Opsani’s Performance
Optimization Report

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Background

Leading enterprises embrace automation because they know it’s key to overcoming the breakneck pace of digital change. But visionary enterprises optimize their IT operation processes by using big data, modern machine learning and other advanced analytics technologies to enable their organizations to become the masters of their competition. Their latest AIOps tools include machines and software intelligence that help DevOps and IT operation professionals do jobs more efficiently and invent a new future for their organization.

In this research, we look at how IT performance optimization is changing and what fundamental changes are required to address the needs of today’s modern digital enterprise.

The IT Performance Operations Paradox

63% of respondents cited that improving  ‘application performance’ is the most important priority for their organization

But a Majority Don’t Have…

the Capabilities to Support Tomorrow’s Application Performance Needs

71% either had limited or no ability to deploy AI

Challenge

1. Building a Proactive Performance Monitoring Approach in Today’s Complex IT Operations Environment

Performance Tuning Is No Longer Human Scale

Source: Gartner Survey Shows 37 Per cent of Organizations Have Implemented AI in Some Form January 21, 2019 

Where’s The Breakdown?

48% of respondents point to the manual time-consuming process as the biggest hurdle for organizations to optimize their applications.

For 69% of enterprises this is especially true.

Source: Microsoft Ignite survey 2 results

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Maximize IT Performance by Automating

Labor vs. Automation

Enterprises that only focus on adding talent to scale automation is costly.

SOURCE: GARTNER
2: Gartner’s IT Automation Predictions for 2019

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Challenge

2. Managing Change Without Leading To Fatigue  

Continuous Integration (CI) makes testing move faster and Continuous Delivery (CD) makes delivery faster

But how can you keep track of the volume of change and deliver optimization faster?

Where’s The Breakdown?

More than half of respondents (56%) say their organization has never optimized their application stack, or only when there is an issue 2

Yet less than half of organizations (22%) are confident of their apps running in the  cloud? 4

2: DockerCon and Velocity Combined Survey Results
4: Microsoft Ignite Survey 1 results

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Manage Change by Continuously Optimizing Your Entire Stack

As your system is released over and over, the cost of change will rise over time.

SOURCE: Kent Beck’s Cost of Change Curve

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Challenge

3. Driving faster and better decision-making with the business

As more enterprises increasingly support cloud services in terms of aggregation, customization, integration and governance, a big challenge is keeping costs under control, while driving faster, better decisions.

Rather than focusing solely on engineering and operations, I&O must develop the capabilities needed to broker IT services with the business strategy and performance.6

2: Gartner Survey Shows 37 Per cent of Organizations Have Implemented AI in Some Form January 21, 2019 

Where’s The Breakdown?

Almost 45% of organizations continue to release software in weekly, daily or hourly sprints 6

But most organizations (45%) have limited or no current ability to deploy AI tools that help make faster decisions 5

6: LTM survey results
5: KubeCon 2019 results  

 

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Increase Productivity by Aligning IT Performance with the Business

Many organizations use IT operation workarounds  which invite inefficiency and costs to skyrocket.

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Where are Digitally  Empowered Enterprises Headed?

Artificial Intelligence for IT Operations (AIOps)

  • 74% are using AIOPs to automate routine functions and avoid costly service disruptions with faster recovery.5
  • 73% are using AIOps capabilities to gain more meaningful insights from system generated and monitoring-related alerts.5
  • 68% of respondents are also applying AIOps to cut through the noise and determine the root cause of performance issues.5

5: OpsRamp blog 

AI Will Drive Infrastructure Decisions 

According to Gartner, global AI-derived business value will reach nearly $3.9 trillion by 2022

Analyst Predictions

Organizations are starting to move automation to a systematic approach. Gartner predicts that by 2023….. 

AI-enabled automation in data management will reduce the need for IT specialists by 20%” 2

40% of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability. 3

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Screenshot 2020-01-08 at 11.44.23 AM

As a result, data management practices are expected to change as organizations apply AI to simplify and automate data management, which includes automating tasks such as performance tuning and optimization.

As the amount of data that organizations have to manage increases, so too will the abundance of false alarms and ineffective problem prioritization. With the shortage of digital dexterity talent in I&O to effectively adopt AI, automation is a key solution. 

How Will Enterprises Get There?

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Adopt Deeper Automation Beyond Surface Level

As the amount of data that organizations have to manage increases, so too will the abundance of false alarms and ineffective problem prioritization. With the shortage of digital dexterity talent in I&O to effectively adopt AI, automation is a key solution. By 2023, 40% of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.

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Manage Complexity Through Collaboration

“One of the top technology challenges in leveraging AI techniques like machine learning (ML) or deep neural networks (DNN) in edge and IoT environments is the complexity of data and analytics. Tight collaboration between the business and IT functions require the help of internal engineering teams is a must.” 3

Are You Ready to Empower Your IT Operations and Lead the Industry?

Gain 235% in Efficiencies 

Opsani AI measures, predicts and implements changes to parameters and resource settings across the VM instance, middleware, application and containers to maximize performance and reduce costs autonomously when you:

  • Deploy new code
  • Evaluate new instance types
  • Experience changes in user patterns

The End

Sources:

SOURCE: GARTNER

1: Gartner, Gartner Survey Shows 37 Percent of Organizations Have Implemented AI in Some Form

January 21, 2019 

2: Gartner, “Gartner’s IT Automation Predictions for 2019”

3: Gartner, “Gartner Top 10 Strategic Technology Trends for 2020”

October 21, 2019

4: Gartner, “Gartner Top Strategic Predictions for 2019 and Beyond”

October 16, 2019

5: OpsRamp blog 

6: Gartner, “Gartner Identifies the Top 10 Trends Impacting Infrastructure and Operations for 2019” December 4, 2018