Operations | Monitoring | ITSM | DevOps | Cloud

Applications fail. Containers crash. It’s a fact of life that SRE and DevOps teams know all too well. To help navigate life’s hiccups, we’ve previously shared how to debug applications running on Google Kubernetes Engine (GKE). We’ve also updated the GKE dashboard with new easier-to-use troubleshooting flows. Today, we go one step further and show you how you can use these flows to quickly find and resolve issues in your applications and infrastructure.

People sometimes think that implementing Site Reliability Engineering (or DevOps for that matter) will magically make everything better. Just sprinkle a little bit of SRE fairy dust on your organization and your services will be more reliable, more profitable, and your IT, product and engineering teams will be happy. It’s easy to see why people think this way. Some of the world’s most reliable and scalable services run with the help of an SRE team, Google being the prime example.

2020 was indeed challenging for Kovai.co still had great learning! One of them is what I am sharing with the community through this blog. For enterprises like us, worldwide work from anywhere became the new reality. We had to move towards a cloud-native world where secure data storage and effective remote management of IT infrastructure were of supreme importance.

It’s no secret that AWS bills are confusing. But it’s particularly difficult for the team who actually writes the check to Amazon for hundreds of thousands or millions of dollars — yet has never personally seen what the inside of the AWS portal looks like (and probably never will).

Software deployment tools allow developers to ensure that software is properly installed with it’s required packages and implementation steps conducted in the correct order. Using these tools is a vital requirement for any business that creates its own software in-house. There is a variety of software that can assist developers in launching their latest code with new ones (such as GitHub Actions) arriving to the forefront of many growing consideration lists.

Say you’re looking for a smart product to detect anomalies in your organization’s IT environment. A sales rep drops by and shows you all kinds of great artificial intelligence (AI) features with fancy-sounding algorithms. It sounds very impressive and seems like there is a lot of very valuable AI in the product. But, in fact, the opposite is true. This is a manual AI product wrapped in a deceiving jacket. Let me tell you more.