Operations | Monitoring | ITSM | DevOps | Cloud

Just flip on Netflix, and you can easily find a few dozen dystopian visions of a climate-ravaged future. As the standard storyline goes, the end of this century will see temperatures rise to ecologically disastrous heights, impacting billions of lives and changing living conditions forever.

Ever since the pandemic hit the world in 2020, many businesses and institutions have begun to adopt cloud computing into their operations. With more employees working from home, companies have moved from on-site data centers and chosen cloud computing services. Although cloud computing is not new, its relevance has increased during the last year and has revolutionized how businesses and institutions are operating now.

Recent data shows that the global APM (application performance management) market is booming. Currently valued at $6.3 billion, the global APM industry is expected to reach $12 billion by 2026. This growth indicates the increasing importance of monitoring, diagnosing, and improving application performance. Visibility and automation is key to sustaining the growth and evolution of APM.

One of the common challenges when doing performance testing is the difficulty of correlating the metrics of your application with your testing results. Having available QA, infrastructure, and application metrics together allows engineering teams to better understand the behavior of their systems during the testing, helping to detect and prevent potential issues in their applications.

Are your cloud costs out of control? Do you struggle with cost overruns or going over your cloud budget? Forecasting costs accurately can help you create a realistic cloud budget you can stick to and prevent cloud bill surprises. In this guide, we’ll cover why it’s so challenging to predict cloud costs and techniques you can use to create an accurate budget your organization will be able to maintain. Table Of Contents.

Let’s remember the time in the 2000s when companies introduced their cloud computing offerings at a large scale. New services were put into the popular IaaS, PaaS, and SaaS categories. New kinds of storage and messaging technologies were promoted. Also, novel approaches were discussed, such as designing applications for horizontal scalability and eventual consistency.

AWS Lambda is a serverless compute service that allows you to run code without having to manage servers. Lambda provides autoscaling and bills only on compute time, so you aren’t paying for unused resources. Some common use cases are file processing, stream processing, and acting as a backend for web and mobile applications. AWS Lambda functions can be invoked with external HTTP requests as well as by events triggered by over 200 different AWS services.

In the digital transformation era, any organization on its growth to glory must consider developing and investing in modernizing their application portfolios. That includes healthy competition, legacy modernization, and creating a unique identity from the rest of others. Moreover, advancements in technology have forced organizations to reconstruct themselves to the new normal. Application modernization is all about the process of repurposing or consolidating current business applications.

Over the last few years, multicloud frameworks have drifted into the mainstream. Organizations now create, store and manage enormous volumes of data across different cloud platforms. Despite the magnitude of this trend, there’s a stark and often disturbing truth: Businesses often have little or no visibility into much of the data that resides in these clouds. The culprit? Dark data.