Transform initiatives

Automation and AIOps

Prevent and resolve IT outages

BigPanda assists enterprises and their ITOps teams in adopting AI/ML automation. Through our Open Box Machine Learning technology, which automates incident management, BigPanda promotes trust and encourages usage by providing transparent, testable, and controllable AI/ML that enterprises can adopt at their own pace.

Why enterprises are embracing Automation and AIOps

Companies are looking to take advantage of this trend and are consequently making considerable investments in Automation across all departments, including IT Operations, where the application of AI/ML to IT Operations is commonly called AIOps.

Enterprises adopting AIOps are doing so because they want to achieve one or more of these goals:

Cost efficiency and team productivity
Improved system performance and lower MTTR
Improved IT Ops reliability, through reduction or elimination of human errors.

The barriers to adopting automation and AIOps successfully

Manual processes = IT Ops pain

Problem

Automating different aspects of the incident management lifecycle is hard

The incident management lifecycle is complex, and consists of several different phases, with each phase relying on different tools and teams.
It’s difficult to automate different aspects of this without resorting to hundreds of hard to create, hard to maintain, and routinely out-of-date rules. This applies both to correlation rules and workflow automation rules.

Negative impact on the business:

Increased operating costs: Without automation, IT Ops, NOC and DevOps teams resort to manual steps and processes across different stages of the incident management lifecycle. As a result:

the volume of alerts generated in modern IT environments requires organizations to grow headcount to handle their incidents and outages, increasing costs.
manual workflows, incidents and outages last longer, increasing downtime related costs.

Performance and availability problems: Because of manual workflows, and the lack of AI-driven automation, incidents and outages last longer, frustrating customers, users and different business units.

BigPanda’s solution

Automates different aspects of the incident management lifecycle

BigPanda uses machine learning (BigPanda’s unique implementation of it is called Open Box Machine Learning) to streamline and automate various aspects of the incident management lifecycle, including correlation, problem detection, root cause analysis, prioritization, sharing, routing and remediation.

Positive impact on the business:

Reduced operating costs: BigPanda’s Open Box Machine Learning-driven automation:

reduces costs by enabling existing enterprise IT Ops, NOC, DevOps and SRE teams handle significantly higher volumes of IT alerts
reduces downtime related costs by reducing the frequency and duration of incidents and outages.

Improved performance and availability: BigPanda’s Open Box Machine Learning-driven automation improves the performance and availability of critical applications by reducing outage frequency and duration.

CONSIDERATIONS GUIDE

Choose the right AIOps platform for your business with this simple guide

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Blackbox AI creates bottlenecks

Problem

Black-box nature of AI inhibits trust and adoption of AI-powered tools

The “blackbox” nature of AI technology makes it very hard for operators to trust insights and decisions made by AI, which in turn stifles adoption of AI tech in the enterprise.

Negative impact on the business:

Increased operating costs: When teams can’t trust AI-generated results, usage and adoption falter. Enterprises are challenged to realize the full ROI on their investments.

BigPanda’s solution

Open Box Machine Learning fosters trust in AI and spurs adoption

BigPanda’s unique Open Box Machine Learning technology provides AI explainability and drives unprecedented transparency, testability and control for operators and administrators. This helps users trust the results generated by BigPanda, adopt BigPanda, and help the enterprise rapidly realize the ROI on BigPanda.

Positive impact on the business:

Reduced operating costs: Because teams can trust the high-quality results generated by BigPanda’s transparent, testable and controllable Open Box Machine Learning technology, they quickly adopt BigPanda. This helps the enterprise rapidly realize the cost savings generated by BigPanda’s automation capability.

Automation: it can’t be all-or-none

Problem

All-or-nothing automation options are a problem

Many IT Ops tools offer a “0” or “1” option – which force enterprises to embrace automation everywhere or stick with a rules-based approach. Because enterprises may be at different stages of maturity OR different parts of the enterprise are at different maturity levels, they may want to adopt automation in a staged manner.

Negative impact on the business:

Decreased business velocity: As businesses transform, different business units and groups transform – and want to adopt automation – at their own pace. An all-or-none approach to automation prevents different BUs and groups from realizing the benefits of automation.

BigPanda’s solution

Adopt automation at your own pace

BigPanda’s automation capabilities can be adopted by organizations at their own pace, based on their level of process / workflow / org maturity. For example, some organizations may be ready for automated ticketing or sharing only. Others may be ready for automatic command execution by integrating with a 3rd party automation tool.

Positive impact on the business:

Increased business velocity: Business units and groups that need to move rapidly can embrace all aspects of BigPanda’s automation capability. Other units and groups can adopt it at a more measured pace. This speeds up enterprise business agility.

Our IT Operations team transitioned to working from home while experiencing a surge of new business—the likes we only see during Christmas and Black Friday normally. BigPanda helps us with a unified view of our IT environment from one console.”

— Ben Narramore
Sony Playstation Network

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