Both Graphite and InfluxDB are time-series monitoring data platforms, both of which have high levels of adoption throughout many industries. Both of them are suitable for enterprise use, are scalable, and are stable. That being said, there are some benefits and drawbacks to each. While InfluxDB has many benefits, many developers still prefer Graphite due to its large community, stability, and reliability.

We recently took a look at some of the repercussions of the global pandemic and how it has caused a dramatic shift in the way we work. In the second instalment of our predictions for 2021, we explore some of the longer term trends that will be top of mind for enterprises this year…

Using the cloud reduces on-premises infrastructure costs and related maintenance. Instead of deploying more servers, storage, and networking components to your own datacenter, you are now deploying these as cloud resources. Using the cloud is supposed to reduce infrastructure and maintenance costs. However, deploying cloud resources also risks over-commissioning, under-usage, and keeping resources running that are not always needed or, even worse, no longer in use.

How do you handle deployment failures with a single-tenant database architecture? We’ve had a question come up from a couple of customers regarding an interesting use case with Redgate’s SQL Change Automation. In this scenario, customers say: A natural question that arises is what to do when a deployment fails against a single database. For example: One approach that seems simplest to folks is wrapping the entire multi-database deployment into a single transaction.

Building Site Reliability Engineering (SRE) teams is hard! There are so many articles and explanations of what SRE means, it’s easy to get lost. Going beyond understanding what the individual SRE role is into building and scaling a team of SREs is more of a challenge. It’s important to find the right information that will help you take your SRE team to the next level.

Although it is not well known to the general public, virtualization technology is widely used in technical environments for being useful when carrying out multiple tasks and for the possibilities it offers for better resource usage. Virtualization technology software is increasingly used by professionals in the sector, having already become an essential tool for the work of many of them.

How does one manage monitoring in the age of digital infrastructure as code? Also as code, of course! Combining HashiCorp Terraform Cloud and Checkly enables you to configure synthetic and API monitoring as part of your existing infrastructure codebase. It is flexible, programmable and will keep you out of maintenance hell, even at scale: it is monitoring for developers. Extending your existing Terraform Cloud configuration takes only two minutes. Let's take a look together.

Should you run big data workloads on Kubernetes? Not so long ago, most people would have said certainly not. Among the reasons you might have heard: Although early adoption of Kubernetes was dominated by stateless services rather than data-centric applications, more and more teams responsible for big data platforms are now looking to adopt Kubernetes, especially those looking to deploy and operate big data workloads in the cloud.

At the beginning of 2020, none of us could have imagined what we would be talking and thinking about at the end of the year. At JFrog, we began by talking about unifying everything in the DevOps lifecycle. Of course very quickly, the message of unity and togetherness would soon become even bigger than we could imagine in light of the global pandemic.

Ketch (https://www.theketch.io) is an open-source application delivery framework for Kubernetes. YAML is a human-readable data-serialization language. It is commonly used for configuration files and in applications where data is being stored or transmitted. Customized YAML files are used by many for the complicated task of deploying to Kubernetes.