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What is OpsMx Enterprise for Spinnaker?

OES is designed with high availability and scalability, making it ideal for handling increasing deployment workloads while being flexible enough to integrate smoothly with diverse SDLC toolchains. The platform offers an intuitive interface that enables users to define custom stages for executing multiple deployments simultaneously, which greatly minimizes the time required for deployment tasks. Users can easily perform actions such as rolling back, advancing, or pausing all concurrent deployments with just a click, simplifying the management process. Furthermore, OES facilitates the automation of repetitive tasks within the SDLC by allowing the creation of multiple child pipelines that can be initiated from a parent pipeline. Its modular design and API-driven architecture enable OES to serve as a central Continuous Delivery (CD) tool for many organizations. This adaptability also allows developers from different teams to effortlessly link external services with Spinnaker, leading to improved deployment orchestration and enhanced collaboration. Ultimately, OES emerges as a robust solution for refining deployment procedures across a variety of environments, ensuring that teams can respond swiftly to changes in their workflows and project demands. The platform's capability to streamline processes not only boosts productivity but also fosters a more integrated development environment.

What is EC2 Spot?

Amazon EC2 Spot Instances enable users to tap into the unused capacity of the AWS cloud, offering remarkable savings that can reach up to 90% when compared to standard On-Demand pricing. These instances are suitable for various applications that are stateless, resilient, or flexible, such as big data analytics, containerized workloads, continuous integration and delivery (CI/CD), web hosting, high-performance computing (HPC), as well as for development and testing purposes. The effortless integration of Spot Instances with a variety of AWS services—including Auto Scaling, EMR, ECS, CloudFormation, Data Pipeline, and AWS Batch—facilitates efficient application deployment and management. Furthermore, by utilizing a combination of Spot Instances alongside On-Demand and Reserved Instances (RIs), as well as Savings Plans, users can significantly enhance both cost efficiency and performance. The extensive operational capacity of AWS allows Spot Instances to provide considerable scalability and cost advantages for handling large-scale workloads. Consequently, this inherent flexibility and the potential for cost reductions make Spot Instances an appealing option for organizations aiming to optimize their cloud expenditures while maximizing resource utilization. As companies increasingly seek ways to manage their cloud costs effectively, the strategic use of Spot Instances can play a pivotal role in their overall cloud strategy.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Amazon S3
Apache Mesos
Checkmarx
Datadog
Docker
GitHub
GitLab
HashiCorp Vault
Kubernetes
Microsoft Azure
New Relic
Oracle Cloud Infrastructure
PagerDuty
Puppet Enterprise
Slack
Sumo Logic
Terraform
Twilio

Integrations Supported

Amazon Web Services (AWS)
AWS CloudFormation

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$0.01 per user, one-time payment,

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

OpsMx

Date Founded

2017

Company Location

United States

Company Website

www.opsmx.com/opsmx-enterprise-spinnaker/scalable-and-extensible/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/spot/

Categories and Features

Categories and Features

Big Data

Data Blends
Data Cleansing
Data Mining
Data Warehousing
High Volume Processing
Predictive Analytics

Continuous Integration

Continuous Delivery
Continuous Deployment

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