The Monitoring and Observability Markets are Obsolete

The digital age is now. Advances in cloud and AI technologies offer intelligence capabilities that far surpass traditional monitoring and observability solutions that are now:

• Limited in scope. Focusing on identifying issues after they occur, rather than predicting and preventing them.
• Reactive. Needing human intervention to investigate and address problems, leading to delays and waste.
• Expensive. Implementing and maintaining separate monitoring and observability tools can be costly—and most people have many.

Cloud Intelligence is here now. You already have access to massive amounts of data from targeted workloads. Massive amounts of compute processing power and AI are available. The building blocks to combine wide and deep data from thousands of cloud workloads and create models on a single AI platform exist today. The result?

• Predictive incident management and autonomous issue mitigation
• Actionable insights to accelerate flow and reduce waste
• Unparalleled customer experience through customer sentiment determination
• Highly accurate predictions for health, compliance, and security
• Reduction in TCO by accessing low-cost computation

When combined with Business Intelligence it adds operational insights and improves clarity, alignment, and governance. It enables insight-driven decision-making across and between all business areas—sales and marketing, HR, finance, GRC, operations, and technology. Make technology your business.

Cloud Intelligence helps digital businesses identify, discover, and recover from a wide range of events including hardware failure, software bugs, and vulnerabilities, drops in brand loyalty, and supply chain or distribution issues. The combination of cloud workload data and AI instructs autonomous mechanisms to investigate, identify, mitigate, and prevent the events now and in the future through the platform itself or connected external solutions.

When you have the machine intelligence to handle data from billions of workloads over time periods and create models, the possible patterns, predictions, and solutions are infinite. Metadata enriches the training data. Forecast models are shared between organizations across industries and fine-tuned by the business using them. Teams subscribe to updates to the models they are using and continue to fine-tune their patterns and predictions based on their own curated workload data.

Cloud Intelligence Use Cases

SLA and contract negotiations

Setting your customers’ expectations correctly is fundamental to your success and ensuring you keep your promises keeps your business healthy. You need to know if there’s any risk to you meeting the Service Level Agreements you’ve set with your clients and, if there is, how to mitigate it fast.

Competitive analysis

You want to disrupt, not be disrupted. But if you do get disrupted, you want early warning of what’s happening and actionable insights to guide your response. You want to be able to easily compare how products and services similar to yours are being used. You want to know where your competitive edge lies and where your business growth is being limited.

Buyer behavior changes

Your buyers can seem unpredictable but often it’s possible to forecast how they will behave based on their likely responses to external events. Mortgage applications will go down if interest rates go up, and lettuce sales increase when the sun shines. You need enough warning to change inventory, shipping, pricing, and plans.

Crisis response

You don’t know when something catastrophic is going to happen but you do need to be able to react when it does. You need to quickly identify how the adverse situation is affecting your customers’ experience and act to respond to the changing environment. All of these use cases require a common set of steps, all of which are already in motion.
You just need to direct your forecast models and act accordingly. The patterns are:

1. Collect data
2. Understand usage pattern
3. Solve your specific problem

Some use cases, like these examples, fit many businesses. Some are unique to you—like the differentiating features you design for your customers.

Data leads to patterns and their events. Data, patterns, and events build and teach models. Models learn to identify patterns from data. Patterns predict events. You have a chance to be ready for those adverse events—to prepare for them, pre-empt them, and prevent them.

Cloud Intelligence reveals previously unseen patterns, predictions, and their predicted outcomes. Traditional monitoring and observability solutions cannot help you discover these outcomes because they have boundaries that limit them. These outcomes relate to your customers’ experiences, your ability to execute your business strategy, and your competitiveness. Your ability to harness and use your data to predict and manage events determines your place in the digital economy. It predicts your organizational performance. Cloud Canaries are Cloud Intelligence. Develop, share, or purchase Canaries. Deploy your Canaries where you need them. Canaries gather data for models to learn and predict events. Canaries perform corrective actions. Initiate new Canaries to collect more data. Canaries are key to Cloud Intelligence.

We are currently testing our latest version – reply to this post or message me if you want to get on our free pilot program.