Elastic Cloud is a reliable and powerful platform for running applications at scale, there are some known issues that users may encounter. Here are some of the known issues for Google Cloud Elastic Cloud:

  1. Performance issues: Users may encounter performance issues with Elastic Cloud, such as slow application response times or high resource utilization. These issues can often be resolved by optimizing the application configuration, such as using the appropriate machine types or adjusting the application settings.

  2. Availability issues: Users may encounter availability issues with Elastic Cloud, such as downtime or service disruptions. These issues can often be resolved by configuring the appropriate high availability and fault tolerance mechanisms, such as load balancing, auto-scaling, and multi-zone deployment.

  3. Security issues: Users may encounter security issues with Elastic Cloud, such as data breaches or unauthorized access. These issues can often be resolved by implementing the appropriate security and compliance controls, such as encryption, access control, and auditing.

  4. Integration issues: Users may encounter integration issues with Elastic Cloud, such as interoperability issues or compatibility issues with other systems. These issues can often be resolved by using the appropriate integration standards, such as REST APIs or messaging protocols, and ensuring that the application is compatible with other systems.

  5. Cost issues: Users may encounter cost issues with Elastic Cloud, such as unexpected charges or inefficient resource utilization. These issues can often be resolved by optimizing the application and cluster configuration, such as using the appropriate machine types, storage options, and pricing models.

Overall, while these issues may impact some users, Google Cloud Elastic Cloud remains a reliable and powerful platform for running applications at scale that is widely used by businesses and organizations around the world. By monitoring their Elastic Cloud usage and reviewing their usage reports and logs, users can ensure that their applications are secure, scalable, and cost-effective, and that they are complying with industry and regulatory standards. Additionally, users can reach out to Google Cloud support for help with any known issues or other technical challenges they may encounter.

[x] Reviewed by Enterprise Architecture

[x] Reviewed by Application Development

[x] Reviewed by Data Architecture