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What is Zipher?

Zipher represents a cutting-edge optimization platform that independently boosts the performance and affordability of workloads on Databricks by eliminating the necessity for manual resource management and tuning while simultaneously making live adjustments to clusters. Leveraging sophisticated proprietary machine learning algorithms, Zipher incorporates a distinct Spark-aware scaler that continuously learns from and analyzes workloads to identify optimal resource distributions, enhance job execution configurations, and fine-tune aspects such as hardware specifications, Spark settings, and availability zones, thus maximizing efficiency and reducing waste. The system consistently monitors evolving workloads to adapt configurations, improve scheduling, and effectively allocate shared computing resources, ensuring compliance with service level agreements (SLAs), while also providing detailed cost analysis that breaks down expenditures associated with Databricks and cloud services, allowing teams to identify key cost drivers. In addition, Zipher guarantees seamless integration with leading cloud providers such as AWS, Azure, and Google Cloud, and offers compatibility with widely-used orchestration and infrastructure-as-code (IaC) tools, establishing it as a flexible solution suitable for diverse cloud environments. By continuously adapting to fluctuations in workloads, Zipher distinguishes itself as an essential resource for organizations aiming to enhance their cloud operational strategies. This adaptability not only streamlines processes but also fosters a more sustainable approach to cloud resource utilization, ultimately driving better business outcomes.

What is AWS Auto Scaling?

AWS Auto Scaling is a service that consistently observes your applications and automatically modifies resource capacity to maintain steady performance while reducing expenses. This platform facilitates rapid and simple scaling of applications across multiple resources and services within a matter of minutes. It boasts a user-friendly interface that allows users to develop scaling plans for various resources, such as Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. By providing customized recommendations, AWS Auto Scaling simplifies the task of enhancing both performance and cost-effectiveness, allowing users to strike a balance between the two. Additionally, if you are employing Amazon EC2 Auto Scaling for your EC2 instances, you can effortlessly integrate it with AWS Auto Scaling to broaden scalability across other AWS services. This integration guarantees that your applications are always provisioned with the necessary resources exactly when required. Ultimately, AWS Auto Scaling enables developers to prioritize the creation of their applications without the burden of managing infrastructure requirements, thus fostering innovation and efficiency in their projects. By minimizing operational complexities, it allows teams to focus more on delivering value and enhancing user experiences.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
AWS Secrets Manager
Amazon CloudWatch
Amazon DynamoDB
Amazon EC2
Amazon Elastic Container Service (Amazon ECS)
Amazon Fresh
Ant Media Server
Apache Airflow
Azure Data Factory
Beats
EC2 Spot
Ease Stream
Observe
Slack
Suntek Reporting
Sweven
Terraform
WebLOAD
dbt

Integrations Supported

Amazon Web Services (AWS)
AWS Secrets Manager
Amazon CloudWatch
Amazon DynamoDB
Amazon EC2
Amazon Elastic Container Service (Amazon ECS)
Amazon Fresh
Ant Media Server
Apache Airflow
Azure Data Factory
Beats
EC2 Spot
Ease Stream
Observe
Slack
Suntek Reporting
Sweven
Terraform
WebLOAD
dbt

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard 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

Zipher

Date Founded

2023

Company Location

United States

Company Website

zipher.cloud/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/autoscaling/

Categories and Features

Server Management

CPU Monitoring
Credential Management
Database Servers
Email Monitoring
Event Logs
History Tracking
Patch Management
Scheduling
User Activity Monitoring
Virtual Machine Monitoring

Server Virtualization

Audit Management
Health Monitoring
Live Machine Migration
Multi-OS Virtual Machines
Patching / Backup
Performance Log
Performance Optimization
Rapid Provisioning
Security Management
Type 1 / Type 2 Hypervisor

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