Operations | Monitoring | ITSM | DevOps | Cloud

Tencent Cloud is among a number of Chinese tech giants making an impact in the enterprise cloud sector. In this blog, we look at how businesses can maximise the potential of their Tencent Cloud instance using direct connections through Console Connect.

Rolled out in 2011, AWS ElastiCache has grown to become one of the most prominent Amazon services among developers. So much so that in the 2020 Stack Overflow Developer Survey, one of its fully-managed engines was voted by developers as the most loved database. On the flip side, however, AWS ElastiCache happens to be infamous for its high costs. Although it offers a flexible pricing system that charges you only for what you use, the usage bill can get pretty high for some users.

A lot of people think that using the cloud makes you elastic, but cloud really only gives you the potential to be elastic. If your apps aren’t elastic, and your cloud usage doesn’t flex up and down based on activity levels, then it’s really just expensive. The same is true of containers—they don’t magically make all of your hosting problems go away, and while they have the potential to make you more agile and efficient, it isn’t that simple.

Serverless applications, more often than not, have logic distributed over multiple functions and services, which with growth and agents and wrappers attached, can get more complex and costly. This is where Serverless monitoring comes in to help. But what is Serverless monitoring? Serverless monitoring allows developers to gain important insight on what happens during each execution and event, errors become more easily visible, and measuring resource consumption for each invocation is possible.

2020 has seen a surge in the number of organizations embracing remote work to adapt to the new normal, leading to increased reliance on digital collaborative workspaces like Microsoft Teams. As organizations migrate critical business processes to such digital workspaces, IT service management teams need to leverage these platforms as channels for delivering IT and enterprise support.

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.