Orchestration
GigaSpaces provides several orchestration
This is the automated configuration, management, and coordination of computer systems, applications, and services. Orchestration strings together multiple tasks in order to execute and easily manage a larger workflow or process. These processes can consist of multiple complex tasks that are automated and can involve multiple systems. Kubernetes, used by GigaSpaces, is a popular open source platform for container orchestration. options so that you can deploy GigaSpaces wherever it suits your needs; locally, on-premise, in the cloud, or in a hybrid environment.
- Standalone - a simple cluster manager that makes it easy to set up a cluster.
- Kubernetes An open-source container orchestration system for automating software deployment, scaling, and management.- the GigaSpaces implementation of the Kubernetes open-source system that automates deploying, scaling, and managing containerized applications.
- ServiceGrid - on-premise orchestration for deploying and managing virtualized applications.
Standalone Mode
This is a simple cluster manager that creates a cluster on your local machine. Use standalone mode to evaluate GigaSpaces products, or during development and testing.
Kubernetes
GigaSpaces products can be deployed in Kubernetes. Kubernetes can be used in any type of environment (on-premise, cloud, or hybrid) and is supported by every major cloud provider, including public cloud platforms like AWS, Microsoft Azure, and GCP.
Benefits of using Kubernetes include:
- The ability to deploy GigaSpaces-based applications in whatever environment best suits the business needs of the enterprise.
- Kubernetes synergizes with GigaSpaces products, simplifying the operationalizing of machine learning and transactional processing at scale.
- GigaSpaces utilizes key features of Kubernetes, such as cloud-native orchestration automation with self-healing, cooperative multi-tenancy, and RBAC Role-based access control (RBAC), also known as role-based security, is a mechanism that restricts system access. It involves setting permissions and privileges to enable access to authorized users. authorization.
- Auto-deployment of data services and deep learning and machine learning frameworks, such as Apache Spark jobs, stateful services (Processing Units This is the unit of packaging and deployment in the GigaSpaces Data Grid, and is essentially the main GigaSpaces service. The Processing Unit (PU) itself is typically deployed onto the Service Grid. When a Processing Unit is deployed, a Processing Unit instance is the actual runtime entity.), as well as the Apache Zeppelin web notebook.
Service Grid
The service grid is an on-premise system for deploying and managing virtualized applications. This orchestration method is responsible for materializing the configuration of the Processing Units, provisioning the instances to the runtime infrastructure, and making sure they continue to run properly over time. Core components of the Service Grid A built-in orchestration tool which contains a set of Grid Service Containers (GSCs) managed by a Grid Service Manager. The containers host various deployments of Processing Units and data grids. Each container can be run on a separate physical machine. This orchestration is available for Smart Cache only. For Smart DIH, we recommend using our Kubernetes orchestration. include the Grid Service Manager, Grid Service Agent, and the GigaSpaces Manager.
Orchestration Option Comparison
You can compare the following parameters between the orchestration options, in order to determine which one best suits your needs:
- Zero configuration required - Can you deploy and run GigaSpaces on demand, or easily on existing machines?
- Auto provisioning - Can you start a cluster from zero?
- Auto-scaling - Does the environment dynamically allocate/de-allocate resources (memory, compute and storage) as well as add or remove nodes?
- Ease of use - How easy is it to configure network and security requirements?
- Support for GigaSpaces product evolution - Can you perform a gradual and controlled upgrade process for the product version and/or microservices? Can you evaluate the effect of your upgrade and of application changes?
- Supported environments - Can your cluster run across regions and multi-cloud providers?
- Supported apps - What type of applications are supported (container or virtualized process)?
- Troubleshooting - Can you monitor your system, get alerts, and obtain and analyze tracing and centralized logging for your system and applications?
| Parameter | Kubernetes | Service Grid |
|---|---|---|
| Zero configuration required | No | Yes |
| Auto-provisioning | No | No |
| Auto-scaling | Yes | No |
| Ease of use (network and security configuration) | No | Yes |
| Supports rolling upgrades | Yes | No |
| Supports canary deployments | Yes | No |
| Includes distributed tracing | No | No |
| Supported environments | ||
| Cloud | Yes | No |
| On premise | Yes | Yes |
| Hybrid or multi-cloud | No | No |
| Supported applications | ||
| Container | Yes | No |
| VM | No | Yes |
| Container + VM | No | No |
| Out-of-the-box monitoring and alerts | Yes | No |
| Centralized log processing | Yes | No |
| Distributed tracing | No | No |