Operations | Monitoring | ITSM | DevOps | Cloud

Big tech companies are betting big on nuclear energy to keep their data centers running. With AI driving up energy use worldwide, it makes you wonder—could nuclear energy be the key to tackling the climate crisis caused by AI? Companies like Google and Microsoft have set ambitious sustainability goals by promising to move to 100% renewable energy before 2030. However, generative AI has made their goals difficult by increasing their electricity consumption multifold.

IT Operations teams must detect and address incidents quickly to ensure efficient operations and reliable IT infrastructures. As organizations grow and scale their service offerings, their IT environments inevitably become more complex. Filtering through alerts becomes increasingly challenging due to excessive noise and a lack of end-to-end visibility. As a result, IT operations teams are forced to escalate issues more frequently.

Just like in traditional software development, creating AI applications isn’t a one size fits all approach. However, many of the challenges and concerns facing AI/ML development teams share common threads – difficulties getting models to production, tangled infrastructure, data quality, security issues, and so on.