Unlocking the full potential of monitoring through ML integration, anomaly detection, and innovative scoring engines. Machine Learning has been making waves in various industries, but its adoption in the monitoring and observability space has been slower than expected. Many “ML” features remain gimmicky and do not provide actual real world value to users that encourages their further use.
As more and more organizations undergo digital transformation, IT automation is becoming more important and essential to implement. A report by Smartsheet found that more than 40% of those surveyed spend about a quarter of their time working on repetitive tasks, and almost 70% of them say that automation’s biggest opportunity would be that it significantly reduces the amount of time spent on these tasks.
Whoever owns Reliability should define its parameters. But who owns the Reliability of a Product? Engineering? Product Management? Or the Customer success team?
Last month, the Singapore bank DBS experienced a 10-hour outage of its digital services. Not only was it massively disruptive to customers, but it caused the bank’s stock to lose 1.4% of its value in a single day. And it’s not the first time DBS has had to deal with the fallout of an IT snafu; in November 2021, Singapore’s finance regulatory body imposed significant additional capital requirements on the bank after its digital banking services were disrupted for two days.
Endpoint management is critical for IT teams. In a SANS survey they found that 44% of IT teams manage anywhere from 5,000 to 500,000 devices. With so many devices, it can be challenging to keep track of the health and status of each individual endpoint. So how can IT teams ensure that organizational endpoints continually contribute to the company’s success? Endpoint lifecycle management is a valuable process that can enable your team to achieve this.
There’s no doubt that the majority of businesses and organizations would struggle to survive without endpoints. Because endpoints directly contribute to a business’s production and success, ensuring that these devices function at peak performance is a top priority for IT teams and MSPs. However, the number of endpoints an organization uses is skyrocketing, and now the average enterprise has approximately 135,000 endpoint devices in use.
Today, “76% of businesses use automation for standardizing or automating daily workflows,” Paperform states. This number will only continue to grow, especially for organizations in the tech industry, such as MSPs. Automation opens new doors for MSPs, allowing them to outperform competitors, save time, lessen heavy workloads, and even increase profits. Learn how your MSP can automate everyday processes to receive all these benefits and more.
Digital transformation and the increase in remote work accelerated the use of multiple technologies in the workplace. These circumstances led to various challenges and increased the urgency to find solutions. Two of the top challenges faced by IT management are accurately assessing IT needs and finding skilled technical staff. Also, in a survey conducted by NinjaOne, it was reported that 87% of organizations saw an increase in the number of new devices the previous year.
