This year we all watched -- for numerous days -- as two hurricanes set their sights on the United States. We can collect data from weather patterns and satellite images in these modern days, to help us fairly accurately predict the weather and prepare for these natural disasters. In analyzing this data the people in the path of the storm can be notified and can prepare so there is less of an impact on them.
Frankly, we need similar, better forecasting platforms for our IT systems. And they're starting to surface in new ways. IT monitoring services already collect a ton of data. How this data is interpreted, analyzed and used to help organizations has generally been up to the organization. Traditionally, IT monitoring solutions have been great at notifying managers of issues as they occur, but these notifications are usually too late to prevent an impact to end users.
Datadog Launches Forecasts
With those needs in mind, cloud monitoring upstart Datadog has launched Forecasts, a new feature that predicts when performance and stability issues will occur within cloud applications.
According to the company, by applying machine-learning algorithms to massive amounts of data, Datadog can generate predictive analytics on everything from application performance to custom business metrics. They claim that this will reduce uncertainty and increase efficiency for businesses, putting the focus on actionable insights instead of troubleshooting problems after customers have already been impacted.
Datadog's Forecasts show users how to:
- Prepare for the future - Graphs are able to show the approximate date that a server will run out of space if the data continues to grow in the same manner, and you can set notifications to alert you a certain amount of time prior to the end date so you can prevent the critical load before it happens.
- Account for seasonality - Much like how busy the gym gets in January and then tapers off throughout the year, the Forecasts feature takes into account the seasonality of your business. The report can show you when your business is likely to require more resources during the times of year that your business spikes.
- Adapt to baseline shifts - If a metric suddenly changes in value, the forecasting algorithm will automatically analyze the most recent behavior to create a reliable prediction.
- Forecast critical business metrics - Predict how critical business metrics are likely to change, such as how many active users you will have at any given time.
- View from one location - Add forecasts to your dashboards and you will be able to see the health and performance of your services, by combining historical trends with future insights.
When a business is down, they are usually unable to generate revenue. By applying machine learning like the Datadog's Forecasts, businesses can attempt to prevent downtime and plan and prepare for impending disasters, much like preparing for a hurricane.
Datadog Partner Program
Poke around Datadog and you'll hear about the company's rapid growth (ask them sometime...). The company has a growing partner program, led by Oracle and New Relic veteran John Gray, that's attracting all types of MSPs. But the company also faces intense competition from entrenched rivals and hungry startups. Key rivals include Cisco's AppDynamics, New Relic, and a long list of application performance monitoring (APM) and infrastructure monitoring companies.
PS: Keep an eye on ChannelE2E. We'll be posting some new insights from Gray in early January or so...
Additional insights from Joe Panettieri.
