In an ideal world, developers would be able to release new products and features from development environments into production extremely fast while also not having to stress about breaking prod. Achieving this combination of development speed while also maintaining software reliability requires having the right toolchain and automation in place.
Public cloud can deliver significant business value across infrastructure cost savings, team productivity, service elasticity, and DevOps agility. Yet, up to 70% of organizations are regularly overshooting their cloud budgets, minimizing the gap between cloud costs and the revenue cloud investments can drive.
Cloud cost anomalies are unpredicted variations (typically increases) in cloud spending that are larger than expected based on historical patterns. Misconfiguration, unused resources, malicious activity or overambitious projects are some of the reasons for unexpected anomalies in cloud costs. Even the smallest of incidents can add up over time leading to cost overruns and bill shock.
When it comes to IoT data, MQTT is a superstar. With so many IoT devices generating data out in the world, developers need ways to access it. After all, data lies at the heart of every application. But data doesn’t just magically manifest itself into your datastore, and building the right data pipeline can make or break an application. Data collection is not a one-size-fits-all problem to solve.
One of the key advantages of cloud services versus on premise deployments is the wide range of purchasing options and pricing models. While it’s an attractive advantage, it can be complicated for organizations to determine the best blend of service pricing models. The ability to define the organization’s blend of purchasing strategies and display the target versus actual performance is critical for optimizing cloud cost management efforts.
Companies are investing heavily in the cloud for the operational and financial benefits. But without a robust cloud cost management strategy in place, the complexity of cloud services and billing can to overspending and unnecessary cloud waste. Being able to accurately predict future cloud spend is one way to more optimize cloud spend and inform budgets.
