Name: Akamas
Author: Akamas

Help Desk

Web and Video Conferencing

Customer Support

Innovation Management

PHP Frameworks

Development

Business Intelligence (BI)

Collaboration

Manufacturing Execution

Payment Facilitation

Quality Management

Enterprise

Accounting

Blockchain Payments

Merger and Acquisition

Payment Hubs

Finance and Accounting

Applicant Tracking

Corporate Learning Management

Employer of Record (EOR)

HR Management

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AIOps

Bot Mitigation

Cloud Storage

Container Security

Data Center Outsourcing (Canada)

Data Center Power

Data Replication

Endpoint Security

Firewall

Fraud Detection

Graph Database

Infrastructure-as-a-Service

Integration Platform as a Service (iPaaS)

LAN Switches

Mobile Data Security

Network Performance Monitoring

Network Troubleshooting

SQL Server Performance Monitoring

Scale-Out Storage

Secure Access Control

Smart Contracts

Testing Services

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Content Management

Email Marketing

Grant Management Software

IP Geolocation

Marketing Attribution

Marketing Automation

Social Media Management

Survey & Forms Building

Translation

Web Analytics

Marketing

Project Management

Task Management

Professional Services

Customer Relationship Management (CRM)

Intelligent Virtual Assistant

Sales Dialer

Sales Training

Sales

Data-Centric Audit Protection (DCAP)

Security

Aviation

Emergency Notification

Fleet Maintenance

Hospital Management

Hotel Management

Retail Analytics

Revenue Cycle Management (RCM)

Shipping

Veterinary

Warranty Management

Vertical-Specific

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Akamas is an AI-powered optimization platform developed by Akamas S.p.A. The platform aims to assist organizations in maximizing the performance, resilience, and cost efficiency of their applications. It caters to businesses of all sizes, ranging from small startups to large enterprises, and is utilized by professionals such as Performance Engineers, Site Reliability Engineers (SRE), DevOps Engineers, IT Operations Managers, and Cloud Architects. It is applicable across various industries, including IT Services, Financial Services, Online Services, Travel and Hospitality, and E-commerce.

## Key Features

**Autonomous Optimization**: Akamas leverages AI to autonomously identify optimal configurations that enhance application performance, resilience, and cost efficiency. It provides recommendations based on custom-defined goals and constraints, making it suitable for live production environments and planned scenarios.

**Application-aware Optimization**: Akamas considers the specific requirements and characteristics of each application to recommend configurations that maximize service quality. It takes into account factors such as workload, resource utilization, and performance metrics. User-defined goals and constraints ensure the best tradeoffs between performance, resilience, and cost efficiency.

**Kubernetes Optimization**: Akamas offers Kubernetes optimization to improve the cost efficiency and performance of Kubernetes applications. It addresses the complexities of resource management at the container and runtime layers in Kubernetes. By minimizing container and pod resources while improving response time and throughput, Akamas reduces business risks and costs.

**Runtime Optimization**: Akamas provides runtime optimization to boost application performance without requiring code changes. It optimizes JVM and Golang parameters to improve agility and efficiency. The AI-powered optimization process identifies the best runtime configurations to achieve higher levels of performance and resilience.

**Cloud Optimization**: Akamas helps organizations reduce cloud costs and improve service quality through application-aware optimization. It goes beyond traditional cloud cost optimization tools by considering real application demand and its impact on performance. Akamas identifies instances in Amazon EC2, Google Cloud Platform (GCP), and Microsoft Azure that maximize cost efficiency and end-to-end performance.

**Big Data Optimization**: Akamas optimizes Spark jobs to make them run faster and more cost-effective. It considers factors such as job size, data volumes, and other variables that impact completion time and execution windows. By finding optimal configurations for Spark, AWS EMR, and Google DataProc, Akamas minimizes resource usage and reduces costs while meeting service level objectives (SLOs).

**Closed-loop Automation**: Akamas supports closed-loop automation by seamlessly integrating with existing change and delivery processes. Configurations can be approved and reviewed by humans, applied in CI/CD pipelines, or autonomously implemented by Akamas. Its Infrastructure-as-Code approach and comprehensive set of APIs and integration mechanisms enable smooth integration with any ecosystem.

**Full-stack Optimization**: Akamas optimizes any application, workload, and infrastructure, whether on-premise or in the cloud. It covers the full stack, including applications, runtimes, containers, middleware, databases, and cloud parameters. Akamas provides out-of-the-box Optimization Packs for key technologies, and custom Optimization Packs can be created without any coding.

**Custom Goals and Constraints**: Akamas allows users to define custom goals and constraints to guide the optimization process. Users can specify their desired tradeoffs between performance, resilience, and cost efficiency. The optimization recommendations provided by Akamas are tailored to meet these customized goals and constraints.

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Full-Stack Monitoring

Infrastructure Monitoring

Kubernetes Platform Monitoring

Application Security

Real User Monitoring

Synthetic Monitoring

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Akamas

Application Performance Management (APM)

Application Performance Management

Application performance management software monitors software to ensure performance and availability

Application monitoring

Application monitoring involves tracking response times and resource usage for applications, including highly-distributed applications

Database monitoring

Database monitoring means looking for database bottlenecks liable to slow response times

Threshold alerts

Alerts indicating when critical thresholds have been reached

Predictive capabilities

Data mining of log and other performance data to understand predictors of slowdowns or outages

Application performance management console

The management console is used to manage monitoring agents and et thresholds, etc.

Collaboration tools

Collaboration tools enable DevOps staff to collaborate by adding notes/comments and also integrating with external collaboration tools like ticketing systems

Out-of-the box templates to monitor applications

Built-in templates for specific applications

Application dependency mapping and thresholding

Mapping relationships between the application and its underlying infrastructure

Virtualization monitoring

Allows for monitoring of virtual applications and servers

Server availability and performance monitoring

Server usage monitoring and capacity forecasting

Ability to assess server usage and forecast future needs

IT Asset Discovery

Discovery of hardware and software assets on the network

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Akamas

Overview

What is Akamas?