On October 4, Facebook and its properties, Instagram and WhatsApp, were down for more than five hours due to configuration changes on routers in Facebook’s data centers. A five-hour outage is an eternity in our always-on digital economy, costing the company an estimated $65 million and 4.8% in stock valuation. The high-profile Facebook outage is emblematic of just how digitally intermediated our economy is becoming, and the incident renews C-level focus on preventing similar service failures.

SaaS is exploding and so it should; it takes commoditized work and infrastructure away from tech teams so that they can focus on differentiating features. But what happens when it goes wrong? How do SaaS platforms make sure they aren't letting their customers down and in turn, letting their customers down? Observability, bolstered with AI gives all the partners the best chance to optimize availability and customer experience. Here's how.

At DevWeek Austin, we discussed how AI and ML have come to the DevOps toolchain and are a great fit! Here are the 3 main takeaways.

Burnout from work is proven to have a tangible impact on your physical health and happiness. Learn how to recognize burnout in yourself and your employees, and build a happy developer culture!

IT operations data grows by the year. Some estimates suggest that the average IT operations team watches their operational data volume double or triple every year. The result of this flood is that IT teams are grasping for any method they can find to make sense of all this data. Many teams are landing on AIOps as their solution to parse and categorize all of these events. AIOps isn’t a perfect fit for every organization, but it is a great fit for many.

The AIOps market is flourishing and the new year is coming up, so let’s take a look at the top 3 trends to watch out for in 2022.

CloudFabrix solution provides a holistic approach for enterprises to implement proactive operations with the objective of eliminating/reducing critical incidents and improving customer satisfaction. The solution primarily relies on applying regression/forecasting models on any time-series data to detect and forecast anomalies. One of the unique features of the solution is the ability to convert unstructured data such as logs/incidents/alerts into time-series data to be used for running prediction models.