Solutions
BEZNext offers software and services optimizing Cloud Decisions
We are experts in Modeling and Performance Optimization
BEZNext offers cloud decisions optimization software and services for right cloud data platform selection, migration to cloud and Dynamic Capacity Management software and services for Data Warehouse and Big Data applications working in Hybrid On Prem and Cloud environments.
Our software and services automate data collection, workload aggregation, characterization and forecasting Determine performance and financial anomalies and root causes Apply modeling to evaluate options and optimize decisions Modeling results set realistic performance and financial expectations Automatic results verification compares actual measurement performance and financial data with expected Decisions based on modeling and optimization reduce uncertainty, increase confidence and reduce the risk of performance and financial surprises It enables better collaboration between business representatives and IT Leaders
BEZNext Cloud Performance and Financial Governance Functions
BEZNext Cost Performance Assurance Solutions
Our History
- We’ve offered capacity management software and services for large data warehouses on Teradata, DB2, Oracle, and SQL Server for long time
- We added Big Data (Hadoop) support in 2014
- We added Cloud Data platforms support in 2017
The Need
- Customers feel uncertainty about cost and performance while making strategic decisions about cloud selection, migration to the cloud and management of multi-cloud environments
- Organizations are concerned with performance and cost prior to deployment of new applications
Current Focus
- We enhanced our modeling and optimization software to optimize performance and financial governance of Hybrid Multi-Cloud environments
- DevOps decisions optimization prior to deployment of new applications
- Typical cloud selection project takes 2-3 weeks instead of 6-9 months POC studies
- Our goal is to reduce the uncertainty and risk of performance and financial surprises
BEZNext Technology Optimizes Cloud Performance and Financial Governance
- Migrating a data warehouse workload to the cloud requires selecting the right cloud data platform, planning migration workloads to the cloud, and optimizing management decisions in the cloud.
- Each Data Warehouse workload includes a group of applications supporting a specific Line of Business. Each workload can be characterized by performance, resource utilization, and data usage profiles, changing during day hours and months of the year.
- These profiles help select candidates for migration to the cloud, and the most appropriate cloud data platform, evaluate migration options, and optimize capacity management decisions. Organizations have many cloud data platform options, migration options, and options for organizing dynamic capacity management in a complex Hybrid Multi-Cloud environment.
- Wrong decisions might affect the cost, performance, and business success, and organizations are concerned with finding a way to reduce uncertainty and risk of performance and financial surprises.
- BEZNext software automates data collection, workload aggregation, characterization, and forecasting, It determines performance, financial anomalies, and root causes.
- Then the Iterative Queueing Network Modeling, Gradient optimization evaluates options and determines solutions capable of meeting SLGs with the lowest cost
- Iterative Queuing Network Modeling and Gradient Optimization determine:
- Modeling results set realistic performance and financial expectations, and automatic results verification compares the actual performance and financial data with expected I
- It increases decisions confidence, reduces the risk of performance and financial surprises, and enables better collaboration between business representatives and IT Leaders.
- The minimum configuration and budget required to meet SLGs for all workloads on different cloud data platforms
- Migration to the cloud decisions optimization
- Dynamic capacity management measures necessary to continuously meet SLGs of changing and growing workloads, number of users, deployment of new workloads and increasing the volume of data
- Automatic verification of results by comparing performance and financial measurement data with expected
- Close loop feedback control through the model modification and development corrective recommendation
Illustration of Modeling and Gradient Optimization determining
the minimum configuration required to meet SLGs for all business workloads
Cloud Data Platform Selection
Assist with an appropriate Cloud Data Platform selection for on-prem workload
- Predict the minimum configuration and budget required to meet SLGs for each of the workload on each cloud data platform Take into consideration the change in resource demand pattern during different hours of the day and expected workload and volume of data growth during next 12 months.
- Differences in cloud data platforms architecture The security implication and tokenization overhead
Review our white paper on "Which Cloud Data Platform is Best for Your Data Warehouse?":
Migration Decisions Optimization
How do we assist with cloud migration decisions optimization
- Assist with creation Migration Plan and predict performance and budget required to meet business goals
- Evaluate Security Tokenization options and compare their impact on performance and cost
- Evaluate ETL options and predict how different options will affect performance and cost
- Evaluate the impact of Data and Applications consolidation and it’s impact on performance and cost
ETL Migration Optimization
Tokenization Considerations:
Modeling and Optimization optimizing application development and operational decisions prior to new applications deployment
Cost/Performance Optimization During Dev/Ops
Recommendations to Application Developers during DevOps process prior to new Application deployment
- Determine anomalies and root causes during testing of new applications prior to deployment
- Develop tuning recommendations
Recommendations to Operations during DevOps prior to deployment of new Application
Select cloud data platform for new application prior to deployment
- Predict the minimum configuration and budget required for deployment of the new application on different cloud data platforms, taking into consideration
- Expected increase in number of concurrent users and volume of data after deployment comparing with the test environment
- Response Time SLG
Set up realistic performance and financial expectations Organize process of verification of results and development proactive recommendations
Verify results
Optimization Dynamic Capacity Management
- Dynamic capacity management is a continuous process controlling resource allocation, workload management, decisions optimization, and verification of results During and after migration to the cloud, organizations face the challenge of managing complex Hybrid Multi-Cloud environments to support performance and financial SLGs for changing and growing workloads and volume of data: • Predict the realistic budget to satisfy SLG for growing workloads on each platform. • Determine performance and financial anomalies and their root causes for each workload on each cloud data platform, changes in the resource demand pattern, and present workload management and resource allocation recommendations on how to meet SLGs with the lowest cost • Predict the impact of new application deployment and develop proactive performance and financial recommendations for developers and operations.
- Objective is to determine Performance and Financial Anomalies and Root Causes
- Allocate sufficient resources on each Cloud to meet SLGs for all business workloads with lowest cost
- Create realistic Budget
- Verify results
- Modify resource allocation and workload management rules to control performance and Cost
- BEZNext software optimizes the resource allocation and workload management rules to meet SLGs for each workload on each platform with the lowest cost
- We automate Data Collection, Workload Characterization and discovery of the most frequent and severe performance and financial anomalies and root causes on each platform for each workload, changes in pattern of resource utilization
- We apply iterative modeling and gradient performance optimization to compare options and develop proactive performance tuning, resource allocation and workload management recommendations
- Automatic results verification achieved by comparing the actual measurement data with expected / predicted results
- Feedback control enables continuous Dynamic Capacity Management
BEZNext Offers Hands-On Workshop on Cloud Performance and Financial Governance
Description
- Cloud platform selection, migration workloads to the cloud, and dynamic capacity management of hybrid multi-cloud environments
- Nine hours of instruction and hands-on learning delivered over three weeks (three hours per week).
- Workshop includes instructor-led lectures, videos, quizzes and lab exercises
- The lab exercises will give students first-hand knowledge of the skills needed to effectively select and manage cloud platforms
- Participants will have access to BEZNext modeling and optimization software
- Participants will run and modify Python program to compare several ML algorithms of anomaly detection.
Workshop participants will learn how to:
- Collect measurement data on-prem and cloud platforms.
- Perform workload characterization
- Detect anomalies and their root causes
- Determine seasonality for each workload
- Predict the minimum configuration and cost required to meet SLAs for each workload on each platform
- Analyze Workload Patterns and Resource Management
- Organize continuous Dynamic Capacity Management to meet SLAs for each workload on each platform.
Prerequisites
- This workshop designed for participants who understand Cloud capabilities and have had exposure to Data Warehouse performance management.
Audience, Who should attend:
- This workshop is for managers, architect, analysts, DBAs, etc. who participate in Cloud Data platform selection and management of the Hybrid Multi-Cloud environments. For the complete program description, please download the workshop brochure here.