threshold : 0, // You can set threshold on how close to the edge ad should come before it is loaded. Default is 0 (when it is visible).
forceLoad : false, // Ad is loaded even if not visible. Default is false.
onLoad : false, // Callback function on call ad loading
onComplete : false, // Callback function when load is loaded
timeout : 1500, // Timeout ad load
debug : false, // For debug use : draw colors border depends on load status
xray : false // For debug use : display a complete page view with ad placements
console.log(“error loading lazyload_ad ” + exception);
Tackling increased complexity in the cloud space, startup YotaScale offers a predictive-analytics-driven platform for optimizing and managing cloud application operations.
The YotaScale Platform offers insights into cloud operations, so IT can take changing application needs into account. Services include anomaly detection, continuous optimization, predictive capacity planning, and contextual analytics such as for usage. The platform detects trends and diagnoses root causes of situations while suggesting fixes and making predictions about future usage patterns.
Underpinning YotaScale Platform is a machine learning pipeline tuned for three years on more than 500 petabytes of data across hundreds of enterprises. The platform is intended to address a series of issues:
YotaScale has been deployed primarily in the Amazon Web Services (AWS) cloud, and the company plans to move into Google Cloud Platform and Microsoft Azure.