Operations | Monitoring | ITSM | DevOps | Cloud

In this blog, we look at the importance of viewing Azure end-to-end transactions from the perspective of a business user, the overall benefit of Business Application Monitoring, and how Serverless360 BAM can help your organization by providing business insights in your Azure integration transactions.

Email marketing is effective when done right. Since emails go through a complex journey after we hit ‘Send,’ we need to know what happens as they travel. Behind the scenes, an email goes through a complex journey that consists of several steps. And each step is defined by the email protocol being used. Depending on the email protocol, our emails will go through more or fewer stages before they reach the recipient's inbox. Keep reading to see email protocols explained.

In our 2022 year in review, we recapped the six highly-requested features that were implemented over the course of the year. We also acknowledged the five highly-requested features that “got away” – meaning we hadn’t gotten to them… yet! Well, GitKraken Client 9.1 is here, we’re happy to share that two of those enhancements are now accounted for, along with other user-requested features and improvements that represent input from over 1,000 users.

Kubernetes is a powerful platform that comes with many features to help engineers run their applications more efficiently. However, as you gain more experience and deploy more workloads, you’ll inevitably start looking for ways to optimize Kubernetes performance. There are many ways to approach optimization. On one hand, you could work exclusively with the tools and configurations provided by Kubernetes itself; on the other, you could reap the benefits of third-party tools.

The adoption of AI/ML in financial services is increasing as companies seek to drive more robust, data-driven decision processes as part of their digital transformation journey. For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year. But productionising machine learning at scale is challenging.

Hey folks! We are super excited to announce that our schedules feature has gone through a bit of an update. Well, more than a bit 🙂. We’ve gone through the feature with a fine-toothed comb and introduced a bunch of UI and functional improvements which we hope will help you achieve one thing: set up, edit and manage your on-call schedules at scale in a matter of minutes (Yes, that was three things but it was tough to condense it to ONE thing)

The first post in this series introduced the idea of the different layers of value that your business can gain from frequent deployments and focused on the hard costs you can save. We’re looking at the role the database plays here because it’s the most complicated part of the process and it’s difficult to hit aggressive KPIs and goals when your teams are burdened with process bloat due to mistake-prone, manual work.